INTERBLOCK CRANE SCHEDULING AT CONTAINER TERMINALS

Size: px
Start display at page:

Download "INTERBLOCK CRANE SCHEDULING AT CONTAINER TERMINALS"

Transcription

1 INTERBLOCK CRANE SCHEDULING AT CONTAINER TERMINALS Omor Sharif University of South Carolina Department of Civil and Environmental Engineering 00 Main Street Columbia, SC 0 Telephone: (0) -0 Fax: (0) omor.sharif@gmail.com Length of paper: Text = 00 words, Number of Figures = ; Number of Tables = ; Total = 0 words Submission Date: April, 0 0 0

2 ABSTRACT It has been recognized that efficiency in yard operations are critical for the overall productivity of the container terminal. Yard cranes are popular and frequently used equipment for handling, reshuffling and managing flow of containers in a yard. An efficient deployment plan for these cranes is required in response to the varying workload among yard blocks in different planning periods. This project studies an algorithm and mathematical model proposed in literature to address the crane deployment problem. The crane deployment problem is, given the forecasted workload of each block in each period of a day, assign the crane among blocks dynamically so that the total unfinished workload in the yard is minimized. Keywords: Rubber tired gantry crane, container terminal, scheduling, yard operations. 0

3 Sharif INTRODUCTION AND PROBLEM STATEMENT The globalization of trade and subsequent growth of containerization for transporting goods in containers have brought many difficulties and challenges in marine terminal operations. Capacity constraints, lack of adequate decision making tools, congestion and environmental concerns are some of the major issues faced by the container terminals today. Increasing containerization has also resulted in increased complexity in planning for terminal managers to provide satisfactory customer service and maintain terminals competitiveness. Various operations research optimization techniques, automated equipment and information technology have become indispensible for efficient management of marine terminal operations and to attain high productivity in container flow with limited resources. Marine terminal operations involve various logistics processes and deployment of expensive resources. Thus efficient decision making is imperative in each process to obtain optimum results. This project addresses an important planning problem in container yard operation. It has been recognized that efficiency in yard operations are critical for the overall productivity of the terminal. The efficiency and quality of management is the container yard operations affect all terminal decisions, related to the allocation of available handling equipment and the scheduling of all activities (Rashidi and Tsang, 00). The storage yard at a container terminal serves as a temporarily storing area for containers before they are picked up by a truck from the land side or they are ready to be loaded into a vessel. Since large terminals have a sizable land space for storage, the yard is typically divided in multiple yard zone and each yard zone is further divided into multiple rectangular shaped yard blocks. Each block contains several lanes of space for storing containers in stack, movement of cranes and parking of transport vehicles for pickup/delivery operations. Figure shows a sample layout of a container terminal with two yard zone and six yard blocks in each yard zone. One very popular equipment used for loading, unloading, rehandling/reshuffling of containers in container yard is Rubber Tired Gantry Crane (RTGC). RTGCs are popular and more frequently used in large terminals with high container flows and other automated technologies (Henesey, 00). An RTGC travels on rubber tired wheels spanning over a yard block width. Figure shows an RTGC standing over a lane yard block. Compared to Rail Mounted Gantry Cranes (RMGCs) which can only travel in one direction across the stacks, RTGCs offer more flexibility since they can be transferred to different blocks as required. Since the workload among the blocks varies throughout the day, the deployment of RTGCs is an important decision making problem the terminal managers have to consider. An efficient deployment plan is necessary to address variable workload demand and is imperative for overall productivity of yard operations and other related processes in a container terminal. This project studies the algorithm and mathematical model proposed by Linn et al. (00) to address the crane deployment problem. The crane deployment problem is, given the forecasted workload of each block in each period of a day, assign the crane among blocks dynamically so that the total unfinished workload in the yard is minimized.

4 Sharif FIGURE A layout of a container terminal (Linn et al, 00). FIGURE RTGC moves on rubber tired wheels spanning over seven lanes of space or a block space. Each block has seven lanes of spaces: six lanes for container storage and one lane for tracks (Linn et al, 00).

5 Sharif BACKGROUND AND LITERATURE REVIEW There is a vast amount of literature in the area of marine container terminal modeling. With container terminal operations becoming more and more important, an increasing number of publications on container terminals have appeared in the literature. A comprehensive review of previous work is beyond the scope of this paper. For a comprehensive survey of container terminals related research, see Vis and Koster (00), Steenken et al. (00), Stahlbock and Vob (00), Crainic and Kim (00), Murty et al. (00), Rashidi and Tsang (00), Vacca et al. (00), Henesey (00). The following review is limited to published works that pertain to yard crane scheduling at seaport container terminals. Also, it should be noted that, in general, there are two types of cranes deployed at a container terminal; namely yard cranes and quay cranes, both of which have been studied extensively. In subsequent discussions, the term crane refers to yard cranes unless stated otherwise. Zhang et al. (00) addressed the dynamic crane deployment problem where given the forecasted workload of yard blocks in each period of a day, the objective is to find the times and routes of crane movements among yard blocks so that the total delayed workload in the yard is minimized. A mixed integer program (MIP) was developed and solved using Lagrangean relaxation. Interblock crane deployment has also been studied by Cheung et al. (00), Linn et al. (00) and He et al. (0). However, these studies do not stipulate detailed work flow for the cranes in serving the trucks. Kim et al. (00b) studied various truck serving rules using simulation to minimize truck delay. The sequencing rules comprise dynamic programming, first-come-first-served, unidirectional travel, nearest-truck-first-served, shortest-processing time rule, and a rule set from reinforcement learning. Ng and Mak (00) studied the problem of scheduling a yard crane to handle a given set of jobs with different ready times. They proposed a branch and bound algorithm to solve an MIP that finds an optimal schedule that minimizes the sum of truck waiting times. In a follow-up study by Ng (00), the author extended his previous work to deal with multiple yard cranes instead of a single yard crane. His model accounted for interference among cranes which may occur when they are sharing a single bi-directional traveling lane. An integer program was proposed and a heuristic was developed to solve the model. Although this work focused on the yard crane scheduling problem to expedite vessel operations, the proposed model and solution methodology are applicable to drayage operations. In contrast to inter-block deployment studies the study provides detail schedule for handling of individual containers. Lee et al. (00) studied the scheduling of a two yard crane system which serves the loading operations of one quay crane at two different container blocks, so as to minimize the total loading time at stack area. A simulated annealing algorithm was developed to solve the proposed mathematical model. Li et al. (00) developed a crane scheduling model where operational constraints such as fixed yard crane separation distances and simultaneous container storage/retrievals are considered. The model was solved using heuristics and a rolling-horizon algorithm. Most of the existing studies that address the yard crane scheduling problem have taken the centralized approach which employs mathematical programming models such as integer programs or mixed integer programs. On the other hand a very few studies employed decentralized approaches such as agent-based modeling which is a relatively new research field within the realm of artificial intelligence. Huynh and Vidal (0) and Vidal and Huynh (0) introduced an agent-based approach to schedule yard cranes with a specific focus on assessing

6 Sharif the impact of different crane service strategies on drayage operations. In their work, they modeled the cranes as utility maximizing agents and developed a set of utility functions to determine the order in which individual containers are handled. 0. METHODOLOGY The container yard operational hours in this study is assumed to be composed of three shifts a day. Each shift can be further divided into two planning periods each of hours length to better manage the varying workload throughout the day. Thus in this study a day is partitioned into six planning periods: 00:00 :00, :00 :00, :00 :00, :00 :00, :00 0:00, and 0:00 :00. Typically, at each day an estimate of the workload for the next day at each block of the yard is available. For safety considerations, a maximum of two RTGCs are deployed per block to handle containers. Though, it is possible to move the RTGCs among different blocks as required, frequent transfers may lead to traffic congestion, the maximum number of interblock movement of an RTGC is kept limited to once each period in this implementation. Two types of RTGC movements can be distinguished based on the time required for the movement. The first type of movement is between adjacent blocks where an RTGC does not need to turn its wheels because origin and destination blocks share the same traveling lane. The second type of movement is between parallel blocks where an RTGC needs two 0 degree turn of wheels because the origin and destination blocks have different travel lanes. The latter type of movements requires additional time. We assume that first type of movement takes minutes and second type of movement takes an extra minutes ie minutes. For instance, in Figure, to transfer an RTGC from block W to W, minutes transfer time is assumed. If an RTGC is transferred from block W to W or W, minutes of transfer time is assumed. 0 FIGURE RTGC transfer time between two blocks (Linn et al, 00). If the expected number of moves to be performed in each block is known, the expected workload can calculated using the following formula in term of crane time units. Workload (crane time units) in a block = Number of moves in the block x Average time required for each move The objective of RTGC deployment is to minimize the remaining workload (overflow) from one period to the next. To simplify the deployment problem, three types of blocks can be distinguished. They are sink blocks, source blocks and neither blocks.

7 Sharif a) Sink blocks: Sink blocks meet the following criteria- Workload > Crane Capacity and Number of Cranes available < Thus sink block needs and can take additional RTGCs. b) Source blocks: Source blocks meet the following criteria- Workload < Crane Capacity and Number of Cranes available Thus source block have extra capacity and can take spare RTGCs. c) Neither blocks: Neither blocks meet the following criteria- Workload = Crane Capacity or Workload > Crane Capacity and Number of Cranes available = Since neither blocks do not need or cannot receive RTGCs, they are discarded from analysis to save computation time. RTGCs can be transferred from source blocks to sink blocks after completion of work in their current block as to spend the extra capacity in sink blocks. However, since this transfer involves travel time between blocks, extra crane minutes available must be greater than travel time, otherwise a transfer is not allowed. Some parameters are defined first for algorithmw i The total workload of block i in the beginning of a period. r i The number of RTGCs in block i at the beginning of the period. T c The total crane-minutes/crane/period. T c =0 for a -hour planning period. N c the maximum number of cranes allowed in each block at any time. N c = for the current case. The deployment algorithm is implemented in two steps. They are ) presort step and ) RTGC deployment step.. Presort step identifies eligible RTGC and sink blocks: For i =, n. If w i T c r i and r i = N c ; remove block i and its RTGCs from further consideration.. If w i = T c r i, remove block i and its RTGCs from further consideration.. If w i > T c r i and r i < N c, make block i a sink block with unfulfilled workload, w i = w i - T c r i. Its RTGC needs to stay in the block for the entire period and is therefore, removed from further consideration.. If w i < T c r i ; then remove the block from further consideration, but it has v i = T c r i - w i excessive RTGC-minutes available. Set n a = Integer(v i /T c ) +.Make n a RTGCs in the block available. If (v i /T c ) ; make one of the RTGCs in the block eligible with v i minutes (i.e. if this RTGC is selected for transferring to new block j, it will begin its transferring immediately after completing w i = T c r i - v i minutes in block i). If < (v i /T c ) ; make two RTGCs currently in the block eligible. One of them can be transferred after completing o i minutes work, and the other can go after completing p i minutes of work in the block i; where o i + p i = w i and o i 0 and p i 0:

8 Sharif If < (v i /T c ) ; make three RTGCs in the block eligible. One can be transferred after completing o i minutes work; the second crane can go after completing p i minutes of work in the block i; the third crane can go after q i minutes where o i + p i + q i = w i and o i, p i, q i 0, etc.. RTGC deployment step identifies the optimal deployment plan for the source and sink blocks. Let: N number of eligible RTGCs. M number of sink blocks. u + i amount of work overflow in block i to next period. u - i amount of work underflow in block i to next period. w i unfulfilled workload (in RTGC-minutes) at sink block i: v j crane-minutes available from eligible RTGC j: S j set of sink blocks to which eligible RTGC j can be transferred. T i set of all eligible RTGCs, which can move to sink block i: c ij travelling time in minutes to go from the block where RTGC j is to block i: γ i = if sink block i has one RTGC stationed in it currently; = if sink block i has zero RTGC stationed. The mathematical program is presented below- 0

9 Sharif 0 In the optimum solution of this model, the y ij provides the optimum deployment of the eligible cranes that minimizes the total amount of work overflow to next period. Constraints () are to insure that one crane will be moved to only one sink block. Constraints () insure that cranecapacity brought into a sink node would be same as the additional crane-capacity needed. Constraints () are to insure that there will be not more than two cranes in each block. Constraints () are nonnegativity constraints and Constraints () are the binary constraints. For the sink blocks i = to M; u i is the amount of work overflow to the next period. These values are to update the workloads of each block for the next period before repeating the deployment algorithm for the following period.. IMPLEMENTATION AND RESULTS The presorting step of the crane deployment algorithm was carried out in Microsoft Excel. Excel is suitable to organize data such as system s initial condition, layout of blocks, workload at each block at different planning period, number of RTGCs initially deployed and transfer time of RTGCs etc. The optimal RTGC deployment step, which is a mixed linear integer program, was implemented in CPLEX, an optimization programming environment developed by IBM ILOG Corp. The solution to a small problem by applying the crane deployment algorithm will now be presented. The sample problem has four yard blocks and their layout is as shown in Figure. BLOCK ( RTGCs) BLOCK (0 RTGCs) BLOCK ( RTGCs) BLOCK (0 RTGCs) FIGURE Block layout for the sample small problem

10 Sharif TABLE Data for the sample problem Block Workload Initial Crane ID (minutes) RTGCs Capacity Note Eligible RTGCs Unfulfilled Workload Extra Crane Capacity w i T c *R i w i ' v j 0 0 Source 0 0 Sink 0 Source Sink Total 00 0 Capacity> Workload Table shows the workload data and initial RTGC assignments at the beginning of a -hr planning period for the four blocks in the studied problem. In fact, the yard operation planner can establish the initial number of RTGCs based on discretion. The only constraint to be ensured is that total number of assigned RTGCs cannot exceed the total available RTGCs and not more than two RTGCs can be assigned per block. The number of RTGCs in each block at the end of the planning period can be treated as the initial number of RTGCs at the beginning of next planning period and the deployment algorithm can be repeated until all six periods in a day is covered. For the sample problem, Table identifies the source and sink blocks and number of eligible RTGCs from each source block. The unfulfilled workload for each sink block and extra crane capacity available from the eligible RTGCs are also shown. Also the transfer times of eligible cranes to sink blocks (c ij ) are shown in Table. TABLE RTGC transfer time for the sample problem Transfer Time Minutes c ij c c c c TABLE Optimal solution for the sample problem Parameter Value Objective u + u + 0 u - 0 u - y, y We assume that the eligible RTGC from block is j= and the eligible RTGC from block is j=. Also, the sink block is i= and sink block is i=. At this point, presort step is done and the data is available to be fed into optimal deployment model. The optimal solution is shown in

11 Sharif Table. The crane from block is moved to block and the crane from block is moved to block after finishing their respective share of workload in their origin block. The total overflow of workload at the end of planning period is minutes. The crane experiences as minutes of idle time at block. The algorithm appears to be very efficient in computational time.. CONCLUSION Yard cranes are popular and frequently used equipment for handling, reshuffling and managing flow of containers in a yard. An efficient deployment plan for these cranes is required in response to the varying workload among yard blocks in different planning periods. This project studies an algorithm and mathematical model proposed in literature to address the crane deployment problem. The deployment algorithm was tested on a sample small sized problem and the results were shown. An efficient reallocation of RTGCs to other blocks when no more workload exists in their block can be achieved using the developed mixed integer program. However, the proposed model can be improved in several ways for performance. For example, one RTGC can be moved out earlier than the other RTGC without sharing workload all the way (when two RTGCs exist in a source block). Also, a RTGC can be relocated more than once in a planning period. Furthermore, the algorithm considers one planning period at some time whereas considering multiple planning periods together may offer better RTGC assignment strategies. Also, the detail workflow for each container move within a block is not addressed in this study. REFERENCES Cheung, Raymond K., Chung-Lun Li, and Wuqin Lin. "Interblock Crane Deployment in Container Terminals." TRANSPORTATION SCIENCE, no. (00): -. Crainic, Teodor Gabriel, and Kap Hwan Kim. "Chapter Intermodal Transportation." In Handbooks in Operations Research and Management Science, edited by Barnhart Cynthia and Laporte Gilbert, -: Elsevier, 00. He, Junliang, Daofang Chang, Weijian Mi, and Wei Yan. "A Hybrid Parallel Genetic Algorithm for Yard Crane Scheduling." Transportation Research Part E: Logistics and Transportation Review, no. (0): -. Henesey, L.E. "Multi-Agent Systems for Container Terminal Management." (00). Huynh, N. " An Agent-Based Approach to Modeling Yard Cranes at Seaport Container Terminals." Paper presented at the Proceedings of the Symposium on Theory of Modeling and Simulation., 0. Kim, Kap Hwan, Keung Mo Lee, and Hark Hwang. "Sequencing Delivery and Receiving Operations for Yard Cranes in Port Container Terminals." International Journal of Production Economics, no. (00): -.

12 Sharif 0 0 Lee, Der-Horng, Zhi Cao, and Qiang Meng. "Scheduling of Two-Transtainer Systems for Loading Outbound Containers in Port Container Terminals with Simulated Annealing Algorithm." International Journal of Production Economics, no. (00): -. Li, Wenkai, Yong Wu, M. E. H. Petering, Mark Goh, and Robert de Souza. "Discrete Time Model and Algorithms for Container Yard Crane Scheduling." European Journal of Operational Research, no. (00): -. Linn, R., J. Liu, Y. Wan, C. Zhang, and K.G. Murty. "Rubber Tired Gantry Crane Deployment for Container Yard Operation*." Computers & Industrial Engineering, no. (00): -. Moorthy, R., and C.P. Teo. "Berth Management in Container Terminal: The Template Design Problem." OR Spectrum, no. (00): -. Ng, W. C. "Crane Scheduling in Container Yards with Inter-Crane Interference." European Journal of Operational Research, no. (00): -. Ng, W. C., and K. L. Mak. "Yard Crane Scheduling in Port Container Terminals." Applied Mathematical Modelling, no. (00): -. Rashidi, H., and E.P.K. Tsang. "Container Terminals: Scheduling Decisions, Their Formulation and Solutions." Submitted to the Journal of Scheduling (00). Stahlbock, Robert, and Stefan Voß. "Operations Research at Container Terminals: A Literature Update." OR Spectrum 0, no. (00): -. Steenken, D., S. Voß, and R. Stahlbock. "Container Terminal Operation and Operations Research-a Classification and Literature Review." OR Spectrum, no. (00): -. Vacca, I., M. Bierlaire, and M. Salani. "Optimization at Container Terminals: Status, Trends and Perspectives." 00. Vidal, JM, and N Huynh. "Building Agent-Based Models of Seaport Container Terminals." Paper presented at the In Proceedings of th Workshop on Agents in Traqffic and Transportation, 0. Vis, Iris F. A., and René de Koster. "Transshipment of Containers at a Container Terminal: An Overview." European Journal of Operational Research, no. (00): -. Zhang, Chuqian, Yat-wah Wan, Jiyin Liu, and Richard J. Linn. "Dynamic Crane Deployment in Container Storage Yards." Transportation Research Part B: Methodological, no. (00): -.

Management Science Letters

Management Science Letters Management Science Letters 2 (202) 7 80 Contents lists available at GrowingScience Management Science Letters homepage: www.growingscience.com/msl Investigating transportation system in container terminals

More information

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. Title Deciding on planning windows by partitioning time for yard crane management in container terminals Author(s)

More information

Simulation-Based Dynamic Partitioning of Yard Crane Workload for Container Terminal Operations

Simulation-Based Dynamic Partitioning of Yard Crane Workload for Container Terminal Operations Simulation-Based Dynamic Partitioning of Yard Crane Workload for Container Terminal Operations Xi Guo, Shell Ying Huang, Wen Jing Hsu and Malcolm Yoke Hean Low School of Computer Engineering Nanyang Technological

More information

Storage Allocation and Yard Trucks Scheduling in Container Terminals Using a Genetic Algorithm Approach

Storage Allocation and Yard Trucks Scheduling in Container Terminals Using a Genetic Algorithm Approach Storage Allocation and Yard Trucks Scheduling in Container Terminals Using a Genetic Algorithm Approach Z.X. Wang, Felix T.S. Chan, and S.H. Chung Abstract Storage allocation and yard trucks scheduling

More information

Transportation Science and Technology

Transportation Science and Technology International Journal of Transportation Science and Technology volume 1 number 2 2012 An Agent-Based Solution Framework for Inter-Block Yard Crane Scheduling Problems by Omor Sharif, Nathan Huynh, Mashrur

More information

The optimal number of yard cranes in container terminal

The optimal number of yard cranes in container terminal Journal of Industrial Engineering International January 2009, Vol. 5, o. 8, 7-76 Islamic Azad Universy, South Tehran Branch The optimal number of yard cranes in container terminal Gholam Reza Amin Assistant

More information

Container Terminal Modelling in Simul8 Environment

Container Terminal Modelling in Simul8 Environment Acta Technica Jaurinensis Series Logistica Vol. 6. No. 4. 2013 Container Terminal Modelling in Simul8 Environment G. Bohács, B. Kulcsár, D. Gáspár Budapest University of Technology and Economics 1111 Budapest,

More information

An Intelligent Decision Support System for Crane Scheduling in a Container Terminal

An Intelligent Decision Support System for Crane Scheduling in a Container Terminal An Intelligent Decision Support System for Crane Scheduling in a Container Terminal Guohua WAN Faculty of Business Administration, University of Macau, Taipa, Macao SAR, China E-mail: ghwan@umac.mo; Telephone:

More information

Selecting the best layout for the container terminal using Modeling and Simulation Techniques

Selecting the best layout for the container terminal using Modeling and Simulation Techniques Selecting the best layout for the container terminal using Modeling and Simulation Techniques Jeyanthinathasarma Gowrynathan, Chanjief Chandrakumar and Asela K.Kulatunga Department of Production Engineering

More information

Berth Allocation Planning for Improving Container Terminal Performances

Berth Allocation Planning for Improving Container Terminal Performances Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management Istanbul, Turkey, July 3 6, 2012 Berth Allocation Planning for Improving Container Terminal Performances

More information

A Discrete Time Heuristic for Storage and Scheduling Unloading Operations in Container Terminal under Capacity and Non-Interference Constraints

A Discrete Time Heuristic for Storage and Scheduling Unloading Operations in Container Terminal under Capacity and Non-Interference Constraints A Discrete Time Heuristic for Storage and Scheduling Unloading Operations in Container Terminal under Capacity and Non-Interference Constraints Sanae Kouismi MOAD-SCM Team, Mohammadia School of Engineering,

More information

Scheduling multiple yard cranes with crane interference and safety distance requirement

Scheduling multiple yard cranes with crane interference and safety distance requirement Scheduling multiple yard cranes with crane interference and safety distance requirement Author Wu, Yong, Li, Wenkai, Petering, Matthew E. H., Goh, Mark, de Souza, Robert Published 2015 Journal Title Transportation

More information

SPACE ALLOCATION AND LOCATION MATCHING IN CONTAINER TERMINALS

SPACE ALLOCATION AND LOCATION MATCHING IN CONTAINER TERMINALS Advanced OR and AI Methods in Transportation SPACE ALLOCATION AND LOCATION MATCHING IN CONTAINER TERMINALS Tonguç ÜNLÜYURT, Hacı Murat ÖZDEMIR Abstract. Operational efficiency at container terminals has

More information

OPTIMIZING CONTAINER TERMINAL OPERATIONS

OPTIMIZING CONTAINER TERMINAL OPERATIONS TLI Asia Pacific White Papers Series OPTIMIZING CONTAINER TERMINAL OPERATIONS Volume 06-Nov-SCO01 A Collaboration Between Robert de Souza Mark Goh Matthew E H Petering Wu Yong Li Wenkai The Logistics Institute

More information

Scheduling Quay Crane and Yard Equipment A case study of terminal in Central region

Scheduling Quay Crane and Yard Equipment A case study of terminal in Central region Thousand TEU Scheduling Quay Crane and Yard Equipment A case study of terminal in Central region Phong Ho Thanh Department of Industrial and Systems Engineering International University Vietnam National

More information

World Academy of Science, Engineering and Technology International Journal of Industrial and Manufacturing Engineering Vol:7, No:10, 2013

World Academy of Science, Engineering and Technology International Journal of Industrial and Manufacturing Engineering Vol:7, No:10, 2013 An Integrated Operational Research and System Dynamics Approach for Planning Decisions in Container Terminals A. K. Abdel-Fattah, A. B. El-Tawil, N. A. Harraz Abstract This paper focuses on the operational

More information

Hybrid search method for integrated scheduling problem of container-handling systems

Hybrid search method for integrated scheduling problem of container-handling systems Hybrid search method for integrated scheduling problem of container-handling systems Feifei Cui School of Computer Science and Engineering, Southeast University, Nanjing, P. R. China Jatinder N. D. Gupta

More information

A Dynamic Truck Dispatching Problem in Marine Container Terminal

A Dynamic Truck Dispatching Problem in Marine Container Terminal A Dynamic Truck Dispatching Problem in Marine Container Terminal Jianjun Chen, Ruibin Bai (IEEE senior member), Haibo Dong, Rong Qu and Graham Kendall Division of Computer Science, University of Nottingham

More information

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. Title Dynamic space and time partitioning for yard crane workload management in container terminals Author(s)

More information

Optimal Design, Evaluation, and Analysis of AGV Transportation Systems Based on Various Transportation Demands

Optimal Design, Evaluation, and Analysis of AGV Transportation Systems Based on Various Transportation Demands Optimal Design, Evaluation, and Analysis of Systems Based on Various Demands Satoshi Hoshino and Jun Ota Dept. of Precision Engineering, School of Engineering The University of Tokyo Bunkyo-ku, Tokyo 113-8656,

More information

DEVELOPMENT OF OPERATION STRATEGY TO IMPROVE EFFICIENCY FOR TWIN AUTOMATED TRANSFER CRANE IN AN AUTOMATED CONTAINER TERMINAL

DEVELOPMENT OF OPERATION STRATEGY TO IMPROVE EFFICIENCY FOR TWIN AUTOMATED TRANSFER CRANE IN AN AUTOMATED CONTAINER TERMINAL DEVELOPMENT OF OPERATION STRATEGY TO IMPROVE EFFICIENCY FOR TWIN AUTOMATED TRANSFER CRANE IN AN AUTOMATED CONTAINER TERMINAL Byung Joo PARK 1, Hyung Rim CHOI 2 1 Research Professor, Department of MIS,

More information

NAVAL POSTGRADUATE SCHOOL THESIS

NAVAL POSTGRADUATE SCHOOL THESIS NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS AN INTEGER LINEAR PROGRAM TO COMBINE CONTAINER HANDLING AND YARD CRANE DEPLOYMENT by Kamil Akel June 2007 Thesis Advisor: Second Reader: Robert F.

More information

Berth allocation planning in Seville inland port by simulation and optimisation

Berth allocation planning in Seville inland port by simulation and optimisation Berth allocation planning in Seville inland port by simulation and optimisation Carlos Arango 1, Pablo Cortés 1, Jesús Muñuzuri 1, Luis Onieva 1 1 Ingeniería de Organización. Engineering School of Seville.

More information

A Framework for Integrating Planning Activities in Container Terminals

A Framework for Integrating Planning Activities in Container Terminals A Framework for Integrating Planning Activities in Container Terminals August 30th, 2007 S. H. Won and K. H. Kim Dept. of Industrial Engineering, Pusan National University, South Korea Contents 1 Introduction

More information

Design of an AGV Transportation System by Considering Management Model in an ACT

Design of an AGV Transportation System by Considering Management Model in an ACT Intelligent Autonomous Systems 9 Book Editors IOS Press, 2006 1 Design of an AGV Transportation System by Considering Management Model in an ACT Satoshi Hoshino a,1,junota a, Akiko Shinozaki b, and Hideki

More information

Improving Productivity of Yard Trucks in Port Container Terminal Using Computer Simulation

Improving Productivity of Yard Trucks in Port Container Terminal Using Computer Simulation The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014) Improving Productivity of Yard Trucks in Port Container Terminal Using Computer Simulation Essmeil Ahmed

More information

Optimization and Simulation Approach for Empty Containers Handling

Optimization and Simulation Approach for Empty Containers Handling Optimization and Simulation Approach for Empty Containers Handling Chafik Razouk / PhD Student at ENSIAS Cedoc ST2I Operations Research & Logistics UM5S Université de Rabat Rabat, Morocco Youssef Benadada

More information

Research Article Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

Research Article Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode Computational Intelligence and euroscience, Article ID 682486, 8 pages http://dx.doi.org/10.1155/2014/682486 Research Article Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal

More information

Research into container reshuffling and stacking problems in container terminal yards

Research into container reshuffling and stacking problems in container terminal yards IIE Transactions (2015) 47, 751 766 Copyright C IIE ISSN: 0740-817X print / 1545-8830 online DOI: 10.1080/0740817X.2014.971201 Research into container reshuffling and stacking problems in container terminal

More information

Traffic Control of Internal Tractors in Port Container Terminal using Simulation

Traffic Control of Internal Tractors in Port Container Terminal using Simulation Proceedings of the 17th World Congress The International Federation of Automatic Control Traffic Control of Internal Tractors in Port Container Terminal using Simulation Henry Y. K. Lau* Nicole M. Y. Lee**

More information

A SIMULATION MODEL FOR INTEGRATING QUAY TRANSPORT AND STACKING POLICIES ON AUTOMATED CONTAINER TERMINALS

A SIMULATION MODEL FOR INTEGRATING QUAY TRANSPORT AND STACKING POLICIES ON AUTOMATED CONTAINER TERMINALS A SIMULATION MODEL FOR INTEGRATING QUAY TRANSPORT AND STACKING POLICIES ON AUTOMATED CONTAINER TERMINALS Mark B. Duinkerken, Joseph J.M. Evers and Jaap A. Ottjes Faculty of OCP, department of Mechanical

More information

ARTICLE IN PRESS. A decision support system for operations in a container terminal. Katta G. Murty a, *, Jiyin Liu b,1, Yat-wah Wan b, Richard Linn c

ARTICLE IN PRESS. A decision support system for operations in a container terminal. Katta G. Murty a, *, Jiyin Liu b,1, Yat-wah Wan b, Richard Linn c Decision Support Systems xx (2004) xxx xxx www.elsevier.com/locate/dsw A decision support system for operations in a container terminal Katta G. Murty a, *, Jiyin Liu b,1, Yat-wah Wan b, Richard Linn c

More information

DISPATCHING TRANSPORT VEHICLES IN MARITIME CONTAINER TERMINALS

DISPATCHING TRANSPORT VEHICLES IN MARITIME CONTAINER TERMINALS DISPATCHING TRANSPORT VEHICLES IN MARITIME CONTAINER TERMINALS by Pyung-Hoi Koo Department of Systems Management and Engineering, Pukyong National University, Busan, Korea Yongsoro 45, Namgu, Busan, South

More information

Dispatching Policy Selection and Orbit Design in the Low Viaduct Rail Transportation System

Dispatching Policy Selection and Orbit Design in the Low Viaduct Rail Transportation System Page 1 of 14 ANZAM 2009 Dispatching Policy Selection and Orbit Design in the Low Viaduct Rail Transportation System Dr.DING Yizhong * and Dr.HAN Xiaolong Logistics Research Center, Shanghai Maritime University,

More information

Design and Operation of Automated Container Storage Systems

Design and Operation of Automated Container Storage Systems Nils Kemme Design and Operation of Automated Container Storage Systems Physica-Verlag A Springer Company 1 Introduction 1 1.1 Definition of the Subject Area 2 1.2 Problem Description and Research Objectives

More information

Solving the Resource Allocation Problem in a Multimodal Container Terminal as a Network Flow Problem

Solving the Resource Allocation Problem in a Multimodal Container Terminal as a Network Flow Problem Author manuscript, published in "Computational Logistics, Jürgen W. Böse, Hao Hu, Carlos Jahn, Xiaoning Shi, Robert Stahlbock, Stefan Voß (Ed.) (2011) 341-353" DOI : 10.1007/978-3-642-24264-9_25 Solving

More information

A DSS (Decision Support System) for Operations in a Container Terminal

A DSS (Decision Support System) for Operations in a Container Terminal A DSS (Decision Support System) for Operations in a Container Terminal Katta G. Murty 1, Jiyin Liu 2, Yat-wah Wan 2,andRichardLinn 3 1 Department of IOE, University of Michigan, Ann Arbor, Michigan 48109-2117,

More information

Optimization of Container Operations at Inland Intermodal Terminals

Optimization of Container Operations at Inland Intermodal Terminals Optimization of Container Operations at Inland Intermodal Terminals Chiara Colombaroni, Gaetano Fusco, Natalia Isaenko Dipartimento di Ingegneria Civile Edile e Ambientale University of Rome Sapienza Rome,

More information

Optimizing Container Movements Using One and Two Automated Stacking Cranes

Optimizing Container Movements Using One and Two Automated Stacking Cranes Calhoun: The NPS Institutional Archive Faculty and Researcher Publications Faculty and Researcher Publications Collection 2009-05 Optimizing Container Movements Using One and Two Automated Stacking Cranes

More information

SIMULATION ANALYSIS OF ALGORITHMS FOR CONTAINER STORAGE AND YARD CRANE SCHEDULING AT A CONTAINER TERMINAL

SIMULATION ANALYSIS OF ALGORITHMS FOR CONTAINER STORAGE AND YARD CRANE SCHEDULING AT A CONTAINER TERMINAL SIMULATION ANALYSIS OF ALGORITHMS FOR CONTAINER STORAGE AND YARD CRANE SCHEDULING AT A CONTAINER TERMINAL Matthew E. H. Petering*, ** and Katta G. Murty* *Department of Industrial and Operations Engineering,

More information

A Method of Container Terminal Resources Scheduling Simulation Research Li Mingqi, Zhang Peng*, Du Yuyue

A Method of Container Terminal Resources Scheduling Simulation Research Li Mingqi, Zhang Peng*, Du Yuyue Joint International Mechanical, Electronic and Information Technology Conference (JIMET 2015) A Method of Container Terminal Resources Scheduling Simulation Research Li Mingqi, Zhang Peng*, Du Yuyue College

More information

Dynamic Scheduling of Automated Guided Vehicles in Container Terminals

Dynamic Scheduling of Automated Guided Vehicles in Container Terminals Department of Computer Science Dynamic Scheduling of Automated Guided Vehicles in Container Terminals Hassan Rashidi Haramabadi A thesis submitted for the degree of PhD Date of conferment: 27 April 2006

More information

Space-Sharing Strategy for Building Dynamic Container Yard Storage Considering Uncertainty on Number of Incoming Containers

Space-Sharing Strategy for Building Dynamic Container Yard Storage Considering Uncertainty on Number of Incoming Containers Jurnal Teknik Industri, Vol. 19, No. 2, December 2017, 67-74 ISSN 1411-2485 print / ISSN 2087-7439 online DOI: 10.9744/jti.19.2.67-74 Space-Sharing Strategy for Building Dynamic Container Yard Storage

More information

Simulation of Container Queues for Port Investment Decisions

Simulation of Container Queues for Port Investment Decisions The Sixth International Symposium on Operations Research and Its Applications (ISORA 06) Xinjiang, China, August 8 12, 2006 Copyright 2006 ORSC & APORC pp. 155 167 Simulation of Container Queues for Port

More information

SIMULATION AND OPTIMIZATION OF SELECTED CLASSIFICATION NUMBERS AT A CONTAINER TERMINAL: TECON - RIO GRANDE, BRAZIL

SIMULATION AND OPTIMIZATION OF SELECTED CLASSIFICATION NUMBERS AT A CONTAINER TERMINAL: TECON - RIO GRANDE, BRAZIL SIMULATION AND OPTIMIZATION OF SELECTED CLASSIFICATION NUMBERS AT A CONTAINER TERMINAL: TECON - RIO GRANDE, BRAZIL Leif Hendrik Meier Andreas Lackner Helge Fischer Jörg Biethahn University of Göttingen,

More information

STORAGE ALLOCATION IN AUTOMATED CONTAINER TERMINALS: THE UPPER LEVEL

STORAGE ALLOCATION IN AUTOMATED CONTAINER TERMINALS: THE UPPER LEVEL POLISH MARITIME RESEARCH Special Issue 2016 S1 (91) 2016 Vol. 23; pp. 160-174 10.1515/pomr-2016-0061 STORAGE ALLOCATION IN AUTOMATED CONTAINER TERMINALS: THE UPPER LEVEL Xia Mengjue 1 Zhao Ning 2 Mi Weijian

More information

Analysis and Modelling of Flexible Manufacturing System

Analysis and Modelling of Flexible Manufacturing System Analysis and Modelling of Flexible Manufacturing System Swetapadma Mishra 1, Biswabihari Rath 2, Aravind Tripathy 3 1,2,3Gandhi Institute For Technology,Bhubaneswar, Odisha, India --------------------------------------------------------------------***----------------------------------------------------------------------

More information

Storage and stacking logistics problems in container terminals

Storage and stacking logistics problems in container terminals Original Article Storage and stacking logistics problems in container terminals Jiabin Luo a,yuewu a, *, Arni Halldorsson b and Xiang Song c a School of Management, University of Southampton, University

More information

Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds.

Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds. Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds. YARD CRANE DISPATCHING TO MINIMIZE VESSEL TURNAROUND TIMES IN CONTAINER

More information

Efficient Container Security Operations at Transshipment Seaports

Efficient Container Security Operations at Transshipment Seaports 1 Efficient Container Security Operations at Transshipment Seaports Brian M. Lewis, Alan L. Erera, and Chelsea C. White III Abstract This paper describes an approach for aiding the management of a container

More information

Industrial Engineering Applications to Optimize Container Terminal Operations

Industrial Engineering Applications to Optimize Container Terminal Operations Industrial Engineering Applications to Optimize Container Terminal Operations Asela K. Kulatunga* & D.H. Haasis+ *glink Postdoctoral researcher, University of Bremen Germany Senior Lecturer, Faculty of

More information

Scheduling and Rostering of Flexible Labour at Container Port Terminals using Metaheuristic Algorithms

Scheduling and Rostering of Flexible Labour at Container Port Terminals using Metaheuristic Algorithms Scheduling and Rostering of Flexible Labour at Container Port Terminals using Metaheuristic Algorithms Ali Rais Shaghaghi 1*, Tom Corkhill 2 and Abdellah Salhi 1 1. Department of Mathematical Sciences,

More information

Highly Efficient AGV Transportation System Management Using Agent Cooperation and Container Storage Planning

Highly Efficient AGV Transportation System Management Using Agent Cooperation and Container Storage Planning Highly Efficient AGV Transportation System Management Using Agent Cooperation and Container Storage Planning Satoshi Hoshino and Jun Ota Dept. of Precision Engineering, School of Engineering The University

More information

A Dynamic and Collaborative Truck Appointment Management System in Container Terminals

A Dynamic and Collaborative Truck Appointment Management System in Container Terminals A Dynamic and Collaborative Truck Appointment Management System in Container Terminals Ahmed Azab, Ahmed Karam and Amr Eltawil Department of Industrial Engineering and Systems Management, Egypt-Japan University

More information

A SIMULATION FRAMEWORK FOR OPTIMIZING TRUCK CONGESTIONS IN MARINE TERMINALS

A SIMULATION FRAMEWORK FOR OPTIMIZING TRUCK CONGESTIONS IN MARINE TERMINALS Journal of Maritime Research, Vol. VII. No. I, pp. 55-70, 2010 Copyright 2010. SEECMAR Printed in Santander (Spain). All rights reserved ISSN: 1697-4840 A SIMULATION FRAMEWORK FOR OPTIMIZING TRUCK CONGESTIONS

More information

Operations research methods in maritime transport and freight logistics

Operations research methods in maritime transport and freight logistics Operations research methods in maritime transport and freight logistics Maritime Economics & Logistics (2009) 11, 1 6. doi:10.1057/mel.2008.18 The current decade has witnessed a remarkable growth in container

More information

A New Simulation Model for a Comprehensive Evaluation of Yard Truck Deployment Strategies at Marine Container Terminals

A New Simulation Model for a Comprehensive Evaluation of Yard Truck Deployment Strategies at Marine Container Terminals RESEARCH ARTICLE A New Simulation Model for a Comprehensive Evaluation of Yard Truck Deployment Strategies at Marine Container Terminals Maxim A. Dulebenets* Florida A&M University - Florida State University,

More information

NAVAL POSTGRADUATE SCHOOL THESIS

NAVAL POSTGRADUATE SCHOOL THESIS NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS REAL-TIME DISPATCHING OF RUBBER TIRED GANTRY CRANES IN CONTAINER TERMINALS by Bradley S. McNary March 2008 Thesis Advisor: Second Reader: Johannes

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution

More information

Optimizing a Containership Stowage Plan. using a modified Differential Evolution algorithm

Optimizing a Containership Stowage Plan. using a modified Differential Evolution algorithm Optimizing a Containership Stowage Plan using a modified Differential Evolution algorithm Speaker: Dr. Yun Dong ydong@tli.neu.edu.cn Supervisor: Pro. Lixin Tang Lixintang@mail.neu.edu.com The Logistics

More information

Journal of Optimization in Industrial Engineering 20 (2016) Mohammad Reza Ghanbari a,*, Parham Azimi b

Journal of Optimization in Industrial Engineering 20 (2016) Mohammad Reza Ghanbari a,*, Parham Azimi b Journal of Optimization in Industrial Engineering 0 (06) 3-40 Performance Improvement through a Marshaling Yard Storage Area in a Container Port Using Optimization via Simulation Technique: A Case Study

More information

Simulation-Based Trucks Configuration for Twin 40 Feet Quay Cranes in Container Terminals

Simulation-Based Trucks Configuration for Twin 40 Feet Quay Cranes in Container Terminals Simulation-Based Trucks Configuration for Twin 40 Feet Quay Cranes in Container Terminals Peng Yun, Wang Wenyuan, Zhang Qi, Chen Modi, and Zhang Ran Abstract Twin 40 feet quay cranes are used to improve

More information

Integrated Berth Allocation and Yard Assignment in Bulk Ports using Column Generation. Tomáš Robenek Nitish Umang Michel Bierlaire

Integrated Berth Allocation and Yard Assignment in Bulk Ports using Column Generation. Tomáš Robenek Nitish Umang Michel Bierlaire Integrated Berth Allocation and Yard Assignment in Bulk Ports using Column Generation Tomáš Robenek Nitish Umang Michel Bierlaire STRC 2012 April 2012 STRC 2012 Integrated Berth Allocation and Yard Assignment

More information

Reliability Analysis of Dangerous Goods Transportation Network in Container Terminals

Reliability Analysis of Dangerous Goods Transportation Network in Container Terminals 2017 International Conference on Mathematics, Modelling and Simulation Technologies and Applications (MMSTA 2017) ISBN: 978-1-60595-530-8 Reliability Analysis of Dangerous Goods Transportation Network

More information

Design of an Automated Transportation System in a Seaport Container Terminal for the Reliability of Operating Robots

Design of an Automated Transportation System in a Seaport Container Terminal for the Reliability of Operating Robots Design of an Automated Transportation System in a Seaport Container Terminal for the Reliability of Operating Robots Satoshi Hoshino and Jun Ota Abstract For the design of an automated transportation system

More information

Available online at ScienceDirect. Procedia Computer Science 65 (2015 )

Available online at   ScienceDirect. Procedia Computer Science 65 (2015 ) Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 65 (2015 ) 662 671 International Conference on Communication, Management and Information Technology (ICCMIT 2015) An Optimization

More information

Rehandling Strategies for Container Retrieval

Rehandling Strategies for Container Retrieval Rehandling Strategies for Container Retrieval Tonguç Ünlüyurt and Cenk Aydin Sabanci University, Faculty of Engineering and Natural Sciences e-mail: tonguc@sabanciuniv.edu 1 Introduction In this work,

More information

Available online at ScienceDirect. Procedia CIRP 40 (2016 )

Available online at  ScienceDirect. Procedia CIRP 40 (2016 ) Available online at www.sciencedirect.com ScienceDirect Procedia CIRP 40 (2016 ) 301 306 13th Global Conference on Sustainable Manufacturing - Decoupling Growth from Resource Use Incorporate LEAN and Green

More information

Modeling and solving the train load planning problem in seaport container terminals

Modeling and solving the train load planning problem in seaport container terminals 11 IEEE International Conference on Automation Science and Engineering Trieste, Italy - August 24-27, 11 ThB2.2 Modeling and solving the train load planning problem in seaport container terminals Daniela

More information

A PETRI NET MODEL FOR SIMULATION OF CONTAINER TERMINALS OPERATIONS

A PETRI NET MODEL FOR SIMULATION OF CONTAINER TERMINALS OPERATIONS Advanced OR and AI Methods in Transportation A PETRI NET MODEL FOR SIMULATION OF CONTAINER TERMINALS OPERATIONS Guido MAIONE 1, Michele OTTOMANELLI 1 Abstract. In this paper a model to simulate the operation

More information

OPERATIONS OPTIMIZATION AT TKD CONTAINER TERMINAL

OPERATIONS OPTIMIZATION AT TKD CONTAINER TERMINAL Scientific Journal of Impact Factor (SJIF): 5.71 International Journal of Advance Engineering and Research Development Volume 5, Issue 03, March -2018 e-issn (O): 2348-4470 p-issn (P): 2348-6406 OPERATIONS

More information

A COMPARISON OF PRIORITY RULES FOR NON-PASSING AUTOMATED STACKING CRANES

A COMPARISON OF PRIORITY RULES FOR NON-PASSING AUTOMATED STACKING CRANES A COMPARISON OF PRIORITY RULES FOR NON-PASSING AUTOMATED STACKING CRANES Héctor J. Carlo, Azaria Del Valle-Serrano, Fernando L. Martínez- Acevedo, Yaritza M. Santiago-Correa University of Puerto Rico Mayagüez,

More information

Research on Multi-Objective Co-operation Optimization of Shipyard Berth Allocation System

Research on Multi-Objective Co-operation Optimization of Shipyard Berth Allocation System Research on Multi-Objective Co-operation Optimization of Shipyard Berth Allocation System Tang Weiwei 1*, Yang Kunrong 2 1 School of Civil Engineering and Transportation South China University of Technology

More information

A SIMULATION BASED HYBRID ALGORITHM FOR YARD CRANE DISPATCHING IN CONTAINER TERMINALS. Xi Guo Shell Ying Huang Wen Jing Hsu Malcolm Yoke Hean Low

A SIMULATION BASED HYBRID ALGORITHM FOR YARD CRANE DISPATCHING IN CONTAINER TERMINALS. Xi Guo Shell Ying Huang Wen Jing Hsu Malcolm Yoke Hean Low Proceedings of the 2009 Winter Simulation Conference M. D. Rossetti, R. R. Hill, B. Johansson, A. Dunkin and R. G. Ingalls, eds. A SIMULATION BASED HYBRID ALGORITHM FOR YARD CRANE DISPATCHING IN CONTAINER

More information

Determination of the number of AGVs required at a semi-automated container terminal

Determination of the number of AGVs required at a semi-automated container terminal Determination of the number of AGVs required at a semi-automated container terminal Iris F.A. Vis, René de Koster, Kees Jan Roodbergen, Leon W.P. Peeters Rotterdam School of Management, Erasmus University

More information

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds.

Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. REUSABLE TEMPLATE FOR SIMULATION OF OVERHEAD CRANES INTERFERENCES ABSTRACT

More information

Locomotive Fuelling Problem (LFP) in Railroad Operations. Bodhibrata Nag 1 & Katta G.Murty 2

Locomotive Fuelling Problem (LFP) in Railroad Operations. Bodhibrata Nag 1 & Katta G.Murty 2 1 Locomotive Fuelling Problem (LFP) in Railroad Operations Bodhibrata Nag 1 & Katta G.Murty 2 About 75% of the world s railroads operate with diesel fuel. Even though European railroads rely on electric

More information

SIMULATION STUDY OF A DYNAMIC AGV-CONTAINER JOB DEPLOYMENT SCHEME

SIMULATION STUDY OF A DYNAMIC AGV-CONTAINER JOB DEPLOYMENT SCHEME 1 SIMULATION STUDY OF A DYNAMIC AGV-CONTAINER JOB DEPLOYMENT SCHEME By Cheng Yong Leong B.Eng. Electrical Engineering National University of Singapore, 2000 SUBMITTED TO THE SMA OFFICE IN PARTIAL FULFILLMENT

More information

1 General Considerations on Container Terminal Planning... 3

1 General Considerations on Container Terminal Planning... 3 Contents Part I Introduction 1 General Considerations on Container Terminal Planning... 3 Jürgen W. Böse 1.1 3-Level-Model...... 3 1.2 Basic Aspects: Technologies & Instruments..... 8 1.3 Main Planning

More information

Jiirgen W. Bose. Editor. Handbook of Terminal. Planning. & Springer

Jiirgen W. Bose. Editor. Handbook of Terminal. Planning. & Springer Jiirgen W. Bose Editor Handbook of Terminal Planning & Springer Parti Introduction 1 General Considerations on Container Terminal Planning 3 Jiirgen W. Bose 1.1 3-Level-Model 3 1.2 Basic Aspects: Technologies

More information

Dispatching Automated Guided Vehicles in a Container Terminal

Dispatching Automated Guided Vehicles in a Container Terminal Dispatching Automated Guided Vehicles in a Container Terminal Yong-Leong Cheng, Hock-Chan Sen Singapore MIT Alliance Program Karthik Natarajan National University of Singapore Chung-Piaw Teo Sungkyunkwan

More information

Maritime Container Transport

Maritime Container Transport Chapter 2 Maritime Container Transport This chapter provides an introduction to the maritime container transport industry. Section 2.1 briefly describes the development of maritime container transport

More information

The Tactical Berth Allocation Problem with QC Assignment and Transshipment Costs

The Tactical Berth Allocation Problem with QC Assignment and Transshipment Costs The Tactical Berth Allocation Problem with QC Assignment and Transshipment Costs Models and Heuristics Ilaria Vacca Transport and Mobility Laboratory, EPFL joint work with Giovanni Giallombardo, Luigi

More information

NAVAL POSTGRADUATE SCHOOL THESIS

NAVAL POSTGRADUATE SCHOOL THESIS NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS OPTIMIZING CONTAINER MOVEMENTS USING ONE AND TWO AUTOMATED STACKING CRANES by Ioannis Zyngiridis December 2005 Thesis Advisor: Second Reader: Robert

More information

Workload balancing in identical parallel machine scheduling using a mathematical programming method

Workload balancing in identical parallel machine scheduling using a mathematical programming method International Journal of Computational Intelligence Systems, Vol. 7, Supplement 1 (2014), 58-67 Workload balancing in identical parallel machine scheduling using a mathematical programming method Yassine

More information

Segregating space allocation models for container inventories in port container terminals

Segregating space allocation models for container inventories in port container terminals Int. J. Production Economics 59 (1999) 415 423 Segregating space allocation models for container inventories in port container terminals Kap Hwan Kim*, Hong Bae Kim Department of Industrial Engineering,

More information

SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL

SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL SIMULATION AND FORECASTING IN INTERMODAL CONTAINER TERMINAL Luca Maria Gambardella 1, Gianluca Bontempi 1, Eric Taillard 1, Davide Romanengo 2, Guido Raso *2, Pietro Piermari 3 1 IDSIA, Istituto Dalle

More information

Sensor Network Design for Multimodal Freight Traffic Surveillance

Sensor Network Design for Multimodal Freight Traffic Surveillance NEXTRANS 2009 Undergraduate Summer Internship Sensor Network Design for Multimodal Freight Traffic Surveillance Eunseok Choi (Joint work with Xiaopeng Li and Yanfeng Ouyang) Motivation Challenge: Real-Time

More information

Transactions on the Built Environment vol 33, 1998 WIT Press, ISSN

Transactions on the Built Environment vol 33, 1998 WIT Press,  ISSN Effects of designated time on pickup/delivery truck routing and scheduling E. Taniguchf, T. Yamada\ M. Tamaishi*, M. Noritake^ "Department of Civil Engineering, Kyoto University, Yoshidahonmachi, Sakyo-kyu,

More information

Vehicle Routing with Cross Docks, Split Deliveries, and Multiple Use of Vehicles. Arun Kumar Ranganathan Jagannathan

Vehicle Routing with Cross Docks, Split Deliveries, and Multiple Use of Vehicles. Arun Kumar Ranganathan Jagannathan Vehicle Routing with Cross Docks, Split Deliveries, and Multiple Use of Vehicles by Arun Kumar Ranganathan Jagannathan A thesis submitted to the Graduate Faculty of Auburn University in partial fulfillment

More information

Strategies for Coordinated Drayage Movements

Strategies for Coordinated Drayage Movements Strategies for Coordinated Drayage Movements Christopher Neuman and Karen Smilowitz May 9, 2002 Abstract The movement of loaded and empty equipment (trailers and containers) between rail yards and shippers/consignees

More information

OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS. Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez

OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS. Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez Héctor J. Carlo, Ph.D. Industrial Engineering, University of Puerto Rico

More information

Container Transfer Logistics at Multimodal Container Terminals

Container Transfer Logistics at Multimodal Container Terminals Container Transfer Logistics at Multimodal Container Terminals Erhan Kozan School of Mathematical Sciences, Queensland University of Technology Brisbane Qld 4001 Australia e.kozan@qut.edu.au Abstract:

More information

University Question Paper Two Marks

University Question Paper Two Marks University Question Paper Two Marks 1. List the application of Operations Research in functional areas of management. Answer: Finance, Budgeting and Investment Marketing Physical distribution Purchasing,

More information

Capacitated vehicle routing problem for multi-product crossdocking with split deliveries and pickups

Capacitated vehicle routing problem for multi-product crossdocking with split deliveries and pickups Available online at www.sciencedirect.com Procedia - Social and Behavioral Sciences 62 ( 2012 ) 1360 1365 WC-BEM 2012 Capacitated vehicle routing problem for multi-product crossdocking with split deliveries

More information

Network Flows. 7. Multicommodity Flows Problems. Fall 2010 Instructor: Dr. Masoud Yaghini

Network Flows. 7. Multicommodity Flows Problems. Fall 2010 Instructor: Dr. Masoud Yaghini In the name of God Network Flows 7. Multicommodity Flows Problems 7.1 Introduction Fall 2010 Instructor: Dr. Masoud Yaghini Introduction Introduction In many application contexts, several physical commodities,

More information

PERFORMANCE EVALUATION OF CONTAINER TERMINAL OPERATIONS. Kinikli, 20020, Denizli, Turkey,

PERFORMANCE EVALUATION OF CONTAINER TERMINAL OPERATIONS. Kinikli, 20020, Denizli, Turkey, PERFORMANCE EVALUATION OF CONTAINER TERMINAL OPERATIONS Osman Kulak a, Olcay Polat a, Hans-Otto Guenther b, a Department of Industrial Engineering, Pamukkale University, Kinikli, 20020, Denizli, Turkey,

More information

Fleet Sizing and Empty Freight Car Allocation

Fleet Sizing and Empty Freight Car Allocation Fleet Sizing and Empty Freight Car Allocation Philipp Hungerländer, Sebastian Steininger 13th July 2018 Abstract Empty freight car allocation problems as well as fleet sizing problems depict highly important

More information

Ferry Rusgiyarto S3-Student at Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia

Ferry Rusgiyarto S3-Student at Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 10, October 2017, pp. 1085 1095, Article ID: IJCIET_08_10_112 Available online at http://http://www.iaeme.com/ijciet/issues.asp?jtype=ijciet&vtype=8&itype=10

More information

SIMULATION MODEL FOR MARITIME CONTAINER TERMINAL

SIMULATION MODEL FOR MARITIME CONTAINER TERMINAL TRANSPORT PROBLEMS 2018 Volume 13 Issue 4 PROBLEMY TRANSPORTU DOI: 10.20858/tp.2018.13.4.5 Keywords: container terminal; simulation model; maritime transport Florin RUSCĂ*, Mihaela POPA, Eugen ROȘCA, Mircea

More information