Alternative Methods for Business Process Planning
|
|
- Peter Pitts
- 6 years ago
- Views:
Transcription
1 Volume 7 (21) Issue DOI /vjes Alternative Methods for Business Process Planning Veronica STEFAN Valentin RADU Valahia University of Targoviste, Romania veronica.stefan@ats.com.ro Abstract Identifying, analyzing and using the most appropriate and efficient methods for planning business processes is a key to success for every enterprise. Our paper are two objectives: to identify the most proper methods used for planning and applying for the same case study. We are looking to demonstrate the methodology of using some software tools and compare the obtained results. The application domain will be the planning of production processes but these methods can be extended to the service processes. The methodology is represented by the mathematical models and software applications in this fields, such as Simplex model theory, Solver Excel tools, WinQSE application, linear programming with PL.exe. The results of the research have a high applicability level and can be extended in other business fields too. Keywords: Business process, Simplex, Solver Excel, WinQSB, Linear programming JEL Classification: O21, O22, O32 Introduction Every organization, profit-oriented or not, large, small, manufacturing production or service have as core function producing some outputs from its processes. The production process can be approached as a cyber system, defined by three components: inputs, outputs, and achieving the production process. In this system, the production process transforms under worker surveillance the inputs, meaning productions factors (raw materials, work tools), in economic goods (goods, works, services), which constitute the output of the system [Filip F. G. (2007)]. For an organization to be effective and efficient in serving its customers, the managers must apply certain fundamental principles and methods of planning and control the process of production for the outputs [Frame, J. D. (2002)], [Westland J. (2006)]. Although planning and control approaches that will be presented are most commonly used in manufacturing companies, many of them have been adapted for use in services companies. 87
2 Volume 7 (21) Issue Planning systems and control in organizations are influenced by many factors such as the timing and synchronization, relationship with the customer and influence of the customer for the design of service, quality (a key dimension of quality being that is intangible, which makes it actual difficult to measure), business environment and its characteristics, analysis of the processes and information flows [Chapman S. N. (2001)]. The aim of the paper is the identification, analysis and compare of some alternative methods for the planning of production processes, methods that can be extended in the future for the service processes. 1. The research objectives and methodology The aim of the paper is identifying, analyzing and presenting the way of applying some several alternative methods of planning, seeking to compare results based on a jointly case study. Planning and control principles used in manufacturing companies can be adapted and used by the companies that provides services. Addressing the planning and control for organizations offering services must take into account additional factors that can influence the result, such as: the timing, scheduled the time and synchronization the events and the activities between customer demands related to delivery of the service from the company [Lewis J. P. (2001)]; relationship with the customer, in a service environment the customer is more involved in the design of the (service); the quality, a key dimension of service quality is that can be intangible, which makes it difficult to measure effectively; the storage, the companies services oriented, that actually do not involve physical goods in their production, often do not storing their output. It is impossible, for example, to store a haircut. The stock (mainly finished products) can be considered as the utilization of the enterprise production capacity ahead of actual demand. Some methods like Simplex model, application Solver Excel and WinQSB tool from PL.exe [Orr A. D. (2004)] will be used to illustrate their application for production companies, considering that they can be adapted for use in services companies too. For application of planning methods above mentioned is necessary to consider the whole ecosystem of planning activities flow, as they are illustrated in the following figure. The flowchart of planning and control activities Figure (Source: Chapman S. N. (2001))
3 2. Defining working hypotheses Volume 7 (21) Issue We considered the situation of planning the number of assortment by each product type, so as to obtain the maximum benefit, considering the productivity conditions [Rusu, A., (2007)]. Our case study will establish the following hypotheses: A machine is working 25 hours per week and produces three articles. The benefit after the sale of these three items is 40 Ron / each piece for the first item, 120 Ron / each piece for the second article and 30 Ron / each piece for the third article. Within an hour the machine can achieve 50 pieces for the first article or 25 pieces of the second article or 75 pieces for the third article. The weekly demand does not exceed 1,000 pieces for the first article, 500 pieces for the second article and 1500 pieces for the third article. We need to plan the production for each of the three articles, for the enterprise to ensure maximum benefit. For the mathematical model of the problem we consider the variables x1, x2, x3 for the quantities that must be produced for each of the three articles: max f 40* x1120* x2 30* x3 x x2 500 x x1 x2 x x1, x2, x3 0 1 As x 1 represents the number of hours in a week when the machine produces a 50 quantity x 1 from the first product, the constraint referring the number of hours has the next form: 3*X1 + 6*X2 + 2*X3 <= Results analysis 3.2. Using SIMPLEX method The mathematical model formulated above, where x1, x2, x3 represent each quantities of the three articles that must be produced, is brought to the next standard form: 89
4 Volume 7 (21) Issue max f 40 * x1120* x2 30 * x3 x1 x x2 x5 500 x3 x x1 *3 6 * x2 2 * x3 x x1, x2, x3, x4, x5, x6, x7 0 The matrix of restrictions coefficients and vectors Pi is the following: It is noted that the base vectors are P 4 P5 P6 P7 so basic unknowns are x 4 x5 x6 x7. The first admissible basic solution, which was obtained by canceling the secondary unknowns, is X T 90 0 The first SIMPLEX table is: Base C B P P 1 P 2 P 3 P 4 P 5 P 6 P 7 P P P P z k -c k P P P P z k -c k P P P / /2 P / /2 z k -c k
5 The differences z k - c k is calculated as follows: Volume 7 (21) Issue Z 1 c 1 = C B * P 1 c 1 = 0*1 + 0*0 + 0*0 + 0*3 40 = -40 Z 2 c 2 = C B * P 2 c 2 = 0*0 + 0*1 + 0*0 + 0*6 120 = -120 etc. The solution is not optimal because there are negative value on the line z k - c k. Get in min(-40, -120, -30) = -120, that means the vector P 2 Get out min(500/1, 3750/6) = 500, that means the vector P 5 Pivot line is divided by 1, so remain unchanged. To make 0 on the pivot column on multiply: pivot line with 0 and add to P4 line pivot line with 0 and add to P6 line pivot line with -6 and add to P7 line It repeat the four above steps and we note that P 3 get in and P 7 get out Optimality criterion is satisfied: all z k - c k differences are greater or equal to 0. The optimal solution can be find on the column P 0 : x 1 =0, x 2 =500, x 3 =375, x 4 =1000, x 5 =0, x 6 =1125, x 7 = 375, so it will produce 0 items from article 1, 500 items from the second article and 375 items from the third article. The benefits are 40* * *375 = Using SOLVER from Excel SOLVER is an add-in program in MS Excel [Pyron T. (2004)] used to find an optimal value, maximum or minimum, for one formula in one cell, named Objective cell. This value is subject to constraints on the values of other formula cells on a worksheet. Solver works with a group of cells called decision variables cells for computing the formulas in the objective and constraint cells. Solver adjusts the values in the decision variable cells to satisfy the limits on constraint cells and produce the result for the objective cell. With Solver we can determine the maximum or minimum value of one cell by changing other cells. Using Solver we reserve cell B2 for the number of products from the first article, cell B3 for the number of products from the second article and B4 for the third article. The cell B5 will contain the left side of the constraint referring to hours, respectively: B5= 3*B2+6*B3+2*B4 The objective function to be maximized is inserted in cell B6: B6 = 40*B2+120*B3+30*B4 91
6 Volume 7 (21) Issue Figure 2. Inserting the input values in Solver Excel In the menu Subject to the constraints we inserted one by one each constraint, like in the next figure. The number of products for the first article is less than or equal to 1000, the number of products for the second article is less than or equal to 500, the number of products for the third article must be less than or equal to 1500, and the last constraint, the required number of hours worked by machine B5 <= The image in the left contains the first constraint, the number of products for the first article is less than or equal to 1000, and the last constraint is referring, to hours: Introducing the constraints Figure 3. With Options button we assure that X1, X2, X3 variables have integers values greater than or equal to 0, marking the option Assume non-negative. In the main menu of Solver we complete the target cell that must be maximum with $B$6 and next we modify the cells with option By changing Cells, $B$2: $B$4. Using the Solve button we obtain the window with final results: Solver Results Figure 4 92
7 Volume 7 (21) Issue Selecting Keep Solver Solution and choosing a feedback with Reports Answer, in the worksheet Excel we find the final results and the next values: X1 = 0, X2 =500, X3=375, and the benefits Figure 5. Results Report and sensitivity analysis 3.4 Using WinQSB for linear programming Linear programming can be used in the production management to solve problems of distribution of production on different machines in terms of maximizing profits for determining the quantities of various goods to be produced [Harts D. (2007)]. We will solve with linear programming the same mathematical model, with objectives and restrictions. 93
8 Volume 7 (21) Issue WinQSB interface with model restrictions and variables Figure 6. Selecting Solve the Problem from the menu Result we obtain the solution: The results with WinQSB Figure 7. The final Simplex table with WinQSB solution Figure 8 94
9 Volume 7 (21) Issue The graphical presentation of the WinQSB solution Figure 9 The result is the same with the two previous methods: X1= 0, X2=500, X3 = 375 and the benefits Thus, with linear programing is much easier to work and to find the final result. In addition, there is the possibility of cooperating with business intelligence applications for integrate the result with other application and to aggregate for complex analysis. Conclusions Key performance for an organization are depending of a related number of factors, its overall efficiency becoming ensured with a continuous and consistent planning process across the organization. One of the most important factor of efficiency is the rigorous and correct planning, based on the most scientific theories, innovative methods and software tools. These software solutions for planning provides more accurate and documented decision support, with significantly improved performance. Providing real-time performance information enables to all levels of decision in a company to take corrective actions, which diminishes the chain propagation of errors and lead to an increased efficiency. The planning process is multi-dimensional and ensures a high degree of objectivity, unlimited from the capacity of a single decision factor. Considering more variables we have a better way to decide, the result is better refined and accurate. Although the costs associated with traditional ways of planning can be considerably reduced, the benefits of implementing a tool to assist the planning process are 95
10 Volume 7 (21) Issue highly increased and the costs of implementing such solutions is quickly pays off through the performance achieved. Using the potential of information technology has proved always a success and the methods utilized contribute to a high level of significantly increased performance. References Chapman, S. N., (2001) The fundamentals of production planning and control, Ed. Prentice Hall, Upper Saddle River, NJ 07458, ISBN X Filip, F. G., (2007) Sisteme suport pentru decizii, Editura tehnică Frame, J. Davidso, (2002) The new project management: tools for an age of rapid change, complexity, and other business realities, San Francisco, John Wiley & Sons Lewis, James P. (2001) Project planning, scheduling and control: a hands-on guide to bringing projects in on time on budget, 3rd ed. Toronto, McGraw-Hill Orr, Alan D., (2004) Advanced project management: a complete guide to the processes, models and techniques, London, Kogan Page Pyron, Tim, (2004) Special edition using Microsoft Office Project 2003, Indianapolis, Que Westland, Jason, (2006) The project management life cycle: a complete step-by-step methodology for iniating, planning, executing & closing a project successfully, London, Kogan Page Harts, D., (2007) Microsoft Office 2007 Business Intelligence, ISBN-13: , McGraw-Hill Osborne Media Rusu, A., (2007) Cercetari operationale, Iasi
DIS 300. Quantitative Analysis in Operations Management. Instructions for DIS 300-Transportation
Instructions for -Transportation 1. Set up the column and row headings for the transportation table: Before we can use Excel Solver to find a solution to C&A s location decision problem, we need to set
More informationA Production Problem
Session #2 Page 1 A Production Problem Weekly supply of raw materials: Large Bricks Small Bricks Products: Table Profit = $20/Table Chair Profit = $15/Chair Session #2 Page 2 Linear Programming Linear
More informationTAKING DECISION BASED ON THE REGRESSION MODEL USING EXCEL 2016
TAKING DECISION BASED ON THE REGRESSION MODEL USING EXCEL 2016 Ana-Maria Mihaela IORDACHE 1* ABSTRACT The management decision is represented by the process of choosing a line of action in order to achieve
More informationA Variable Capacity Parallel Machine Scheduling Problem
Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management Istanbul, Turkey, July 3 6, 2012 A Variable Capacity Parallel Machine Scheduling Problem Emine Akyol
More informationProposed Syllabus. Generic Elective: Operational Research Papers for Students of B.Sc.(Hons.)/B.A.(Hons.)
Proposed Syllabus for Generic Elective: Operational Research Papers for Students of B.Sc.(Hons.)/B.A.(Hons.) under the Choice Based Credit System Department of Operational Research University of Delhi
More informationSENSITIVITY AND DUALITY ANALYSES OF AN OPTIMAL WATER TREATMENT COST MODEL FOR GHANA. Douglas Kwasi Boah, Stephen Boakye Twum and Kenneth B.
SENSITIVITY AND DUALITY ANALYSES OF AN OPTIMAL WATER TREATMENT COST MODEL FOR GHANA Douglas Kwasi Boah, Stephen Boakye Twum and Kenneth B. Pelig-Ba 1 Faculty of Mathematical Sciences, Department of Mathematics,
More informationCHAPTER 5 SUPPLIER SELECTION BY LEXICOGRAPHIC METHOD USING INTEGER LINEAR PROGRAMMING
93 CHAPTER 5 SUPPLIER SELECTION BY LEXICOGRAPHIC METHOD USING INTEGER LINEAR PROGRAMMING 5.1 INTRODUCTION The SCMS model is solved using Lexicographic method by using LINGO software. Here the objectives
More informationOMGT2146. Supply Chain Analysis and Design. Introduction to Modeling. Course Information. Week 1
OMGT2146 Supply Chain Analysis and Design Week 1 Introduction to Modeling COMMONWEALTH OF AUSTRALIA Copyright Regulations 1969 WARNING This material has been reproduced and communicated to you by or on
More informationLinear Programming: Basic Concepts
Linear Programming: Basic Concepts Irwin/McGraw-Hill 1.١ The McGraw-Hill Companies, Inc., 2003 Introduction The management of any organization make Decision about how to allocate its resources to various
More informationDSS MODEL BASED ON RULES AND OLAP FOR MANAGEMENT BY BUDGETS
DSS MODEL BASED ON RULES AND OLAP FOR MANAGEMENT BY BUDGETS Ph. D. Lecturer Claudiu Brândaş West University of Timisoara, Romania Abstract Implementing Decision Support System (DSS) for the management
More informationGetting Started with OptQuest
Getting Started with OptQuest What OptQuest does Futura Apartments model example Portfolio Allocation model example Defining decision variables in Crystal Ball Running OptQuest Specifying decision variable
More informationLinear Programming and Applications
Linear Programming and Applications (v) LP Applications: Water Resources Problems Objectives To formulate LP problems To discuss the applications of LP in Deciding the optimal pattern of irrigation Water
More informationIntroduction to Management Science
Test Item File Introduction to Management Science Bernard W. Taylor III Martha Wilson California State University, Sacramento Upper Saddle River, New Jersey 07458 Contents Chapter 1 Management Science
More informationHEMCHANDRACHARYA NORTH GUJARAT UNIVERSITY, PATAN C B C S : B.Sc. PROGRAMME. S101 :: Statistical Methods - I
S101 :: Statistical Methods - I First Paper No. S 101 Course Name Statistical Methods - 1 Effective From June 2012 Unit Content Weitage Credit No. 1 Classification and Presentation of Data 1. Concept of
More informationENTREPRENEURSHIP DECISION MAKING MODEL FOR INVESTMENT ACTIVITY
Volume 22, Special Issue Print ISSN: 1098-8394; Online ISSN: 1528-2651 ENTREPRENEURSHIP DECISION MAKING MODEL FOR INVESTMENT ACTIVITY Svitlana Marova, Donetsk state University of management Valentyna Tokareva,
More informationLinear Programming. Chapter 2: Basic Concepts. Lee-Anne Johennesse. Advanced Quantitative Methods 7 March 2016
Linear Programming Chapter 2: Basic Concepts Lee-Anne Johennesse Advanced Quantitative Methods 7 March 2016 Linear Programming Chapter 2: Basic Concepts Introduction Part A The Wyndor Glass Company Product
More informationITT Technical Institute. BU334 Accounting Application to Internet Technology Onsite Course SYLLABUS
ITT Technical Institute BU334 Application to Internet Technology Onsite Course SYLLABUS Credit hours: 4 Contact/Instructional hours: 50 (30 Theory Hours, 20 Lab Hours) Prerequisite(s) and/or Corequisite(s):
More informationUse an Excel spreadsheet to solve optimization problems
Math 19 Project 4 (Work in groups of two to four.) Linear Programming Names Use an Excel spreadsheet to solve optimization problems Example 1: The Solar Technology Company manufactures three different
More informationWind Turbine Power Limitation using Power Loop: Comparison between Proportional-Integral and Pole Placement Method
International Journal of Education and Research Vol. 1 No.11 November 2013 Wind Turbine Power Limitation using Power Loop: Comparison between Proportional-Integral and Pole Placement Method 1* NorzanahRosmin,
More informationone Introduction chapter Overview Chapter
one Introduction Chapter chapter Overview 1.1 Introduction to Decision Support Systems 1.2 Defining a Decision Support System 1.3 Decision Support Systems Applications 1.4 Textbook Overview 1.5 Summary
More informationChapter 3 Formulation of LP Models
Chapter 3 Formulation of LP Models The problems we have considered in Chapters 1 and 2 have had limited scope and their formulations were very straightforward. However, as the complexity of the problem
More informationUsing Excel s Solver
Using Excel s Solver How to get the computer to do the work. A Profit Maximization Problem. Lecture 8 Slide 1 Is the Solver Installed If your Tools pulldown menu in Excel looks like this, without a Solver
More informationMasters Programs Course Syllabus
[SEMESTER].[HALF] [SCHOOL YEAR] 2 4 6 1 B U S I N E S S I N T E L L I G E N C E INSTRUCTOR: MIGUEL DE CASTRO NETO CONTACT: mneto@novaims.unl.pt http://www.novaims.unl.pt/mneto SHORT BIO: OFFICE HOURS:
More informationMANAGEMENT INFORMATION SYSTEMS 8/E
MANAGEMENT INFORMATION SYSTEMS 8/E Raymond McLeod, Jr. and George Schell Chapter 6 Systems Concepts Copyright 2001 Prentice-Hall, Inc. 6-1 Four Model Types 1) Physical models Three dimensional representation
More informationLean Manufacturing using Axiomatic Design
Lean Manufacturing using Axiomatic Design Sachpreet Singh Aulakh, Janpreet Singh Gill Abstract The manufacturing system design is the topic of discussion in this paper. Numerous manufacturing system design
More informationShort-Run Manufacturing Problems at DEC 2. In the fourth quarter of 1989, the corporate demand/supply group of Digital
Short-Run Manufacturing Problems at DEC 2 In the fourth quarter of 1989, the corporate demand/supply group of Digital Equipment Corporation (DEC) was under pressure to come up with a manufacturing plan
More informationMANAGEMENT INFORMATION SYSTEMS: DEFINITION AND ATTRIBUTION
1 MANAGEMENT INFORMATION SYSTEMS: DEFINITION AND ATTRIBUTION Amarin Tawata Faculty of Management Science Silpakorn University, Petchburi IT Campus 1 Moo 3 Tambon Sampraya Ampur Cha-Am Petchburi 76120,
More informationModeling Linear Programming Problem Using Microsoft Excel Solver
Modeling Linear Programming Problem Using Microsoft Excel Solver ADEKUNLE Simon Ayo* & TAFAMEL Andrew Ehiabhi (Ph.D) Department of Business Administration, Faculty of Management Sciences, University of
More informationENGG1811: Data Analysis using Excel 1
ENGG1811 Computing for Engineers Data Analysis using Excel (weeks 2 and 3) Data Analysis Histogram Descriptive Statistics Correlation Solving Equations Matrix Calculations Finding Optimum Solutions Financial
More informationCh.01 Introduction to Modeling. Management Science / Instructor: Bonghyun Ahn
Ch.01 Introduction to Modeling Management Science / Instructor: Bonghyun Ahn Chapter Topics The Management Science Approach to Problem Solving Model Building: Break-Even Analysis Computer Solution Management
More informationCombinatorial Optimization Model for Group Decision-Making
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 18, No 2 Sofia 2018 Print ISSN: 1311-9702; Online ISSN: 1314-4081 DOI: 10.2478/cait-2018-0028 Combinatorial Optimization Model
More informationCase on Manufacturing Cell Formation Using Production Flow Analysis
Case on Manufacturing Cell Formation Using Production Flow Analysis Vladimír Modrák Abstract This paper offers a case study, in which methodological aspects of cell design for transformation the production
More informationTotal Optimal Performance Scores: A Practical Guide for Integrating Financial and Nonfinancial Measures in Performance Evaluation
Total Optimal Performance Scores: A Practical Guide for Integrating Financial and Nonfinancial Measures in Performance Evaluation B Y J OHN B RIGGS, PH.D., CMA; M. CATHY C LAIBORNE, PH.D., CMA, CPA; AND
More informationINFORMS Transactions on Education
This article was downloaded by: [46.3.192.115] On: 01 January 2018, At: 02:32 Publisher: Institute for Operations Research and the Management Sciences (INFORMS) INFORMS is located in Maryland, USA INFORMS
More informationINFS 214: Introduction to Computing
INFS 214: Introduction to Computing Session 8 Application Software Lecturer: Dr. Ebenezer Ankrah, Dept. of Information Studies Contact Information: eankrah@ug.edu.gh College of Education School of Continuing
More informationA Fuzzy Multiple Attribute Decision Making Model for Benefit-Cost Analysis with Qualitative and Quantitative Attributes
A Fuzzy Multiple Attribute Decision Making Model for Benefit-Cost Analysis with Qualitative and Quantitative Attributes M. Ghazanfari and M. Mellatparast Department of Industrial Engineering Iran University
More informationA trim-loss minimization in a produce-handling vehicle production plant
ORIGINAL ARTICLE A trim-loss minimization in a produce-handling vehicle production plant Apichai Ritvirool 1 Abstract A trim-loss minimization in a produce-handling vehicle production plant Songklanakarin
More informationMULTI-SOURCING MULTI-PRODUCT SUPPLIER SELECTION: AN INTEGRATED FUZZY MULTI-OBJECTIVE LINEAR MODEL. Kittipong Luangpantao. Navee Chiadamrong.
MULTI-SOURCING MULTI-PRODUCT SUPPLIER SELECTION: AN INTEGRATED FUZZY MULTI-OBJECTIVE LINEAR MODEL Kittipong Luangpantao Logistics and Supply Chain Systems Engineering Program, Sirindhorn International
More informationTRIAGE: PRIORITIZING SPECIES AND HABITATS
32 TRIAGE: PRIORITIZING SPECIES AND HABITATS In collaboration with Jon Conrad Objectives Develop a prioritization scheme for species conservation. Develop habitat suitability indexes for parcels of habitat.
More informationCode No: RR Set No. 1
Code No: RR410301 Set No. 1 IV B.Tech I Semester Regular Examinations, November 2007 OPERATIONS RESEARCH ( Common to Mechanical Engineering, Mechatronics and Production Engineering) Time: 3 hours Max Marks:
More informationIntroduction to Management Science 8th Edition by Bernard W. Taylor III. Chapter 1 Management Science
Introduction to Management Science 8th Edition by Bernard W. Taylor III Chapter 1 Management Science Chapter 1- Management Science 1 Chapter Topics The Management Science Approach to Problem Solving Model
More informationEnhancing Forecasting Capability of Excel with User Defined Functions
Spreadsheets in Education (ejsie) Volume 2 Issue 3 Article 6 5-10-2008 Enhancing Forecasting Capability of Excel with User Defined Functions Deepak K. Subedi Marshall University, subedi@marshall.edu Follow
More informationExcel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray)
Gebauer/Matthews: MIS 213 Hands-on Tutorials and Cases, Spring 2015 111 Excel Solver Tutorial: Wilmington Wood Products (Originally developed by Barry Wray) Purpose: Using Excel Solver as a Decision Support
More informationCommon Tool for Intelligent Scheduling / Critical Chain Project Management for US Navy & Contractor Shipyards
Common Tool for Intelligent Scheduling / Critical Chain Project Management for US Navy & Contractor Shipyards Rob Richards, Ph.D. April 20, 2016 Planning, Production Processes & Facilities Panel (PPP&F)
More information231 Quantitative Applications in Management
231 Quantitative Applications in Management Objective of the course is to guarantee a deeper insight into the subject and lead towards analytical solutions to problems treated. This course is the foundation
More informationAnalysis of Agile and Multi-Agent Based Process Scheduling Model
International Refereed Journal of Engineering and Science (IRJES) ISSN (Online) 2319-183X, (Print) 2319-1821 Volume 4, Issue 8 (August 2015), PP.23-31 Analysis of Agile and Multi-Agent Based Process Scheduling
More informationThe Comparing Analysis between Network Modeling Module of Informatics Program WinQSB and Transportation Module of Informatics Program QM
ANALELE UNIVERSITĂłII EFTIMIE MURGU REŞIłA ANUL XV, NR. 1, 2008, ISSN 1453-7397 Olga Ioana Amariei, Denis Fourmaux, Constantin Dumitrescu, Raul Malos The Comparing Analysis between Network Modeling Module
More informationEffect of Transportation Model on Organizational Performance: A Case Study of MTN Nigeria, Asaba, Delta State, Nigeria
International Journal of Innovative Social Sciences & Humanities Research 6(2):76-82, April-June, 2018 SEAHI PUBLICATIONS, 2018 www.seahipaj.org ISSN: 2354-2926 Effect of Transportation Model on Organizational
More informationTransportation Cost Optimization
Transportation Cost Optimization Bashkim Çerkini Kellogg and Brown & Root, Ferizaj, Kosovë bashkimqerkini@gmail.com Roberta Bajrami University AAB, Ferizaj, Kosovë Roberta.Bajrami@universitetiaab.com Robert
More informationApplication of Dynamic Programming Model to Production Planning, in an Animal Feedmills.
Application of Dynamic Programming Model to Production Planning, in an Animal Feedmills. * Olanrele, Oladeji.O.,,2 Olaiya, Kamorudeen A. and 2 Adio, T.A.. The Polytechnic Ibadan, Mechatronics Engineering
More information2015 Conference Proceedings. Graphics
Graphics Design Refinement by Iterative Virtual Experimentation (DRIVE) for Analysis of Steering Column Mounting Bracket Design of an On-Highway Construction Vehicle Mr. Charles M. Matt Watson, CSTM, Morehead
More informationLinear programming A large number of decision pr
Linear programming A large number of decision problems faced by a business manager involve allocation of limited resources to different activities. Linear programming has been successfully applied to a
More informationCHAPTER 3 MODELLING AND SIMULATION
58 CHAPTER 3 MODELLING AND SIMULATION 3.1 NEED FOR SIMULATION Simulation is the use of modeling to represent (but not replicate ) a system or process at an appropriate level of detail, and thereby help
More informationA BI-OBJECTIVE MODELING FOR A CELLULAR MANUFACTURING SYSTEM DESIGN USING FUZZY GOAL PROGRAMMING UNDER UNCERTAINTY
Indian Journal of Fundamental and Applied Life Sciences ISSN: 645 (Online) An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/05/0/jls.htm 05 Vol. 5 (S), pp. 89-90/Ansari
More informationOPERATIONS RESEARCH SECOND EDITION. R. PANNEERSELVAM Professor and Head Department of Management Studies School of Management Pondicherry University
OPERATIONS RESEARCH SECOND EDITION R. PANNEERSELVAM Professor and Head Department of Management Studies School of Management Pondicherry University NEW DELHI-110001 2009 OPERATIONS RESEARCH, Second Edition
More informationPRODUCT-MIX ANALYSIS WITH DISCRETE EVENT SIMULATION. Raid Al-Aomar. Classic Advanced Development Systems, Inc. Troy, MI 48083, U.S.A.
Proceedings of the 2000 Winter Simulation Conference J. A. Joines, R. R. Barton, K. Kang, and P. A. Fishwick, eds. PRODUCT-MIX ANALYSIS WITH DISCRETE EVENT SIMULATION Raid Al-Aomar Classic Advanced Development
More informationTHE COST OF INTERNAL VARIETY: A NON-LINEAR OPTIMIZATION MODEL
INTERNATIONAL DESIGN CONFERENCE - DESIGN 2006 Dubrovni - Croatia, May 5-8, 2006. THE COST OF INTERNAL VARIETY: A NON-LINEAR OPTIMIZATION MODEL T. Nowa and M. Chromnia eywords: design for variety, cost
More informationDetermining the Significance of the Criteria Describing Enterprise Marketing
Determining the Significance of the Criteria Describing Enterprise Marketing Romualdas GINEVIČIUS Vilnius Gediminas Technical University LT-03 Vilnius, Saulėtekio al., Lithuania and Valentinas PODVEZKO
More informationGenetic Algorithms and Sensitivity Analysis in Production Planning Optimization
Genetic Algorithms and Sensitivity Analysis in Production Planning Optimization CECÍLIA REIS 1,2, LEONARDO PAIVA 2, JORGE MOUTINHO 2, VIRIATO M. MARQUES 1,3 1 GECAD Knowledge Engineering and Decision Support
More informationProject Manager Management Competency vs. Technical Competency. Which Is More Important to Overall Project Management Success?
Publications 4-2014 Project Manager Management Competency vs. Technical Competency. Which Is More Important to Overall Project Management Success? Barry Jon Bauer Embry-Riddle Aeronautical University,
More informationSCHEDULING PROBLEMS FOR JOBS AND DIFFERENT MACHINES WITH MAKE SPAN CRITERION AND LEFT TIME ALIGNMENT
Mechanical Testing and Diagnosis ISSN 47 9635, (IV), Volume 3, pp. 3- SCHEDULING PROBLEMS FOR JOBS AND DIFFERENT MACHINES WITH MAKE SPAN CRITERION AND LEFT TIME ALIGNMENT Daniel REZMIRES*, Alfredo MONFARDINI**,
More informationInfluence of Transformational Leadership, Organizational Culture and Trust on Organizational Commitment
International Journal of Managerial Studies and Research (IJMSR) Volume 4, Issue 9, September 2016, PP 47-51 ISSN 2349-0330 (Print) & ISSN 2349-0349 (Online) http://dx.doi.org/10.20431/2349-0349.0409006
More informationMODULE - 9 LECTURE NOTES 4 DECISION SUPPORT SYSTEMS
1 MODULE - 9 LECTURE NOTES 4 DECISION SUPPORT SYSTEMS INTRODUCTION DSS is an interactive computer-based system to help decision makers use communications technologies, data, documents, knowledge and/or
More informationUSING THE MIN/MAX METHOD FOR REPLENISHMENT OF PICKING LOCATIONS
Transport and Telecommunication, 2, volume 8, no., 9 8 Transport and Telecommunication Institute, Lomonosova, Riga, LV-9, Latvia DOI./ttj-2-8 USING THE / METHOD FOR REPLENISHMENT OF PICKING LOCATIONS Raitis
More informationEnhancing Microsoft Office PerformancePoint Server 2007 through Integrated Business Planning
Enhancing Microsoft Office PerformancePoint Server 2007 through Integrated Business Planning Because Performance is the Point River Logic enhances Microsoft s Business Intelligence platform by increasing
More informationDEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING. the Polytechnic Ibadan, Mechatronics Engineering Department; 3, 4
DEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING 1 Olanrele, O.O., 2 Olaiya, K. A., 3 Aderonmu, M.A., 4 Adegbayo, O.O., 5 Sanusi, B.Y. 1, 2,5 the Polytechnic Ibadan, Mechatronics
More informationCONSIDERATION OF FACTORS IN TURNAROUND REFINERY (TAR) PROJECT MANAGEMENT
CONSIDERATION OF FACTORS IN TURNAROUND REFINERY (TAR) PROJECT MANAGEMENT Fabić M. 1, Pavletić 2, D., Soković M. 3 1 Clinical Hospital Center Rijeka, Krešimirova 42, 51000 Rijeka, marko.fabic@gmail.com
More informationISE480 Sequencing and Scheduling
ISE480 Sequencing and Scheduling INTRODUCTION ISE480 Sequencing and Scheduling 2012 2013 Spring term What is Scheduling About? Planning (deciding what to do) and scheduling (setting an order and time for
More informationMAN256 Introduction to Management Science
MAN256 Introduction to Management Science Sections 01 & 02 FINAL EXAM May 21, 2004, 15:00 Student Name: Student Number: Notes: The exam s duration is 135 minutes. Use your time efficiently. This is a closed-book
More informationProgram Evaluation Methods and Case Studies
Test Bank for Program Evaluation Methods and Case Studies Eighth Edition Emil J. Posavac Loyola University of Chicago Prentice Hall Boston Columbus Indianapolis New York San Francisco Upper Saddle River
More informationAn Analysis of Cointegration: Investigation of the Cost-Price Squeeze in Agriculture
An Analysis of Cointegration: Investigation of the Cost-Price Squeeze in Agriculture Jody L. Campiche Henry L. Bryant Agricultural and Food Policy Center Agricultural and Food Policy Center Department
More informationInformation System of Scenario Strategic Planning
Information System of Scenario Strategic Planning Denis R. Tenchurin dtenchurin@gmail.com Maxim P. Shatilov maxim.shatilov@gmail.com Scientific advisor: prof. Sergei M. Avdoshin savdoshin@hse.ru Abstract
More informationSTUDY ON EXPERT SYSTEM FOR TOWED WATER-SAVING IRRIGATION MECHANIZATION TECHNOLOGY
STUDY ON EXPERT SYSTEM FOR TOWED WATER-SAVING IRRIGATION MECHANIZATION TECHNOLOGY Na.Jia 1, 2 1, 2,, Changle Pang, Zhuomao E 1, 2 1 China Agricultural University, College of Engineering, 17 Tsinghua East
More informationKeywords: Transportation problem; initial solution; distribution; algorithm; VAM, LC, NWC
American International Journal of Research in Science, Technology, Engineering & Mathematics Available online at http://www.iasir.net ISSN (Print): 2328-3491, ISSN (Online): 2328-3580, ISSN (CD-ROM): 2328-3629
More informationImprovement and Simulation of Rear Axle Assembly Line Based on Plant Simulation Platform
2017 International Conference on Mechanical Engineering and Control Automation (ICMECA 2017) ISBN: 978-1-60595-449-3 Improvement and Simulation of Rear Axle Assembly Line Based on Plant Simulation Platform
More informationApplied Data Analysis (Operations Research)
Applied Data Analysis (Operations Research) Pongsa Pornchaiwiseskul Pongsa.P@chula.ac.th http://j.mp/pongsa Faculty of Economics Chulalongkorn University Pongsa Pornchaiwiseskul, Faculty of Economics,
More informationModels in Engineering Glossary
Models in Engineering Glossary Anchoring bias is the tendency to use an initial piece of information to make subsequent judgments. Once an anchor is set, there is a bias toward interpreting other information
More informationTRANSSHIPMENT MODEL IN THE FUNCTION OF COST MINIMIZATION IN A LOGISTICS SYSTEM
48 TRANSSHIPMENT MODEL IN THE FUNCTION OF COST MINIMIZATION IN A LOGISTICS SYSTEM Teaching Assistant Faculty of Economics in Osije Croatia ABSTRACT Transportation is the most important subsystem of logistics
More informationIntroduction to Research
Introduction to Research Arun K. Tangirala Arun K. Tangirala, IIT Madras Introduction to Research 1 Objectives To learn the following: I What is data analysis? I Types of analyses I Different types of
More informationOptimal Planning of the Production of Corpus Details on Metal Cutting Machines with the Help of Computer Numeric Control
IOSR Journal of Computer Engineering (IOSR-JCE) e-issn: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 5, Ver. VI (Sep. - Oct. 2016), PP 86-90 www.iosrjournals.org Optimal Planning of the Production of
More informationMilitary Application of Multi-Criteria Decision Making
AARMS Vol. 14, No. 4 (2015) 291 297. Military Application of Multi-Criteria Decision Making GYARMATI József 1 Which is the most appropriate military device for the army based on user interest? This is
More informationAs government agencies and businesses become
RESEARCH FEATURE A Formal Process for Evaluating COTS Software s A software product evaluation process grounded in mathematics and decision theory can effectively determine product quality and suitability
More informationTIM/UNEX 270, Spring 2012 Homework 1
TIM/UNEX 270, Spring 2012 Homework 1 Prof. Kevin Ross, kross@soe.ucsc.edu April 11, 2012 Goals: Homework 1 starts out with a review of essential concepts from statistics in Problem 1 we will build on these
More informationMinimization of Billet Remnant Using Zero-One Integer Programming
Minimization of Billet Remnant Using Zero-One Integer Programming Julsiri Jaroenpuntaruk*, Chartchai Matrakul** Department of Industrial Engineering Faculty of Engineering Thammasat University, Rangsit
More informationPRODUCTIVITY PROFITABILITY B Y M OHAN P. R AO, P H.D. A Simple Method to Link
A Simple Method to Link PRODUCTIVITY to PROFITABILITY B Y M OHAN P. R AO, P H.D. When billions of dollars are invested in technology, business managers would like to know the impact of the investment on
More informationEngineering the German Way. To get the most value out of the summer school, we provide a combination of two courses:
Engineering the German Way Engineering the German Way (EGW) is a 4.5-week Summer School in Munich at the University of Applied Sciences. It offers an in-depth study of engineering and cultural business
More informationBuilding Flexible Project Plans with Microsoft Project 2010
Building Flexible Project Plans with Microsoft Project 2010 50586A; 2 Days, Instructor-led Course Description This two-day instructor-led course provides students with the knowledge and skills to create
More informationStructural Optimization Using the Grouping Method and the 1/3rd Rule Based on Specific Strain Energy
Young-Doo Kwon et al / International Journal of Engineering and Technology (IJET) Structural Optimization Using the Grouping Method and the 1/3rd Rule Based on Specific Strain Energy Young-Doo Kwon *1,
More informationPhysics 141 Plotting on a Spreadsheet
Physics 141 Plotting on a Spreadsheet Version: Fall 2018 Matthew J. Moelter (edited by Jonathan Fernsler and Jodi L. Christiansen) Department of Physics California Polytechnic State University San Luis
More informationDemand function and its role in a business simulator
MPRA Munich Personal RePEc Archive Demand function and its role in a business simulator Dominik Vymetal and Filip Ježek Silesian Univerzity in Opava, School of Business Administration in Karviná 22. March
More informationInstructor: Dr. Asad Esmaeily, 2139 Fiedler Hall, Tel: , Class web site:
Kansas State University CE 537 (3 Units) Spring 2004 Semester Civil Engineering Department Introduction to Structural Analysis Prof. Asad Esmaeily Instructor: Dr. Asad Esmaeily, 2139 Fiedler Hall, Tel:
More informationPrioritizing IT Projects: An Empirical Application of an IT Investment Model
Communications of the International Information Management Association, Volume 3 Issue 2 Prioritizing IT Projects: An Empirical Application of an IT Investment Model Adam D. Denbo California State Polytechnic
More informationAdvanced skills in CPLEX-based network optimization in anylogistix
Advanced skills in CPLEX-based network optimization in anylogistix Prof. Dr. Dmitry Ivanov Professor of Supply Chain Management Berlin School of Economics and Law Additional teaching note to the e-book
More informationIntroduction to Management Science, 11e (Taylor) Chapter 3 Linear Programming: Computer Solution and Sensitivity Analysis
Instant download and all chapters Test Bank Introduction to Management Science 11th Edition Bernard W. Taylor III https://testbankdata.com/download/test-bank-introduction-managementscience-11th-edition-bernard-w-taylor-iii/
More information231 Quantitative Applications in Management
231 Quantitative Applications in Management Objective of the course is to guarantee a deeper insight into the subject and lead towards analytical solutions to problems treated. This course is the foundation
More informationProject Portfolio Management Prototype Application Design
58 Project Portfolio Management Prototype Application Design Paul POCATILU Academy of Economic Studies, Bucharest The management of project portfolio in a company requires the use of specific software,
More informationAPPLICATIONS OF THE GROUP TECHNOLOGY THEORY IN MANUFACTURING
7 th INTERNATIONAL MULTIDISCIPLINARY CONFERENCE Baia Mare, Romania, May 17-18, 2007 ISSN-1224-3264 APPLICATIONS OF THE GROUP TECHNOLOGY THEORY IN MANUFACTURING Jozef Novak-Marcincin Prof. Ing. PhD., Faculty
More informationA Spreadsheet Approach to Teaching Shadow Price as Imputed Worth
A Spreadsheet Approach to Teaching Shadow Price as Imputed Worth Jerry D. Allison University of Central Oklahoma Edmond, OK 73034 Phone: (405) 974-5338 Fax: (405) 974-3821 Email: jallison@ucok.edu ABSTRACT
More informationCriteria For Selection of Software Development Environment For Construction Robotic Systems
Criteria For Selection of Software Development Environment For Construction Robotic Systems Khaled Zied and Derek Seward Engineering department, Lancaster University, Lancaster, LA1 4YR, UK k.zied@lancaster.ac.uk
More informationChapter 11. Decision Making and Relevant Information Linear Programming as a Decision Facilitating Tool
Chapter 11 Decision Making and Relevant Information Linear Programming as a Decision Facilitating Tool 1 Introduction This chapter explores cost accounting for decision facilitating purposes It focuses
More information