A FLEXIBLE APPROACH FOR THE DESIGN OF A MULTIMODAL TERMINAL SIMULATION MODEL

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1 A FLEXIBLE APPROACH FOR THE DESIGN OF A MULTIMODAL TERMINAL SIMULATION MODEL Alicia García and Isabel García Departament de Ingeniería Mecánica Universidad Carls III de Madrid. Avda. de la Universidad, Leganés (Madrid) agarci1@ing.uc3m.es, igarcia@ing.uc3m.es KEYWORDS Multimdal transprt, terminal simulatin, flexible design. ABSTRACT We present a decisin supprt tl fr the analysis and redesign f railrad intermdal terminals. It is a simulatin-based platfrm which prvides indicatrs f service level, resurce use and prductivity linked t the terminal peratins and infrastructures. The platfrm is cmpsed f tw basic elements: a simulatin mdel implemented in a cmmercial simulatr, Witness, and a cnfiguratin interface implemented in MS Excel. The cmbinatin f these cmpnents has facilitated building a very flexible and easy-t-use platfrm s that a user withut any knwledge f the simulatin sftware will be able t implement a simulatin mdel f the terminal, by nly filling in the required data thrugh an MS Excel file. As the design f the platfrm has fcused n flexibility, a wide range f terminals can be implemented, in terms f infrastructures, handling material, lay ut and train and demand patterns. We als present a case study t demnstrate the use f the platfrm. 1. INTRODUCTION Despite the well-knwn benefits that culd derive frm the use f intermdal transprt (energy efficiency, reduced rad cngestin and envirnmental damage ), the chice f a transprt mde relaies n the existence f a guarantee f the effectiveness and efficiency f the transprt service. Thus, it is critical t analyse the transprt chain frm a glbal perspective in rder t identify the bttlenecks and ther barriers that may be preventing the develpment f cmbined transprt. We believe that simulatin may play an imprtant rle in the develpment f the necessary quantitative tls, t analyse transprt netwrks. Hwever many times, the gap between researchers and managers has been a burden fr the use f simulatin in real life prblems. Therefre, in this research prject we have fcused n the design and develpment f a flexible and easy-tuse simulatin platfrm. In an intermdal chain many factrs critically affect perfrmance, and ne f them is the peratins that take place in the transhipment terminals. Therefre, the study and ptimizatin f terminal peratins has been the bject f many research wrks, especially in the last tw decades. Many simulatin mdels have been prpsed t study terminal peratins frm a hlistic perspective. Fr example, Shabayek and Yeung (2002) prpse a deterministic mdel implemented with Witness, which prvides fr indicatrs f resurce use in Hng Kng s cntainer terminal. Similarly, Crtés et al. (2007) shw a simulatin mdel implemented with the cmmercial sftware Arena, which represents the peratin f the Prt f Seville in detail, including the prcesses regarding truck management (entering/exiting the terminal and lading and unlading peratins); ship arrival and dck allcatin, unlading/lading peratins, etc. The simulatin delivers results regarding infrastructure and resurce use, truck flw and vessel thrughput time. These tw research wrks are gd examples f the benefits f using simulatin t study the perfrmance f a specific terminal. Hwever if the study is t be extended t an entire netwrk, a mre flexible mdel design f the mdel, such us the ne we present, culd be mre apprpriate, as the ttal develpment cst f the mdel wuld be significantly reduced. Mrever, the study f a variety f scenaris ften requires a substantial mdificatin f the mdel cde, if flexibility has nt been intrduced as a design requirement f the mdel. With the prpsed apprach, many f the changes that culd be intrduced t implement the alternative scenaris wuld be trivial. T stablish the research bjectives f this wrk we have chsen t fcus n the simulatin f railrad terminals in a rail netwrk, thereby develping a simulatin platfrm based n the cmbinatin f Witness, as the simulatin sftware, and MS Excel t develp the user interface. The details f the research wrk are structured as fllws: In sectin tw, we describe the system studied in terms f infrastructures, resurces and peratins. This cnceptualizatin leads t the specificatins f the mdel and the prgramming strategy adpted, which are explained in sectin 3. In sectin 4 we present a case study that illustrates the use f the simulatin platfrm. Finally, in sectin 5 we summarize the cnclusins f this research. Prceedings 23rd Eurpean Cnference n Mdelling and Simulatin ECMS Javier Otamendi, Andrzej Bargiela, Jsé Luis Mntes, Luis Miguel Dncel Pedrera (Editrs) ISBN: / ISBN: (CD)

2 2. TERMINAL CONCEPTUALIZATION There are a wide variety f terminals with varius characteristics: lcalizatin, mdes f transprt invlved, vlume f transhipments. These characteristics intrduce differences amng them which have t be carefully analysed t assess their ptential impact n the mdel flexibility. The mst significant criterin fr classifing terminals is prbably the number f mdes invlved in transhipment peratins. Regarding this criterin, we may divide the rail netwrk terminals int tw categries: marine and interir terminals. In the first type, there are ptentially three transprtatin mdes invlved (sea, rail and rad), whereas in the secnd entails, nly rail and rad mdes. In this research, we have chsen t fcus n interir terminals fr several reasns. First, they are less cmplex than marine terminals, and thus they cnstitute a better starting pint fr the develpment f the simulatin platfrm. Secndly, they have received less attentin in the related literature than the maritime nes. Finally, after a careful analysis f their characteristics, they seem t prvide a reasnable balance between a variety f characteristics (which justifies a flexible apprach), and cmmn aspects (which facilitates a successful implementatin). The experience gained in this first wrk will be used t extend the mdel apprach t the implementatin f maritime terminals. The interir railrad terminals mdelled perfrm the fllwing main prcesses: - Truck arrival and departure. - Truck lading and unlading. - Cntainer receptin and strage. - Train arrival and departure. - Train lading and unlading. T accmplish these prcesses, a variety f infrastructures and resurces are used. We present belw a brief descriptin f them. Figure 1 shws a scheme f these resurces and their cnnectins: - Entry and exit s used by the trucks. - Truck lading and unlading psitins. - Truck parking area. This is a FIFO queue used when all the lading/unlading psitins are in use. - Stacking areas. We have cnsidered tw types: Lng-term stacking yards. Mst f the terminal strage capacity is cncentrated in these yards. In the cases studied, these yards are separated frm the train lading/unlading area and cntainers have t be handled by mbile cranes. Shrt term stacking lines. Cntainers are stred in lines n bth sides f the lading/unlading tracks. These lines may usually be reached by the lading/unlading gantry cranes. We have included bth types f stacking areas in the mdel. The cntainers are generally stred in the lng-term stacking yards. Shrt-term stacking lines are reserved fr thse that are t be delivered in less than 24 hurs. Entry Exist Entry track Exit track Parking Truck lading/ unlading area Diesel engines Lng term stacking area Mbile cranes Shrt term stacking lines Gantry cranes Figure 1: Scheme f Terminal Infrastructure and Operatins - Terminal Enter/Exit tracks. We have assumed that the terminal has ne entry track and ne exit track, which are used by the trains t enter and exit the terminal. - Receptin/expeditin and lading/unlading tracks. We have cnsidered that all these tracks can assume any f the functins depending n the needs at any given time. - Cranes, used fr truck lading and unlading, t manage the stacking yards and fr train lading and unlading. Usually there are tw types f cranes in interir terminals with a certain cntainer vlume: gantry cranes and mbile cranes. In the Spanish case (which has been the reference fr many design aspects), gantry cranes are usually reserved fr train lading and unlading. In fact, they are nrmally attached t the lading/unlading tracks and can nly mve alng them, thereby making transhipments between trains and the shrt-term stacking yards. Mbile cranes may be used fr all

3 the lading/unlading peratins that take place at the terminal. Therefre, we evaluated tw alternatives: Using gantry cranes fr train lading and unlading and mbile cranes fr these tw peratins and als fr truck lading and unlading and peratins in the lng-term stacking yards. Specialized functins: the gantry cranes wuld have the same use as in the frmer alternative, and mbile cranes wuld nly be used fr truck lading and unlading and peratins in the lng-term stacking yards. We adpted the secnd alternative because we estimated that the use f mbile cranes fr the same functin perfrmed by gantry cranes wuld be a rather unusual situatin, which culd just be mitted in the simulatin. - Diesel engines, which are in charge f the train mvement inside the terminal. - The human persnnel wh perate the terminal have nt been cnsidered explicitly, as mst f them are crane peratrs. Mrever, cranes are scheduled fllwing peratr shifts and therefre, peratr activity may be mnitred thrugh the perfrmance measures linked t crane use. 3. DESIGN AND IMPLEMENTATION OF THE SIMULATION PLATFORM The first decisin regarding platfrm design is the chice f simulatin sftware. In this case, this decisin did nt require much analysis because the research team had substantial experience with the use f Witness t develp cmbined transprt mdels (see García and Gutiérrez, 2003; Marín et al., 2004). In thse situatins the sftware had perfrmed very well. Additinally, the fact f having previus knwledge f the sftware was anther pint in its favur. The decisin abut the user interface was mre cmplicated and required the cmparisn f varius appraches. Tw f them were thrughly explred: - The use f Witness utilities, mainly mdules and dialgue bxes. - A MS Excel file apprpriately cmbined with the Witness mdel. After cmparing them, we chse the secnd alternative, mainly because its implementatin seemed faster and mre rbust and because it permits defining a terminal mdel fr any user regardless f simulatin language. The starting pint fr the platfrm design was the cnceptualizatin described in the previus sectin. Each f these elements was analysed in detail in rder t establish the mdel specificatins regarding it. The aim was t btain the right balance between flexibility and specifity. Fr example, the number f mbile cranes is ne f the characteristics that changes frm ne terminal t anther. Therefre, the platfrm shuld allw the user t establish the number f mbile cranes at a terminal. At the same time, the mre flexible the mdel design is, the mre cmplex the mdel prgramming becmes. In this case, the right equilibrium was reached in allwing the user t establish the number f gantry cranes fr any quantity between 0 and 8. Anther feature f the simulatin platfrm is related t the use f mdules. The terminal peratins may be divided int functinal areas, accrding t the terminal activities mentined in the previus sectin. We have identified five areas, each f which led t a mdule: - Truck lading and unlading mdule. - Train lading and unlading mdule. - Cntainer receptin and strage mdule. - Lng term stacking yard mdule. - Mbile cranes mdule. All these mdules are prgrammed t leave mst f the defining elements expressed as parameters, the values f which shall be entered by the user thrugh the MS Excel file. The MS Excel file reprduces the same structure as the Witness mdel, using a separate sheet fr each mdule. In the next tw subsectins, we explain in greater detail the tw main building blcks f the platfrm Witness Simulatin Mdel We present belw a brief explanatin f the main activities simulated by the mdel. - Truck unlading. The trucks arrive at the terminal accrding t a stchastic arrival pattern, defined by the user. The truck enters the terminal and if pssible, ccupies an unlading psitin. In the case that all psitins are taken, it waits in the terminal parking area until a psitin is available. The unlading prcess nly begins when the truck is in the unlading psitin and a mbile crane is available t perfrm the task. When the unlading task is finished the truck leaves the terminal and the mbile crane transprts the cntainer t the apprpriate stacking yard. - Truck lading. This prcess is rather symmetrical t the unlading prcess described bellw. The main difference is that the truck arrival generates a

4 search rder fr the apprpriate cntainer that is executed as sn as a mbile crane is available. Figure 2 shws the truck lading and unlading mdule. Entry Truck lading/ unlading area Mbile cranes Lng term stacking area 3.2. User Interface. MS Excel File The user interface is implemented thrugh a MS Excel file. The file is structured by sheets, each f which crrespnd t a Witness mdule. All the data necessary t define the infrastructure, demand, train schedule is intrduced by the user thrugh this MS Excel file and the user des nt need t d any prgramming wrk in Witness. Once all the required data is filled in, the user can just pen the Witness file and run the simulatin. Exit Parking Shrt term stacking lines The file is structured as fllws: - General data: Terminal layut, lad receptin hurs, maximum number f destinatins Figure 2: Simulatin Mdel Truck Lading and Unlading Mdule - Train unlading. Trains arrive at the terminal accrding t a fixed schedule. The train enters using a single entry track. Afterwards, the electric engine is substituted by the diesel engine, which carries the train t an available lading/unlading track. The unlading prcess is perfrmed by a gantry crane and the cntainers are prvisinally stred in the shrt-term stacking lines. Next, mbile cranes transprt the cntainer t the lng-term stacking yard r t the truck lading area. - Train lading. The trains als leave the terminal accrding t a fixed schedule. When the remaining time fr train departure reaches the limit specified a lading rder fr the train is generated. The cntainers that are t be laded are transprted frm the lng-term stacking yard t the shrt-term stacking lines. Subsequently, the gantry cranes transfer the cntainers frm the stacking lines t the train. When the lading prcess is finished, the electric engine is fixed and the train waits until departure time. The results prvided by the simulatin may be gruped int three sets: service level, prductivity and resurce use. Service level results arising frm the mdel are, fr example: the number f trains per week which fail t be laded, average and maximum waiting time fr trucks, average and maximum cntainer time at the terminal. Terminal prductivity is measured by the number f laded and unladed trucks per day and the average train length (in number f cntainers). Finally, the mdel quantifies the use f the terminal resurces: gantry and mbile cranes, engines, stacking areas, lading/unlading tracks and parking areas. - Truck lading/unlading area: Number f s, entry prcessing time, parking capacity, number f lading/unlading psitins and truck arrival distributins. - Train lading/unlading area: trains timetable, number f tracks, advance befre the scheduled departure fr the train lading and minimum and maximum length f trains. - Mbile cranes: number f cranes, wrk shifts, crane speed, cntainer lading and unlading time. - Gantry cranes: number f gantry cranes, cntainer lading and unlading time. - Diesel engines: number f engines, wrking shifts, speed and time required t change between electric engine and diesel engine. - Stacking areas: stacking area dimensins and maximum stacking height. The afrementined time data may be defined as determininate parameters r as randm distributins. As an example, in the case f the input f the number f mbile cranes, Figure 3 shws the manner in which the MS Excel interface and the Witness mdel are linked. In the Figure s upper left crner the MS Excel is shwn. The MS Excel sheet prvides a brief explanatin abut the parameters that must be entered by the user. The table shws the three default values, which may be changed by the user, fr the three required parameters: number f mbile cranes that wrk ne, tw r three shifts. The right lwer crner f Figure 4 shws the cde that creates the specified number f mbile cranes in the Witness mdel.

5 MS Excel interface Witness simulatin mdel traffic is named D=1 and the subsequent indexes, 2 t 5, crrespnd t the fur destinatin rail terminals. The incming (I) and utging (O) trains fllw the schedule shwn in Table 1. Fr the utging trains, the table specifies the destinatin index. Table1: Train Timetable Figure 3: Data Input fr the Number f Gantry Cranes The user interface has been furnished with many utilities which prevent it frm making mistakes in the data input prcess: explanatins abut the data required, errr messages that display when the input intrduced is incrrect, links between sheets which help fllw the right rder and prtecting instruments s that the sheet structure cannt be mdified. 4. CASE STUDY In this sectin, we present an applicatin f the simulatin platfrm used t study the capacity f a terminal. The case study is based n an existing cntainer terminal in Spain Simulated Scenari The terminal studied has the fllwing resurces and infrastructures: - Tw entry s and tw exit s fr trucks. The time spent by trucks at these s fllws a randm empirical distributin, varying between 4 and 6 minutes. - The parking area has a maximum capacity f 4 trucks. The parking area is used in the case that all the lading/unlading psitins are ccupied. - The lng term stacking area has a maximum capacity f 440 ITUs, and the shrt-term stacking lines have a maximum capacity f 180 ITUs. - One entry track and ne exit track. Fur lading/unlading tracks and ne diesel engine. - Tw gantry canes and tw mbile cranes the prcessing times f which have been represented as randm empiric distributins. The terminal exchanges cntainers with fur ndes f the rail cntainer netwrk and distributes and receives rad traffic within its wn regin. The destinatins are cded by indexes D=i, i=1 5. The utging rad Mn Tue Wed Thur Fri Sat Sun 1:40 I I I I I I 6:35 O 2 O 2 O 2 O 2 O 2 O 2 9:10 I I I I I 10:00 O 3 O 3 O 3 13:12 I I I 21:20 O 4 O 4 O 4 O 4 O 4 21:40 I The lading rder is pened 120 minutes prir t the train departure and it is clsed 20 minutes prir t it. A lading rder will nly be accepted if there is a minimum f six train platfrms t be laded. Truck traffic is apprximately 80 trucks a day, including bth delivery and cllectin flws. The arrivals f the trucks distribute randmly with a daily seasnality Results Analysis We have simulated the previusly-described terminal peratin. The duratin f the simulatin was ne week. As sme f the inputs are stchastic variables, we carried ut five replicatins. The results demnstrate a lw r very lw use f the terminal equipment. As shwn in Table 2, the average percentage f ttal time that the tw mbile cranes are used (MC) is nearly t 40%. The percentage f time that the tw gantry cranes are used is even lwer: apprximatelly 13%. Finally, the use f the diesel machine that mves the trains inside the terminal is just ccasinal and represents less than 2% f ttal time. Table 2: Use Percentage f Terminal Equipment MC GC DM Rep Rep Rep Rep Rep Average S.D Similar results are btained regarding t the use f infrastructures. Table 3 shws the average and standard deviatin btained fr the five replicatins fr the use f entry and exit s f the terminal (bth ccupied arund 14% f ttal time), the trucks lading/unlading

6 psitins, which are used nly 5.3% f ttal time and the tracks, which are used abut 12% f ttal time. Table 3: Infrastructures Percentage f Ttal Time Used Entry Gates Exit Gates Lad/Unlad Tracks This resurce availability leads t gd results in terms f service quality. Fr example: - The waiting times in the truck lading/unlading mdule are small. As we explained befre, there is a parking area where trucks may wait t be prcessed if all the lading/unlading psitins are ccupied. As shwn in Table 4, the average value fr the waiting time in this parking area is 1.06 minutes. Once there is an available lading/unlading psitin, the truck waits an average time f 2.57 minutes fr the mbile crane t arrive if it is waiting t be laded, and an average f 1.66 minutes, if it is waiting t be unladed. The fact that waiting time fr the lading prcess is higher than the waiting time fr the unlading is cnsistent with the mdel hypthesis, as the frmer invlves the additinal peratin f finding the cntainer t be laded in the stacking area. Table 4: Waiting Times in the Truck lading/unlading Mdule (Minutes) Parking Lading Unlading The perfrmance indicatrs assciated with train lading/unlading prccesses als have satisfactry values: As we shw in Table 5, the average time emplyed in train lading is minutes and the mean time fr train unlading is minutes. - The average cntainer delay at the terminal is high: apprximately 45 hurs. This value is related t train frequency and the destinatin f cntainers. - Finally, the average number f cntainers n a train is relatively high: 24 cntainers. Table 5: Results f the Train Lading/Unlading Mdule Lading (min) Unlading (min) Number f Cnt Even if the general picture f the terminal perfrmance shws a clear resurce availability in average values, the simulatin has revealed that the system als has sme peaks that ccasinally cause resurce verlad: - We have bserved sme punctual demand peaks, which cause verlading at sme terminal pints. Fr example, smetimes the influx f trucks is t high t be managed at the entry s and sme trucks are rejected. As shwn in Table 6, the absence f a queue utside the terminal, causes at these peak mments the rejectin f 6 trucks which intend t unlad cntainers and 1.6 trucks that are cming t pick up cntainers. - The mbile cranes have als experienced verlad, which causes transitry blcking in the cntainer transhipments between the lng-term stacking yard and the shrt-term stacking lines. In this mdel, mbile crane verlading leads t the rejectin f sme lading rders, namely, an average f 3.2 rders, cnsidering the five replicatins (see Table 6). Table 6: Number f Trucks and Trains Rejected Trucks fr lading Trucks fr unlading Trains fr lading Trains fr unlading CONCLUSIONS We have presented a simulatin platfrm that is designed t leave mst f the infrastructure, demand and resurces characteristics in a parametric frm, s that the user may implement a wide range f different terminal cnfiguratins by nly entering the required data int a very easy-t-use interface. This flexible apprach is especially useful in generating varius scenaris in the terminal redesign prcess easily and quickly. It can als be very interesting when the bjective is t create a netwrk mdel with many different terminals. T illustrate the use f the platfrm, we have implemented a case study where a terminal is represented. We have measured the terminal perfrmance in terms f average values, but we have als studied the exceptinal mments when resurces becme verladed. REFERENCES Abacumkin, C. and Ballis, A Develpment f an expert system fr the evaluatin f cnventinal and innvative technlgies in the intermdal transprt area. Eurpean Jurnal f Operatinal Research. N. 152,

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