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研究生:艾蔓妲
研究生(外文):Amanda Guadalupe Rodriguez Lopez
論文名稱:Dock Assignment and Truck Scheduling at Cross-docking Terminals
論文名稱(外文):Dock Assignment and Truck Scheduling at Cross-docking Terminals
指導教授:丁慶榮丁慶榮引用關係
學位類別:碩士
校院名稱:元智大學
系所名稱:工業工程與管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:英文
論文頁數:96
中文關鍵詞:Cross-dockingTruck SchedulingDock AssignmentReduced Variable Neighborhood SearchSupply Chain Management
外文關鍵詞:Cross-dockingTruck SchedulingDock AssignmentReduced Variable Neighborhood SearchSupply Chain Management
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In a cross docking system products are received at the terminal, occasionally gathered with other products going to the same destination, then shipped at the earliest opportunity, without going into long-term storage. Applying cross docking in the distribution network can reduce transportation cost, the inventory holding cost, cycle time and increase customer satisfaction. In order to obtain such benefits, the company should be able to operate the cross docking effectively and efficiently. For this purpose several scheduling and door assignment procedures have been introduced in recent years, which aim at solving the so called truck scheduling and dock assignment problem.
This research deals with both dock assignment and truck scheduling problems. The integration of both problems is discussed in two scenarios: one considers a static dock assignment and truck scheduling, and the other one addresses a dynamic dock assignment and truck scheduling. Mathematical formulations for both problems are first presented as 0-1 integer programming models. Since both dock assignment and truck scheduling problems are NP-hard, the integration of both problems is more difficult to solve. Thus we propose different heuristic algorithms to solve the integrated problem. For the static dock assignment and truck scheduling three different reduced variable neighborhood search (RVNS) algorithm frameworks are proposed, while for the dynamic dock assignment and truck scheduling a RVNS algorithm with three different types of solution initialization is proposed. The experimental results show that the RVNS algorithms for the static dock assignment and truck scheduling are capable of finding good solutions in a much shorter computation time when it is compared with Gurobi optimizer solutions. For the RVNS for the dynamic dock assignment and truck scheduling it was observed that the algorithm converges to the same quality of solution no matter the type of initial solution generated for small instances, however for large instances a better quality of solution is obtained when the algorithm is seeded by a construction heuristic.

In a cross docking system products are received at the terminal, occasionally gathered with other products going to the same destination, then shipped at the earliest opportunity, without going into long-term storage. Applying cross docking in the distribution network can reduce transportation cost, the inventory holding cost, cycle time and increase customer satisfaction. In order to obtain such benefits, the company should be able to operate the cross docking effectively and efficiently. For this purpose several scheduling and door assignment procedures have been introduced in recent years, which aim at solving the so called truck scheduling and dock assignment problem.
This research deals with both dock assignment and truck scheduling problems. The integration of both problems is discussed in two scenarios: one considers a static dock assignment and truck scheduling, and the other one addresses a dynamic dock assignment and truck scheduling. Mathematical formulations for both problems are first presented as 0-1 integer programming models. Since both dock assignment and truck scheduling problems are NP-hard, the integration of both problems is more difficult to solve. Thus we propose different heuristic algorithms to solve the integrated problem. For the static dock assignment and truck scheduling three different reduced variable neighborhood search (RVNS) algorithm frameworks are proposed, while for the dynamic dock assignment and truck scheduling a RVNS algorithm with three different types of solution initialization is proposed. The experimental results show that the RVNS algorithms for the static dock assignment and truck scheduling are capable of finding good solutions in a much shorter computation time when it is compared with Gurobi optimizer solutions. For the RVNS for the dynamic dock assignment and truck scheduling it was observed that the algorithm converges to the same quality of solution no matter the type of initial solution generated for small instances, however for large instances a better quality of solution is obtained when the algorithm is seeded by a construction heuristic.

Abstract...…………………...…………………………………………………… ii
Table of Content..…...……...………….…………………………………………. iv
List of Figures.…...…..………………………………………………………….. vii
List of Tables.....………………………………………………………………….. viii
Chapter 1 Introduction …………………………………………………………... 1
1.1 Research Background ….…………………………………………...….. 1
1.2 Motivation …………………….…………………………………......… 3
1.3 Research Objective …………….………………………………….....… 4
1.4 Thesis Organization …………….………………………………...…… 4
Chapter 2 Literature Review …………………………………………………..... 5
2.1 Cross docking …………………………………………….………...….. 5
2.1.1 Dock Assignment ...............................................................…...... 5
2.1.2 Truck Scheduling ……………………………………………...... 8
2.2 Machine Scheduling ……………………………………………....…… 11
2.3 Dock Assignment and Truck Scheduling ………………………....…… 12
2.4 Variable Neighborhood Search …………………………………....…… 13
2.5 Summary …………………………………….…………………......….. 16
Chapter 3 Static Dock Assignment and Truck Scheduling …………………….... 17
3.1 Problem Statement ……………………………………….………...….. 17
3.2 Dock Assignment Problem ……………………………….………...….. 18
3.2.1 Assumptions ………………………...…………….………...….. 18
3.2.2 Model 1: Mixed Service Mode ..................................................... 18
3.2.3 Model 2: Exclusive Service Mode ……………………………... 20
3.3 RVNS for Model 1 ……………………………………………..……..... 21
3.4 RVNS for Model 2 ……………………………………………..……..... 24

3.5 Sequence of Trucks …………………………………………………..... 27
3.5.1 Assumptions ………………………...…………….…..….....….. 27
3.5.2 Notation ……………………...………………….......……....….. 27
3.5.3 Problem Formulation …………..……………..........….........….. 29
3.5.4 RVNS for Truck Sequencing …...........................……………..... 33
Chapter 4 Dynamic Dock Assignment and Truck Scheduling ………………...... 42
4.1 Problem Statement ……………...………………….…….………...….. 43
4.2 Model Formulation ……………………………………….………...….. 44
4.2.1 Assumptions ……………...……………………….………...….. 44
4.2.2 Notation ……………...……………………………………...….. 45
4.3 Mathematical Formulation ……………………………….………...….. 46
4.4 RVNS for Dynamic Dock Assignment and Truck Scheduling ……..….. 48
4.4.1 Algorithm Framework ……………………………...…….....….. 48
4.4.2 Solution Representation …………………….……...…….....….. 49
4.4.3 Neighborhood Structures ……...………...….……...…….....….. 50
Chapter 5 Numerical Experiments …………………………………………….... 54
5.1 Dock Assignment ……………...……………….………..…..……...….. 54
5.1.1 Testing Models for Optimal Solutions ……………………......... 54
5.1.2 RVNS Results ….....................................................................….. 56
5.2 Static Dock Assignment and Truck Scheduling.…..……..…..……...….. 61
5.2.1 Problem Size …………………………………………………… 61
5.2.2 Testing for Optimal Solutions …….……………………………. 62
5.2.3 RVNS Results …………………….……………………………. 64
5.3 Dynamic Dock Assignment and Truck Scheduling ……..…..……...….. 69

Chapter 6 Conclusions and Future Research .………………………………….... 74
6.1 Conclusions ……………………………………………………………. 74
6.2 Future Research …..……………………………………………………. 75
References ……………………………………………………………………..... 76
Appendix …………………………………………………..…………………..... 80
Appendix A: Flow Matrixes for Small Instances…......…………………..... 80
Appendix B: Impact of the Number of Iterations in the Static Dock
Assignment RVNS……..…………………………..………..... 81
Appendix C: Impact of the Number of Iterations in the Dynamic Dock
Assignment RVNS……..…………………………..………..... 83
Appendix D: Results for the Static Dock Assignment and Truck Scheduling 85
Appendix E: Results for the Dynamic Dock Assignment and Truck
Scheduling…………………………………………………….. 86
Appendix F: Results for the t-test performed among three RVNS
Frameworks……………………….………………..………..... 91
Appendix G: Results for the t-test performed among three types of
Initialization...…………………….………………..………..... 94


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