Maximizing reader insights into the challenges facing maritime supply chains and container port logistics service providers in Asia, this book highlights their innovative responses to these challenges through real-world case studies.
With a focus on mathematical modeling, simulation and heuristics approaches, this book provides academics, engineers, container terminal operators, students in logistics and supply chain management with the latest approaches that can be used to address the planning and scheduling problem in large container terminal yards.
This book can be used on a self-contained basis as teaching cases in an undergraduate or specialist class setting, or on techniques applied to maritime container operations for port operations.
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1 | (4) |
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4 | (1) |
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2 Maritime Terminal Operational Problems |
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5 | (26) |
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2.1 Container, Container Vessels, and Configuration of a Container Terminal |
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5 | (9) |
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8 | (2) |
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10 | (1) |
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11 | (2) |
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2.1.4 Practical Example of CT: PSA Singapore Terminals |
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13 | (1) |
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14 | (2) |
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16 | (15) |
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16 | (3) |
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19 | (1) |
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20 | (3) |
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2.3.4 Integration of Decision Problems |
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23 | (2) |
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25 | (6) |
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3 Discrete Time Model and Algorithms for Container Yard Crane Scheduling |
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31 | (22) |
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31 | (3) |
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34 | (1) |
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3.2.1 Some Approaches to YC Work Schedules |
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34 | (1) |
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35 | (7) |
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36 | (1) |
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36 | (1) |
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37 | (3) |
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40 | (2) |
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3.4 Model Integrated with Heuristics (DMIP2) |
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42 | (2) |
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43 | (1) |
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3.5 Rolling-Horizon Algorithm for DMIP2 (DMIP3) |
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44 | (4) |
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3.5.1 Constraints and Sets Used in the Rolling-Horizon Algorithm |
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46 | (1) |
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3.5.2 Flow Diagram of Rolling-Horizon Algorithm |
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46 | (2) |
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48 | (1) |
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3.6 Influence of Weights in Objective Function |
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48 | (1) |
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49 | (4) |
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Appendix 1 Definition of Sets and Parameters |
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50 | (1) |
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51 | (2) |
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4 A Continuous-Time Model for Multiple Yard Crane Scheduling with Last-Minute Job Arrivals |
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53 | (32) |
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53 | (5) |
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53 | (1) |
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54 | (2) |
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56 | (2) |
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4.2 Continuous-Time Model (CMIP1) |
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58 | (12) |
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59 | (1) |
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59 | (7) |
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66 | (1) |
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67 | (3) |
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4.3 Algorithms Integrated with the Continuous-Time Model |
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70 | (6) |
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70 | (2) |
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4.3.2 Rolling-Horizon Algorithm (RHA) |
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72 | (1) |
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4.3.3 Results of the Continuous-Time Model Integrated with Heuristics and RHA |
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73 | (3) |
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4.4 Last-Minute Job Arrivals |
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76 | (1) |
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77 | (1) |
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4.5.1 The Best Performance Measure |
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77 | (1) |
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4.5.2 Influence of Objective Weights |
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78 | (1) |
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78 | (7) |
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Appendix 1 Definition of Sets and Parameters |
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78 | (2) |
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Appendix 2 Constraints Used in CMIP2 |
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80 | (3) |
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83 | (2) |
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85 | (12) |
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5.1 Concurrent Scheduling |
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85 | (2) |
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87 | (1) |
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5.3 Clustering-Reassigning Heuristic |
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88 | (6) |
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89 | (2) |
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5.3.2 Comparison with the Continuous MILP Model |
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91 | (3) |
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94 | (3) |
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94 | (3) |
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6 Validation via Simulation |
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97 | (12) |
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6.1 Simulation at the Block Level |
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97 | (2) |
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6.2 Simulation at the Terminal Level |
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99 | (8) |
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6.2.1 The Simulation Model |
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100 | (4) |
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104 | (3) |
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107 | (2) |
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108 | (1) |
| Index |
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109 | |
Dr. Wenkai Li is currently an assistant professor at International University of Japan, Japan teaching Operations Management, Supply Chain Management and Applied Statistics. He has held appointments as research fellows at National University of Singapore, the Logistics Institute-Asia Pacific and Monash University, Australia. Dr. Li has also acted as a consultant to organizations such as PSA Corp., Singapore, Emerson Singapore, DFS Singapore, Sinopec Group, China, PetroChina, China, etc. Dr. Li has been working and published extensively on areas such as maritime terminal, retailer, refinery, airlines, etc.
Dr. Yong Wu is currently a lecturer at the Department of International Business and Asian Studies, Griffith University, Australia. He obtained his Ph.D. degree from Nanyang Technological University, Singapore and his Master's degree from Nanjing University of Aeronautics and Astronautics, China. He teaches in the area of logistics and supply network management and his research interests include supply network modelling and simulation, logistical operations research and global optimization and computational intelligence for problems in logistics and supply network management and other related areas. He is a member of the Institute for Operations Research and the Management Sciences (INFORMS).
Prof. Mark Goh is an associate professor at NUS Business School and the Director (Industry Research) at the Logistics Institute-Asia Pacific. He has held appointments as a visiting Professor in Business Logistics Strategy at Chulalongkorn University, Commonwealth Fellow to the UK, Citibank International Fellow to the US, visiting research fellow at UMIST, visiting scholar at Beijing University, visiting professor at Melbourne University, Universiti Sains Malaysia, Sun Yat-Sen University, Kaohsiung, King Mongkut University of Technology Thonburi, and professor at the University of South Australia. He is currently on the editorial boardsof several leading journals. His current research interest is on buyer-seller relationships, performance measurement and supply chain strategy, with over 280 technical papers in internationally refereed journals and conferences.
Lisainfo e-raamatute kohta