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Integrated Scheduling of Quayside Cranes and Auto-Guided Vehicles for Quayside Operation in Automated Container Terminals.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Integrated Scheduling of Quayside Cranes and Auto-Guided Vehicles for Quayside Operation in Automated Container Terminals./
作者:	Zhaoyu, Chen.
面頁冊數:	1 online resource (87 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-04, Section: A.
Contained By:	Dissertations Abstracts International84-04A.
標題:	Operating systems. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29352730click for full text (PQDT)
ISBN:	9798352684795

Integrated Scheduling of Quayside Cranes and Auto-Guided Vehicles for Quayside Operation in Automated Container Terminals.
Zhaoyu, Chen.

Integrated Scheduling of Quayside Cranes and Auto-Guided Vehicles for Quayside Operation in Automated Container Terminals. - 1 online resource (87 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: A.

Thesis (M.E.)--National University of Singapore (Singapore), 2022.

Includes bibliographical references

Auto-Guided-Vehicles (AGV) have been considered as the solution for horizontal transportation of containers in automated container seaports. In recent years, the evolving Quay Crane (QC) automation technology makes it possible to achieve seamless coordination between AGVs and Automated QCs. In this study, Quayside operation will be modeled as a blocking parallelmachine flow shop scheduling problem (BPMFSS). AGV operations will be integrated and scheduled to optimize its operational efficiency in container terminals.In this study, the quayside operation in automated container terminals will be decomposed into multiple stages. A BPMFSS model is established for integrated scheduling for QCs and AGVs at quayside operation, with the introduction of "flow machines" representing each operation stage. Three machines represent AGV traveling to QC for container delivery or pickup, AGV parking under QC, and AGV interacting with QC, respectively. Once the AGV finishes its operation, it will depart from the last machine and is free for the next job order. With the aversion of traffic management at Quayside, entry and exit of AGV operation zone will be regulated to reduce the possibility of congestion under QC.A Mixed-integer programming model (MIP) is formulated for this scheduling problem, with an objective to minimize total completion time. Three derivative models are developed based on the base model to reflect different operational strategies. A Sequential Heuristic solution method and a PSO-based solution method are proposed to solve this MIP model. Inspired by the proposed Sequential Heuristic method, a learning cycle is applied to study the behavior of optimal solutions, which will help to refine the process sequence for the proposed Sequential Heuristic Method. Numerical results show that the proposed Learning-Based Sequential Heuristic Method processes excellent efficiency in solving this model. And several propositions are provided to evaluate the performance of different QC operation practices for automated container terminals.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352684795Subjects--Topical Terms:

3681934
Operating systems.
Index Terms--Genre/Form:

542853
Electronic books.

Integrated Scheduling of Quayside Cranes and Auto-Guided Vehicles for Quayside Operation in Automated Container Terminals.
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504 $a Includes bibliographical references
520 $a Auto-Guided-Vehicles (AGV) have been considered as the solution for horizontal transportation of containers in automated container seaports. In recent years, the evolving Quay Crane (QC) automation technology makes it possible to achieve seamless coordination between AGVs and Automated QCs. In this study, Quayside operation will be modeled as a blocking parallelmachine flow shop scheduling problem (BPMFSS). AGV operations will be integrated and scheduled to optimize its operational efficiency in container terminals.In this study, the quayside operation in automated container terminals will be decomposed into multiple stages. A BPMFSS model is established for integrated scheduling for QCs and AGVs at quayside operation, with the introduction of "flow machines" representing each operation stage. Three machines represent AGV traveling to QC for container delivery or pickup, AGV parking under QC, and AGV interacting with QC, respectively. Once the AGV finishes its operation, it will depart from the last machine and is free for the next job order. With the aversion of traffic management at Quayside, entry and exit of AGV operation zone will be regulated to reduce the possibility of congestion under QC.A Mixed-integer programming model (MIP) is formulated for this scheduling problem, with an objective to minimize total completion time. Three derivative models are developed based on the base model to reflect different operational strategies. A Sequential Heuristic solution method and a PSO-based solution method are proposed to solve this MIP model. Inspired by the proposed Sequential Heuristic method, a learning cycle is applied to study the behavior of optimal solutions, which will help to refine the process sequence for the proposed Sequential Heuristic Method. Numerical results show that the proposed Learning-Based Sequential Heuristic Method processes excellent efficiency in solving this model. And several propositions are provided to evaluate the performance of different QC operation practices for automated container terminals.
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