4.7 Article

Integrated optimization of container allocation and yard cranes dispatched under delayed transshipment

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2023.104429

关键词

Container terminal; Delayed transshipment; Multi-period liner shipping; Yard resources dispatching; Benders decomposition algorithm

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This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
Due to variations in carrying capacity and visiting periods of vessels calling at terminals, certain transshipped containers may not be able to be transported immediately after arrival. Instead, they must be temporarily stored in the yard and scheduled for later transportation. Increased container storage time in the yard as a consequence of transit delays not only incurs additional costs for shipping companies, but also introduces new issues for terminal yard management. Therefore, this study investigates the daily storage yard management challenges that arise in marine container terminals that integrate space allocation and yard crane deployment decisions while considering the delayed transshipment of containers. A mixed-integer linear programming model is proposed to describe the problem, whose objectives are to minimize the transportation costs for container loading and discharge operations, penalty costs associated with the delayed transshipment of containers, transportation costs associated with containers not transshipped within the planning horizon, and yard crane inter-block movement costs. The Benders decomposition algorithm is applied to address this problem, and the traditional decomposition approach is improved by adding characteristics such as the development of strong optimality cuts and the generation of a powerful initial solution to the master problem. Extensive experiments are performed to validate the effectiveness of the model and efficiency of the proposed improved Benders decomposition algorithm.

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