Optimization for multi-resource integrated scheduling in the automated container terminal with a parallel layout considering energy-saving

Kexin Tang, Yu Zhang, Caiyun Yang, Lijun He, Chuanjie Zhang, Wenfeng Zhou

Abstract: The integrated scheduling of multi-equipment in automated container terminals (ACT) is a focus of attention in port industry. With the application of parallel layout in ACT, the high coupling between equipment has become more prominent, which poses a huge challenge for achieving collaborative management. This study addresses a multi-resource problem in the ACT with a parallel layout, optimizing the task assignment and operations sequencing of various equipment with the goal of energy-saving. First, we analyze the coupling behaviors of multi-equipment and define the critical time relationships by adopting a node relationship diagram. Based on this, a multi-resource integrated scheduling model that considers the practical constraints faced by cranes is developed. To solve this complex scheduling problem, a co-learning imperial competition algorithm (CLICA) is designed. In the algorithm, the time-varying and compensation strategies are introduced to enhance the optimization capability. We employ a multi-dimensional hybrid coding scheme to express each solution, where a pre-allocation method is inserted. Experimental results demonstrate that the CLICA excels in solution quality and convergence speed, with a maximum reduction of 23.4 kW⋅h in the large-case L12. The average gap between CLICA and the theoretical lower bound is only 4.18 % in large-scale cases. In addition, compared with the scheduling method in perpendicular layout, the energy consumption of equipment in parallel layout can be saved by about 41 %. Based on the research background and experimental analysis, it provides managerial insights to support comprehensive decision-making for terminal operators.