Title: Optimisation of berth and quay crane joint scheduling considering efficiency and energy consumption

Authors: Dusu Wen; Xumao Li; Xiaoyun Ren; Mingjun Ji; Qiuxi Long

Addresses: College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China; CCCC Water Transportation Consultants Co., Ltd., China ' Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China; Laboratory for Traffic & Transport Planning Digitalization, Beijing 100028, China; School of Transportation, Southeast University, Nanjing 210096, China ' Xiangtan University, Xiangtan, Hunan, 411105, China ' College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China ' Australian National University, College of Engineering and Computer Science, Canberra 2601, Australia

Abstract: In order to reduce the energy consumption of ships and quay crane in the port area, the joint scheduling problem of berth and quay crane is studied on the premise that ship arrival information and terminal status information are known. Considering the needs of the shipping company and the interests of the port owner, a multi-objective mixed integer programming model is established to maximise the operational efficiency of ships in the port and minimise the total cost of the terminal, and a local search strategy is designed to solve the quay crane scheduling problem between adjacent ships. At the same time, combining topological structure and iterative coefficient mechanism, an improved particle swarm optimisation algorithm is designed to solve the model, and the Pareto non-inferior solution set is obtained. Finally, the applicability and effectiveness of the proposed model and algorithm are verified by comparison of algorithms with different scales and analysis of multi-scenario results.

Keywords: container terminal; joint scheduling; multi-objective optimisation; particle swarm algorithm; PSO; energy consumption.

DOI: 10.1504/IJSTL.2023.136048

International Journal of Shipping and Transport Logistics, 2023 Vol.17 No.4, pp.487 - 505

Received: 12 Jan 2022
Accepted: 04 Jul 2022
Published online: 15 Jan 2024 *

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