Meng Yu, Xuetao Liu, Xiaojing Ji, Yucong Ren, Wenjing Guo
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Integrated berth allocation and quay crane assignment and scheduling problem under the influence of various factors
As the important resources and equipment of container terminals, berths and quay cranes (QCs) face various challenges in actual operations and their operation efficiency in turn affects the performance of the whole terminal. The authors investigate an integrated berth allocation and QC assignment and scheduling problem under the influence of various factors, including the two main factors of vessel arrival time uncertainty and tide, and the two secondary factors of berth deviation and interference between cranes. To formulate the problem, the authors develop a multi-factor robust scheduling model. A Genetic Algorithm (GA) with Brain Storm Optimisation based on the Contract Net Protocol (CNP) is designed to optimise the berth and QC scheduling scheme. Specifically, the authors use the GA for individual coding and population initialisation, use the brainstorming algorithm for clustering, and introduce the CNP for individual updating. The experimental results show that the designed algorithm can adapt the scheduling plan to complex environments and can improve the service level of terminals.
期刊介绍:
IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly.
The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).