Multiobjective hybrid genetic algorithm for quay crane scheduling in berth allocation planning

Chengji Liang, Lin Lin and Jungbok Jo

International Journal of Manufacturing Technology and Management, 2009, vol. 16, issue 1/2, 127-146

Abstract: With the development of the global business and logistics under the internet environment a Container Terminal (CT) system becomes more and more busy. Therefore, the available resources in the seaport get scarcer than before. In order to increase the operating efficiency of CT system, the resources planning problem has become a critical issue in the fields of operations research and logistics. In this paper, we introduce the Berth Allocation Planning (BAP) problem and formulate a multiobjective mathematical model considering each berth for container ship with different number of Quay Cranes (QCs) and balance of QC's workload. In order to solve this QC scheduling in BAP problem, we propose a multiobjective hybrid Genetic Algorithm (mohGA) approach with a priority-based encoding method. To demonstrate the effectiveness of proposed mohGA approach, numerical experiment is carried out and the best solution to the problem is obtained.

Keywords: port management; container terminals; berth allocation planning; quay cranes; workload balance; multiobjective mathematical modelling; multiobjective hybrid GAs; genetic algorithms; quay crane scheduling. (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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