A Decision Model for Berth Allocation Under Uncertainty Considering Service Level Using an Adaptive Differential Evolution Algorithm

Changchun Liu, Xi Xiang, Canrong Zhang () and Li Zheng ()
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Changchun Liu: Department of Industrial Engineering, Tsinghua University, Beijing 100084, P. R. China2Logistics Engineering and Simulation Laboratory, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, P. R. China
Xi Xiang: Department of Industrial Engineering, Tsinghua University, Beijing 100084, P. R. China2Logistics Engineering and Simulation Laboratory, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, P. R. China
Canrong Zhang: Logistics Engineering and Simulation Laboratory, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, P. R. China
Li Zheng: Department of Industrial Engineering, Tsinghua University, Beijing 100084, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2016, vol. 33, issue 06, 1-28

Abstract: This paper focuses on the berth allocation problem, which is to determine where and when the vessels to be loaded and unloaded at a terminal within a given planning horizon, with consideration of uncertain factors, mainly including the arrival and operation time of the calling vessels. Based on the concept of service level which is commonly used in the inventory system, a decision model is constructed to minimize the cost of baseline schedule, which includes delay cost and nonoptimal berthing location cost. According to the specific characteristics of the model, the upper and lower bounds are found. And due to the NP-hardness of the constructed model, an adaptive differential evolution is employed to solve the problem. Finally, extensive numerical experiments are conducted to test the performance of the proposed models and solution approaches.

Keywords: Container terminals; berth allocation; uncertainty; service level; adaptive differential evolution (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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DOI: 10.1142/S0217595916500494

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