Immune Cross Entropy Algorithm for Robust Berth Allocation and Quay Crane Assignment Problem

Abstract

Considering different kinds of uncertainties such as late arrival of ships and extended handling time in the actual operation of container terminal, a robust berth allocation and quay crane assignment problem (BACAP) model which aims at minimizing the total stay time of all vessels is proposed. The buffer time between vessels based on weighted slack time can effectively absorb the impact of uncertainty on initial scheduling. Then an immune cross entropy algorithm (ICEA) is proposed to solve the problem. Based on the construction of discrete probability matrix, some solutions are generated and elite solutions are selected. Furthermore, according to the characteristics of BACAP, some immune maturation operators are utilized to balance the local search and global optimization ability of the algorithm. Finally, a robust berth allocation and quay crane scheduling plan in uncertain environment is generated. Computational experiment verifies the feasibility of the model and the effectiveness of the proposed algorithm.