An Improved Equilibrium Optimizer for Solving Multi-quay Berth Allocation Problem

Abstract

AbstractThe multi-quay berth allocation problem (MQBAP) is an important problem in the planning of seaside operations (POSO) to find the best berthing solution for all the vessels. In this paper, an efficient method based on equilibrium optimizer (EO) is proposed for MQBAP. The dynamic multi-swarm strategy (DMS) is proposed to improve rapid decline problem in population diversity during the iterative process of EO, which is subsequently applied to MQBAP. In this paper, a certain improvement is also made on the original model of MQBAP by proposing an alternate quay selection mechanism, which aims to make the MQBAP model more complete. To verify the effectiveness of the proposed algorithm on MQBAP, this paper uses six test cases and seven comparative algorithms to verify it comprehensively from total service cost, berthing time, and berthing location. The results show that DEO achieved the smallest total service costs of 7584 and 19,889 on medium-scale, and 44,998, 38,899, and 57,626 on large-scale systems.