Variable neighborhood search methods for the dynamic minimum cost hybrid berth allocation problem

Abstract

This study considers the Dynamic Minimum Cost Hybrid Berth Allocation Problem (DMCHBAP) with fixed handling times of vessels. The objective function to be minimized consists of three components: the costs of positioning, waiting, and tardiness of completion for all vessels. Having in mind that the speed of finding high-quality solutions is of crucial importance for designing an efficient and reliable decision support system in container terminal, metaheuristic methods represent the natural choice to deal with DMCHBAP. Four variants of Variable Neighborhood Search (VNS) metaheuristic are designed for DMCHBAP. All four proposed VNS methods are evaluated on four classes of randomly generated instances with respect to solution quality and running times. The conducted computational analysis indicates that all four VNS-based methods represent promising solution approaches to DMCHBAP and similar problems in maritime transportation.