Authors: Kovač, Nataša
Davidović, Tatjana 
Stanimirović, Zorica
Affiliations: Computer Science 
Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Population-based Metaheuristics for the Dynamic Minimum Cost Hybrid Berth Allocation Problem
Journal: International Journal on Artificial Intelligence Tools
Volume: 30
Issue: 4
First page: 2150017
Issue Date: 1-Jun-2021
Rank: ~M23
ISSN: 0218-2130
DOI: 10.1142/S0218213021500172
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: costs of positioning, waiting, and tardiness of completion for all vessels. A mathematical formulation of DMCHBAP, based on Mixed Integer Linear Programming (MILP), is proposed and used within the framework of commercial CPLEX 12.3 solver. As the speed of finding high-quality solutions is of crucial importance for an efficient and reliable decision support system in container terminal, two population-based metaheuristic approaches to DMCHBAP are proposed: combined Genetic Algorithm (cGA) and improvement-based Bee Colony Optimization (BCOi). Both cGA and BCOi are evaluated and compared against each other and against state-of-the-art solution methods for DMCHBAP on five sets of problem instances. The conducted computational experiments and statistical analysis indicate that population-based metaheuristic methods represent promising approaches for DMCHBAP and similar problems in maritime transportation.
Keywords: bee colony optimization | Container terminal | genetic algorithm | penalties | scheduling vessels
Publisher: World Scientific

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