Solving the berth allocation problem with service priority via multi-objective optimization

This paper studies a multi-objective instance of the berth allocation problem (BAP). The BAP involves the determination of exact berthing times and positions of incoming ships in a container port so as to minimize concurrently the three objectives of makespan of the port, total waiting time of the ships, and degree of deviation from a predetermined service priority schedule. These objectives represent the interests of both port and ship operators. Unlike most existing approaches in the literature which are single-objective-based, a multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The multi-objective approach reveals several interesting characteristics of the BAP.