Multi-objective bacterial colony optimization algorithm for integrated container terminal scheduling problem

This paper proposes a multi-objective integrated container terminal scheduling problem considering three key components: berth allocation, quay cranes assignment and containers transportation in port operation process. In the suggested problem, one of the objectives is to shorten service time of ships with by coordinating of quay cranes, and the other is to reduce operating costs of quay cranes and yard trucks. Then, a Multi-objective Bacterial Colony Optimization algorithm (MOBCO) incorporating concepts of multi-swarm, topology, personal best and global best, named Multi-objective BCO with ring topology (MORBCO), is designed to handle the resulting problem. The extension of standard MOBCO to the MORBCO involves the addition of three specialized strategies: global chemotaxis operation, elite reproduction strategy and personal best archive with neighborhood communication mechanism. In order to test the performance of the MORBCO, benchmark tests are performed and compared with traditional MOBCO and three other well-known multi-objective algorithms first. The computational results indicate that the proposed algorithm can outperform other rivals and efficiently solve a variety of multi-objective problems in most of cases. Subsequently, MORBCO and two best performing algorithms from the previous test are applied to three instances generated by the proposed model. Judging by quality and diversity of obtained non-dominant solutions, we find that MORBCO has superior performance, especially for large instances of the container terminal problem.