A HPSO for solving dynamic and discrete berth allocation problem and dynamic quay crane assignment problem simultaneously

作者：Hsu Hsien Pin^*

来源：Swarm and Evolutionary Computation, 2016, 27: 156-168.

DOI：10.1016/j.swevo.2015.11.002

• Berth allocation problem (BAP)
• Quay crane assignment problem (QCAP)
• Particle swarm optimization (PSO)
• Genetic algorithm (GA)

Berth allocation problem (BAP) and quay crane assignment problem (QCAP) are two essential seaside operations planning problems faced by operational planners of a container terminal. The two planning problems have been often solved by genetic algorithms (GAs) separately or simultaneously. However, almost all these GAs can only support time-invariant QC assignment in which the number of QCs assigned to a ship is unchanged. In this study a hybrid particle swarm optimization (HPSO), combining an improved PSO with an event-based heuristic, is proposed to deal with two specific seaside operations planning problems, the dynamic and discrete BAP (DDBAP) and the dynamic QCAP (DQCAP). In the HPSO, the improved PSO first generates a DDBAP solution and a DQCAP solution with time-invariant QC assignment. Then, the event-based heuristic transforms the DQCAP solution into one with variable-in time QC assignment in which the number of QCs assigned to a ship can be further changed. To investigate its effeteness, the HPSO has been compared to a GA (namely GA1) with time-invariant QC assignment and a hybrid GA (HGA) with variable-in-time QC assignment. Experimental results show that the HPSO outperforms the HGA and GA1 in terms of fitness value (FV).

• 出版日期2016-4