Discrete multi-objective artificial bee colony algorithm for green co-scheduling problem of ship lift and ship lock

Abstract

This paper investigates a multi-objective green co-scheduling problem of ship lift and ship lock (GCP-SL&SL) at the Three Gorges Cascade Hub (TGCH). A mathematical model of GCP-SL&SL with objectives of the average utilizations rate of the lock chamber, average waiting time and total energy consumption of vessels, is proposed by separating it into three sub-problems: the facility assignment, lockage assignment and lockage operation scheduling. To solve this problem, a discrete multi-objective artificial bee colony (DMOABC) algorithm is developed. Within the DMOABC, a two-dimensional matrix encoding scheme is designed to encode and a group right-shift decoding scheme is specifically proposed to decode each food source. Then, a novel fitness evaluation mechanism based on fuzzy relative entropy is introduced to hand this multi-objective problem. Next, the food sources are improved from three aspects: (1) the employed bee phase uses new evolutionary operators for fast local search; (2) the onlooker bee phase adopts a modified tabu search for strong global search; (3) the scout bee phase embeds chemical reaction optimization for disturbing population. Finally, extensive experiments are conducted with the real data from historical traffic at TGCH. The results demonstrate our proposed algorithm is significantly better at solving the GCP-SL&SL than other five well-known multi-objective algorithms. The effect analysis under different scenarios indicates that the average waiting time of vessels at the dam is greatly reduced because of considering the synchronous moving process.