Guanglei Jiao
ABSTRACT
Based on the analysis of the ship block painting scheduling problem (SBPSP), this paper proposes a multi-objective low-carbon ship block painting scheduling problem that considers the electrical energy consumed by VOCs equipment and the carbon emissions caused by LNG gas. The objective function of this study is to minimize the maximum makespan, uneven workload, and carbon emission. Considering the constraints of human resources, a multi-day planning and scheduling model including sand-washing and spraying tasks is established. Since the problem is a non-deterministic polynomial time hard problem (NP-hard), an improved artificial bee colony algorithm (IABC) is proposed to efficiently obtain a near-optimal solution in a reasonable time. Based on the model, a three-dimensional encoding solution method is designed, and a special solution combination method and crossover operators are designed according to the characteristics of the problem. The greedy randomized adaptive search procedures (GRASP) and the variable neighborhood search (VNS) algorithm are mixed in the IABC algorithm to increase search efficiency. Finally, this paper conducts numerical experiment analysis on the improved algorithm and the results of NSGA-II, SS, and ABC algorithms. Through three evaluation metrics, it is proved that the algorithm can be better applied to the scheduling problem of ship block scheduling problem.
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