An Efficient Optimization Algorithm for Resource-Constrained Steelmaking Scheduling Problems

Abstract

In this paper, we address the steelmaking scheduling problems with multiple constrained resources. The objective is to minimize the maximum completion time. We consider the continuous casting constraint and resource constraints simultaneously. Based on the artificial bee colony (ABC) algorithm, we propose several heuristics and develop a discrete ABC (DABC) algorithm for the considered problem. In the proposed algorithm, a two-phase-based encoding mechanism is presented to create different searching abilities during different stages of evolution. Next, a decoding method considering the resource constraints is designed. A local search procedure is developed to utilize the two-phase encoding mechanism efficiently. Then, a global search heuristic is investigated to enhance the ability to escape from the local best. Finally, we test the proposed DABC algorithm by running it on sets of instances that are randomly generated based on realistic steelmaking production system. After detailed comparisons and statistical analysis, the competitive performance of the proposed DABC algorithm is verified.

Keywords

• Multi-objective optimization
• resource-constrained
• hybrid flow shop scheduling steelmaking casting problem