Optimising steel production schedules via a hierarchical genetic algorithm

Abstract

This paper presents an effective scheduling in a steel-making continuous casting (SCC) plant. The main contribution of this paper is the formulation of a new optimisation model that more closely represents real-world situations, and a hierarchical genetic algorithm (HGA) tailored particularly for searching for an optimal SCC schedule. The optimisation model is developed by integrating two main planning phases of traditional scheduling: (1) planning cast sequence, and (2) scheduling of steel-making and timing of all jobs. A novel procedure is given for genetic algorithm (GA) chromosome coding that maps Gantt chart and hierarchical chromosomes. The performance of the proposed methodology is illustrated and compared with a two-phase traditional scheduling and a standard GA toolbox. Both qualitative and quantitative performance measures are investigated.