A Subpopulation-Based Differential Evolution Algorithm For Scheduling With Batching Decisions In Steelmaking-Continuous Casting Production

This paper studies a scheduling problem with batching decisions in steelmaking-continuous production. The problem is to minimize the makespan by selecting machines for a set of charges and given the charges scheduling as well as batching decisions. We formulate the problem as a MILP model by considering the practical technological requirements and the rules of batching. To solve the problem, we propose a Subpopulation-based Differential Evolution (SPDE) algorithm with a real-coded representation for fitness evaluation, a classification scheme for a trade-off between exploration and exploitation and a new perturbation-based neighborhood search. Computational results on random instances show that the proposed algorithm can obtain better solutions than other DE variants tested. In addition, the proposed algorithm competes well with IBM ILOG CPLEX optimizer in solving the problem.