Multi-objective Optimization Model and Algorithm for Hot Rolling Lot Planning

Abstract

A multi-objective combinatorial optimization model is formulated for hot rolling lot planning problem in the production scheduling of iron and steel enterprises and a new modified multi-objective genetic local search algorithm is designed to solve the model. The model can solve the problem more precisely than previous methods. The algorithm can provide the schedulers with more than one solution in order to help schedulers make further decisions. Simulation experiment using production data shows that the model and algorithm are effective