Scheduling a Continues Galvanization Line using Genetic Algorithm

This work deals with a scheduling system for a continuous galvanization line, an important and complex problem for logistic optimization in steel plants. The problem tackled in this work involves several constraints and characteristics inspired by reallife manufacturing plants and literature. Given the complexity of the problem, which belongs to the class of NP-hard problems, a GA methodology was developed. The solution is based on combining a penalty procedure defined for constraints, and assigning various weights for different characteristics of coils. Considering the ability and flexibility of GAs, a set of parameters are analyzed to achieve practical and best results. Our approach achieved satisfying continuous galvanization line sequences with minimum number of coil transitions which improve productivity and reduce costs.