Hybrid Flow Shop Scheduling Problem Based on Evolutionary Multi-objective Algorithm

A new evolutionary algorithm for solving multi-objective hybrid flow shop scheduling problem(HFSP) which is an important topic in supply chain network optimization is presented.The general model for the HFSP is proposed,and a matrix gene encoding method and a sort of fitness assignment strategy which can approach the optimum solutions with dynamic weighting are discussed.The algorithm process is presented by using elitist strategy.The convergent performance of the algorithm is analyzed by computing the progress measurement.The performance analysis and the experimental results show that the algorithm is effective for high-dimensional multi-objective problems and can converge to satisfactory solutions at a high speed.