Reasonably arranging the order production dates and satisfying the order requirements of subsequent processes can ensure the continuity of order production and reduce the waste of resources caused by downtime and production restrictions.Aiming at the order scheduling problem within a planning cycle,a multi-objective optimization model was established,an improved differential evolu-tion algorithm(three mutation strategies-multi-objective differential evolution,TMS-MODE)was de-signed,and an adaptive mutation strategy for different individuals was adopted to balance the search depth and breadth of the algorithm.The proposed algorithm was validated through practical cases,and it shows significant performance advantages over common NSGA-Ⅱ and the basic MODE algorithm in terms of diversity,convergence,and uniformity in medium to large-scale scenarios.
hot rollingorder planbalance between supply and demandmultiple objective differenti-al evolution
NETL
NSTL
万方数据
维普
