Order-planning model and algorithm for manufacturing steel sheets

Abstract A multi-objective order-planning model is formulated for manufacturing steel sheets. The objectives include minimizing tardiness cost, balancing utility of capacities and minimizing inventory cost. The weighted-sum approach is used for transferring the multiple objectives into single one, as well as a penalty function is used for incorporating constraints into the objective function. Specific particle swarm optimization (PSO) algorithm is designed to solve the model. Taking three practical order-planning problems as instances, different sets of parameter combinations are systemically designed to test effectiveness and efficiency of the algorithm in experiments; computation results show that the model and algorithm are superior to human–machine coordination method.