A hybrid particle swarm optimization and tabu search algorithm for order planning problems of steel factories based on the Make-To-Stock and Make-To-Order management architecture

Abstract

This paper presents the production planning management architecture for iron-steel manufacturing factories based on Make-To-Order (MTO) and Make-To-Stock (MTS) management ideas. Within this architecture, we discuss the procedures of order planning in details and construct a nonlinear integer programming model for the order planning problem. This model takes into account inventory matching and production planning simultaneously, and considers multiple objectives, such as the total cost of earliness/tardiness penalty, tardiness penalty in delivery time window, production, inventory matching and order cancelation penalty. In order to solve this nonlinear integer program, this paper designs a hybrid Particle Swarm Optimization (PSO) and Tabu Search (TS) algorithm, in which new heuristic rules to repair infeasible solutions are proposed, and then analyzes the parameter settings for PSO and the combined algorithm by simulations. This paper also compares the results of using PSO individually, TS individually, and the hybrid PSO/TS algorithm to solve the models with three different order quantities. Numerical results show that the hybrid PSO/TS algorithm provides better solutions while being computationally efficient.