Multi-level inventory matching and order planning under the hybrid Make-To-Order/Make-To-Stock production environment for steel plants via Particle Swarm Optimization

• A production planning problem based on MTO–MTS policy for steel plant is presented.
• A model which co-optimizes multi-inventory matching and order planning is proposed.
• An improved PSO algorithm with local search and repair strategy is proposed.

This paper proposes a nonlinear integer programming model which co-optimizes the multi-level inventory matching and order planning for steel plants while combining Make-To-Order and Make-To-Stock policies. The model considers order planning and inventory matching of both finished and unfinished products. It combines multiple objectives, i.e., cost of earliness/tardiness penalty, tardiness penalty within delivery time window, production cost, inventory matching cost, and order cancelation penalty. This paper also proposes an improved Particle Swarm Optimization (PSO) method, where strategies to repair infeasible solutions and inventory-rematching scheme are introduced. Parameters of PSO and the rematching scheme are also analyzed. Three sets of real data from a steel manufacturing company are used to perform computational experiments for PSO, local search, and improved PSO. Numerical results show the validity of the model and efficacy of the improved PSO method.