A Robust Model for Aggregate Production Planning: Solving with Particle Swarm Optimization

Aggregate production planning (APP) is concerned with determining the quantity of production, inventory and work force levels for the intermediate future to satisfy fluctuating demand over a planning horizon. In this paper, we consider multi-period, multi-product and multi-machine systems with setup decisions in which some parameters such as production cost and customer demand are uncertain. We proposed a mixed integer linear programming (MILP) model to formulate robust aggregate production planning to minimize total costs. Due to NP-hard class of APP, a particle swarm optimization (PSO) is implemented to solve this problem and the result obtained are compared to those of the LINGO8 software in small-sized problem. Results suggest that the PSO algorithm have goodability to solve the problem.