Multi-objective Aggregate Production Planning for Multiple Products: A Local Search-Based Genetic Algorithm Optimization Approach

Abstract The diversity of products and fierce competition make the stability production cost manufacturing industry more important. So, purpose this paper is to deal with multi-product aggregate planning (APP) problem considering in workforce total costs, propose an efficient algorithm. Taking into account relationship raw materials, inventory product demand, a multi-objective programming model for APP established minimize costs instability work force. To improve efficiency algorithm, feasible region planned number workers each period are determined local search algorithm used ability. Based on analysis range, genetic designed solve combined For analyzing effect information entropy strategy, NSGA-II strategy multi-population compared analyzed examples, simulation results show that feasible, based has better performance problem.