Aggregate production planning with multiple fuzzy goals

This work presents a novel interactive multiple fuzzy objective linear programming (MFOLP) model for solving the aggregate production planning (APP) decision problem in a fuzzy environment. The proposed model minimizes total production costs, carrying and backordering costs, and costs of changes in labor levels, while considering inventory levels, labor levels, machine capacity, warehouse space, and the time value of money. An industrial case demonstrates the feasibility of applying the proposed model to the APP problem. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple fuzzy goal values. Furthermore, the proposed model provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the fuzzy data and related model parameters until a satisfactory solution is obtained. Several significant characteristics that differentiate the proposed model from other APP models are presented.