Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty

Presenting a fuzzy multi-objective multi-period mixed-integer non-linear aggregate production planning model.Considering various sources of uncertainty in a multi-product multi-site multi-customer supply chain.Developing a fuzzy programming method to solve the presented model.Considering a real-world case study and using some comparing measures. The main focus of this paper is to develop a model considering some significant aspects of real-world supply chain production planning approved by industries. To do so, we consider a supply chain (SC) model, which contains multiple suppliers, multiple manufactures and multiple customers. This model is formulated as a fuzzy multi objective mixed-integer nonlinear programming (FMOMINLP) to address a comprehensive multi-site, multi-period and multi-product aggregate production planning (APP) problem under uncertainty. Four conflicting objectives are considered in the presented model simultaneously, which are (i) to minimize the total cost of the SC (production costs, workforce wage, hiring/firing and training costs, transportation cost, inventory holding cost, raw material purchasing cost, and shortage cost), (ii) to improve customer satisfaction, (iii) to minimize the fluctuations in the rate of changes of workforce, and (iv) to maximize the total value of purchasing in order to consider the impact of qualitative performance criteria. This model is converted to multi-objective mixed-integer linear programming (MOMILP) through three steps of the developed method and then the MOMILP model is solved by two different methods. Additionally, comparison of these two methods is presented and the results are analyzed. Finally, the efficiency of the model is investigated by a real industry SC case study.