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. number of time periods (t =1,…, T) number of products (i =1,…, I) number of production sites (j =1,…, J) number of suppliers (s=1,…, S) number of worker levels (k =1,…, K) number of consumers (c =1,…, C) number of raw materials (m =1,…, M) regular time production cost per unit at site j in period t overtime production cost per unit at site j in period t subcontracting production cost per unit at site j in period t cost of raw material m provided by supplier s in period t shipping costs from the supplier s to site j in time t average failure rate of raw material m supplied by supplier s to site j in period t acceptable failure rate of site j for incoming shipments of raw material m average service level of supplier s site j acceptable service level labor cost of the k-levels (k =1,…, K) worker at site j in period t firing cost of the k-levels worker at site j in period t hiring cost of the k-levels worker at site j in period t training cost for the k-levels worker trained to level k′at site j in period t inventory holding cost of product i at site j in period t transportation cost from site j to consumer c in period t inventory holding cost of raw material m at site j in period t cost of penalties associated with shortage of product i for consumer c in period t sale price of product i for consumer c in period t demand of production i from consumer c in period t maximum amount of subcontracting for product i at site j in period t machine hour used for produce product i at site j in period t maximum machine capacity available for product i at site j in period t warehouse space per unit for ith product at site j in period t warehouse space per unit for the mth raw material at site j in period t maximum warehouse space available at site j in period t number of units of raw material m required for each unit of product i lead time required for shipping raw material from supplier s to site j available regular time at site j in period t available over time at site j in period t available subcontracting time at site j in period t production time of product i at site j number of the k-level initial labor considered for primary planned period at site j fraction of the workforce variation allowed in period t lead time required for shipping raw material from site j to consumer c raw material storage capacity at site j final production storage capacity at site j productivity of k-level workers (0≤ ν k ≤1) maximum number of raw material m supplier s could provide in period t 1 if training from skill level k to skill level k′ is possible; 0, otherwise total score of supplier s considering qualitative performance factors escalating factor for the regular production cost escalating factor for the overtime production cost escalating factor for subcontracting production cost escalating factor for the raw material cost escalating factor for the labor salary cost escalating factor for the labor firing cost escalating factor for the labor hiring cost escalating factor for the labor training cost escalating factor for the raw material inventory cost escalating factor for the production inventory cost escalating factor for suppliers to the site shipping cost escalating factor for sites to the consumer transportation cost escalating factor for the product shortage cost quantity of production in regular time for product i produced at site j in period t quantity of production in overtime for product i produced at site j in period t subcontracting quantity for product i produced at site j g in period t quantity of units of raw material m shipped from supplier s to site j in period t quantity of k-level workers at site j in period t quantity of k-level workers at site j fired in period t quantity of k-level workers at site j hired in period t quantity of k-level workers at site j trained to level k′ in period t inventory level of final product i at site j in period t number of units of final product i provided by site j for consumer c in period t inventory level of raw material m at site j at the end of period t shortage of product i in demand point c in period t 
Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty