Revised multi-choice goal programming for incorporated dynamic virtual cellular manufacturing into supply chain management: A case study

In this paper, a bi-objective optimization model is proposed for a dynamic virtual cellular manufacturing system and supply chain design. The presented model considers important manufacturing features thoroughly such as multi-plants and facility locations, multi-markets allocations, multi-period production planning under uncertain demand of products and capacities of resources. The proposed model is converted into an equivalent auxiliary crisp model. Then, to solve the model, a revised multi-choice goal programming approach is applied for finding a favorite solution. The aims of the proposed model are to minimize the total cost of supply chain design which includes holding cost, outsourcing cost, maintenance and overhead cost of machines, fixed cost, external transportation cost and minimizing the total number of exceptional elements and movements of the labors between active plants. The Computational results are explained in terms of a real case study as well as the validity of the proposed model solution method.