Network Design for Allied Supply Chains under Uncertain Conditions: A Possibilistic Programming Approach

Abstract

The complex relationships between firms in today’s competitive business world affect supply chain (SC) structures so that managers have to consider SC versus SC relations instead of firm versus firm ones. In the corporate or multi-business companies, it is possible to share a number of resources between different SCs to achieve synergy and reduce costs. This paper addresses the strategic–tactical SC planning decisions (i.e., SC network design and master planning) in an uncertain environment for allied SCs belong to a single corporate. First, a fuzzy mixed-integer mathematical programming model that considers the imprecise nature of critical parameters such as cost coefficients, capacity levels, market demands is developed for integrated design of two SCs. Then, a robust possibilistic programming model is proposed to cope with the inherent uncertainty in the model parameters. The proposed model is able to achieve significant cost synergies via integrating the design of corporate SCs. Using hypothetical data inspired by an industrial case, the performance and applicability of the proposed models are investigated via experimental evaluations. Computational results indicate that our proposed model and solution approach can effectively be used to solve the allied SCs under uncertain condition.