Abstract
This paper proposes a hybrid goal programming-data envelopment analysis (GP-DEA) model in a network structure to present improvement solutions and rank units of a supply chain. The improvement solutions are presented for all efficient and inefficient units based on experts’ requirements. Therefore, the goals are considered as fuzzy values. To deal with uncertainty, a suitable fuzzy possibilistic approach is employed. Given robust optimization approach, the units of the supply chain are ranked based on penalties of deviations from goals as feasibility robustness and also the average and standard deviation of deviations as optimality robustness. One advantage of the proposed model is that it can determine balancing values and improvement solutions for flows among the units of a supply chain which have dual-roles factors so that the deviations from their goals are minimized. The proposed robust network GP-DEA model is run in a case study. The outcome of this paper can be used to evaluate and rank all types of supply chains with different network structures.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.