A Fuzzy Optimization Approach for Designing a Sustainable RL Network in a Strategic Alliance Between OEM and 3PRL

Abstract

Increased competition, higher profits, and drive toward sustainability are motivating third party revere logistics providers (3PRLs) to seek strategic alliances with original equipment manufacturers (OEMs) for recovering maximum value from product returns. With emphasis on combining technological capabilities, enhancing performance levels, developing a fast redistribution system, and addressing common sustainable concerns, a successful partnership can be achieved between the 3PRLs and OEMs. An alliance between the OEM and 3PRL is such that either the OEM outsources all its reverse logistics (RL) activities to the provider or both parties collaborate for jointly planning and executing the RL operations through mutually shared infrastructure and facilities while sharing profits. However, from 3PRL provider’s perspective, a long-term view is needed to anticipate the economic viability of a collaborative system before entering into a logistics relationship with the manufacturers. As our contribution to the existing literature, we propose a fuzzy integer nonlinear programming model which can be used as a decision tool by 3PRLs for making this key decision of enhancing sustainability of the product recovery design. The proposed model is designed with the main objective of maximizing the profit generated by the multi-echelon RL network while analyzing the nature of the alliance to be formed between the OEMs and 3PRLs for each product to be recovered. The model also determines which clients (manufacturers) and how many clients to be acquired for maximum profitability. The core focus of the research is to exploit the maximum recoverable potential of the product returns and achieve a socially and environmentally sound and yet profitable RL system. The proposed model is validated by considering case study of a 3PRL offering product recovery services such as collection, repair, refurbishing, dismantling, and redistribution to manufacturers of electronic equipments.