Multi-criteria optimization for a cost-effective design of an RFID-based meat supply chain

Purpose - In this paper, the authors investigated a proposed radio-frequency identification (RFID)-based meat supply chain to monitor quality and safety of meat products we purchase from supermarkets. The supply chain consists of farms, abattoirs and retailers. The purpose of this paper is to determine a cost-effective trade-off decision obtained from a developed multi-criteria optimization model based on three objectives. These objectives include customer satisfaction in percentage of product quantity as requested by customers, product quality in numbers of meat products and the total implementation cost. Furthermore, this work was aimed at determining the number and locations of farms and abattoirs that should be established and quantities of products that need to be transported between entities of the proposed supply chain.

Design/methodology/approach - To this aim, a tri-criteria optimization model was developed. The considered criteria were used for minimizing the total implementation cost and maximizing customer satisfaction and product quality. In order to obtain Pareto solutions based on the developed model, four solution approaches were employed. Subsequently, a new decision-making algorithm was developed to select the superior solution approach in terms of values of the three criteria.

Findings - A case study was applied to examine the applicability of the developed model and the performance of the proposed solution approaches. The computational results proved the applicability of the developed model in obtaining a trade-off among the considered criteria and solving the RFID-based meat supply chain design problem.

Practical implications - The developed tri-criteria optimization model can be used by decision makers as an aid to design and optimize food supply chains. 

Originality/value - This paper presents a development of first, a cost-effective optimization approach for a proposed RFID-based meat supply chain seeking a trade-off among three conflicting criteria; and second, a new decision-making algorithm which can be used for any multi-criteria problem to select the best Pareto solution.