Supply chain coordination based on mean-variance risk optimisation: pricing, warranty, and full-refund decisions

Abstract

This study focuses on optimising sales of different brands of a single-product supply chain model that consists of several manufacturers and a retailer. The price and quality of the products drive competition between manufacturers who sell a single product through a retailer to the customers. This study aims at maximising the profit values of the retailer and manufacturers, simultaneously. Accordingly, four scenarios are defined with respect to the different contracts, including the cost sharing, profit sharing, revenue sharing, and buyback. Mean-variance risk management is applied to the proposed models. A full-refund return policy and warranty are also considered. A novel hybrid metaheuristic that combines the advantages of the group search optimiser (GSO) and human behaviour-based optimisation (HBBO) algorithms, entitled ‘GSO-HBBO’ algorithm is provided to find the high-quality solutions in fewer numbers of the iterations. The performance of the GSO-HBBO algorithm is compared with the GSO and HBBO algorithms based on different measures such as quality of the generated solutions and CPU-Time. The results show that the presented algorithm generates much better solutions than GSO and HBBO algorithms in a reasonable time. The managerial insights confirmed that the profit-sharing and buyback contracts make the most profit for both manufacturer and retailer.