Effect of circular economy for waste nullification under a sustainable supply chain management

Abstract

In a production–consumption system, sustainable supply chain management is responsible for controlling excessive waste. In this study, two parallel production and consumption supply chains are proposed for waste nullification. The circular economic concept of 3R (reduce, restore, and recycle) is incorporated in this study. After deterioration, the primary product in the first chain becomes the raw material for the secondary chain production system (second production facility). During the shipment of waste to the recycling industry, loss of waste occurs owing to damage or leakage from the waste containers. The leakage cost (maintenance cost) of the waste container is included in the restoration of waste. The novelty of this study is validated by the optimal values of the price discount and container leakage cost, which emphasize the two factors of a circular economy: reducing and restoring waste in successive steps. The joint cost function (mixed-integer nonlinear programming) of the two-supply chain is optimized using a classical approach. A single-setup-multiple-delivery policy for the shipment of the primary, waste, and secondary products reduces the joint costs. A comparison of the single-setup-multiple-delivery and single-setup-single-delivery policies is presented for cost optimization. A significant numerical result is derived for the validation of this concept: as the leakage cost increases from $5 per container to $10 per container, the supply chain’s overall cost immediately decreases by approximately 90%. However, the problem becomes infeasible beyond this range, which also validates the extreme sensitivity of the restoration of waste for recycling, which optimizes the entire cost of the supply chain. Another significant factor in the primary chain that helps to reduce the generation of waste is the price discount policy. The sensitivity analysis graph indicates that it is also an extremely sensitive parameter for optimizing the entire supply chain.