Multi-objective optimization of sustainable supply chain under carbon policies

Abstract

As the effects of global climate change increase, both academics and policymakers are assessing the impacts of carbon reduction strategies on industrial systems. Businesses now face the challenge of designing supply chain networks that are both economically efficient and environmentally sustainable. This study examines the impacts of carbon policies on sustainable supply chain networks by developing a multi-objective optimization model. The study analyses how three main carbon policy instruments, namely carbon cap, carbon taxes and carbon cap-and-trade, affect total costs and carbon emissions in a multi-stage supply chain by using mathematical modeling. The Augmented Epsilon Contraint method is used to generate Pareto optimum solutions that result in trade-offs between environmental impact and total cost. These Pareto optimal solutions are ranked using the TOPSIS method, presenting strategic alternatives for decision-makers. The results clearly show that carbon regulatory tools are necessary for designing the supply chain with climate awareness.