摘要
Due to the increase in environmental awareness and stringent government regulations, companies are paying closer attention to producing consumer goods with low carbon emissions. In many cases, the production operations of these products are outsourced to independently owned manufacturers in the corresponding supply chains. This paper proposes a new decision framework to use in a decentralized decision making environment that evaluates the tradeoffs between the total costs and the carbon emission occurred during the extraction of the material, the production operations and assembly, and the required transportation. Under the proposed framework, the product designer decides the preliminary design options and amount of carbon rebate, and the manufacturer optimizes its supply chain decisions according to the design and amount of carbon rebate. The supply chain optimization problem is formulated and solved by dynamic programming. The problem is complex for three reasons. First, the problem has dual objectives: cost and carbon emission. Second, there are several options to reduce carbon emission. Third, the product design requirement imposes constraints on the feasibility and efficiency of these options. We develop graphical tools to help product designers identify the set of Pareto-efficient options and illustrate the tradeoffs. A real-world table lamp manufacturing case illustrates how to use the proposed framework including the sequence of decisions, the information required, and the interpretations of the graphical tools.