BUS606: Operations and Supply Chain Management

In this study, two models were constructed to ensure sustainability for the traditional supply chain. The analysis in Section 3.1 shows that the mathematical model in Scenario 2 proposed in this study can ensure better sustainability compared to that of the traditional supply chain status. In particular, Pareto points 1–18 were superior to the traditional supply chain in terms of total cost and total carbon emissions. Clearly, the scenarios analyzed in this study show significant improvement results. The model in Scenario 1 used return vehicles to carry out reverse logistics in an attempt to ensure a greener and more sustainable supply chain. The model in Scenario 2 used return vehicles to reduce the lead time from the manufacturing supplier to the distribution center (warehouse), which led to greater inventory stability at the distribution center (warehouse) and reduced inventory levels.

With the goal of minimizing costs and carbon emissions, the role of return vehicles was explored under two different scenarios. A four-level supply chain model was also established to serve as the basis of the supply chain. A more effective inventory system was proposed to not only reduce costs and ensure a greater inventory stability, but also to make sure that the inventory status was consistent with the indicator lines of Scenario 1. In addition, the recycling and reuse of packaging material as it pertains to reverse logistics was analyzed to determine how to reduce carbon emissions throughout the entire supply chain. Finally, based on the data analysis of the case study, two conclusions are summarized as 1. The Scenario 2 model has a superior inventory status, with an overall reduction rate of 36%, which proves that a higher delivery frequency and the reduction of lead time are able to create an even more efficient inventory status. Therefore, we encourage business executives to refer to the mathematical models proposed in this research paper when they look for options to reduce inventory. They can plug the statistical data into the mathematical models to obtain the Pareto points and the percentage of inventory reduction. In Section 3 of our paper, we discuss the role of two key elements: the environment and the economy. In our scenario models, there are 18 Pareto points that reduce both the cost and carbon emissions, which creates a win-win situation for the company. From these results, it can be concluded that this research provides better alternatives to the traditional supply chain. Business executives will be able to choose from these 18 different options and find the most suitable solution for their companies. 2. Allowing returning vehicles to carry packing material for reverse logistics recycling not only resolves the issue of returning empty vehicles but also resolves the transportation vehicle issue in reverse logistics, which creates yet another win-win situation. In this model, the transportation vehicle is the key component of forwarding logistics in the supply chain when delivering merchandise and in the reverse logistics on its return journey. Thus, vehicles using this model can carry out the function of both forward and reverse logistics, minimizing the possibility of empty vehicle transportation. This transportation model can be utilized to reduce carbon emissions from the recycling of packing materials within the manufacturing process and in vehicle transportation.

This study sought to arrive at an optimal policy regarding carbon emissions and materials recovery objectives. We include additional considerations in the scope of green and sustainable topics to this multi-objective problem. The environmental concerns are a recommended future direction for research.

In addition, while open-loop recycling networks with minimal levels are favored due to their relatively high recycling equipment investment costs, varying the recycling network model to arrive at a more realistic consideration can also be accomplished by altering the number of facilities, their relative distances from each other, and their individual capacities. To arrive at an optimal solution for the extended carbon-capped network with multiple echelons, the JIT NP-hard problem requires a metaheuristic approach, such as a genetic algorithm method.

Furthermore, the analysis on current reverse logistics trends suggests that future research regarding supply chain networks should employ increased levels of complexity to match specific business conditions. Empirical research, such as case studies, interviews, and analyses, could also be used to assess the effectiveness of the reverse logistics strategies used in specific organizations, in addition to proposing alternative models for improvement.