دانلود رایگان مقاله انگلیسی طراحی شبکه لجستیک معکوس برای یخچال های چند دوره ای - الزویر 2018

Abstract

This paper focuses on the design of a multi-stage reverse logistics network for product recovery. Different recovery options such as product remanufacturing, component repairing and material recycling are simultaneously considered. Initially, we propose a mixed integer linear programming model – with a profit maximization objective – for the network design problem. The structure of the product, by way of bill of materials (BOM), is also incorporated into the proposed model in order to analyze the flow at component and material levels. Sensitivity analysis is carried out to study the effects of variations in the values of the input parameters such as product return quantity, unit transportation cost per unit distance, and unit processing cost. The analysis shows that the design decisions of different facilities considerably change even for 5 to 20% variations in input parameter values. This led to the development of a refined mathematical model which incorporates variations in the different input parameter values over time. The new model provides a unified design for the entire planning horizon and has been validated with the design of a used refrigerator recovery network.

7. Conclusions

Enterprises across the globe are spending a lot of time, effort and money to set up their reverse supply chains. A reverse supply chain is made up of a series of activities that are required to retrieve used products from customers, either for disposal or reuse. Reverse supply chains are setup either because of environmental considerations or customer pressures or economic incentives. The main contribution of our study is the development of a generalized mathematical model for the design of a reverse supply chain that can (a) accommodate variations in input parameters over time, and (b) accommodate multiple recovery options simultaneously.

Our model will assist with decisions on the location of reverse logistics facilities while, simultaneously, maximizing profits. Since our model explicitly considers the product BOMs, our expectation is that decision makers will be able to take advantage of component commonalities among different products and analyze the flow at component and material levels between different pairs of entities in the network. This in turn, should enable the decision maker to decide on the usage of appropriate mode of transportation between different facilities of the network. By way of a detailed sensitivity analysis, this work also provides insights into the effect of input parameters on the profit function.

By validating the model with the network design for used refrigerators, we establish its practical relevance. From the results, it is clear that our model is robust enough to accommodate variations in inputs up to a limit of ± 15% in the cost structure and ± 20% in the product return quantity.