A general reverse logistics network design model for product reuse and recycling with environmental considerations
Reverse logistics is believed to be one of the most promising solutions for capturing the remaining values from used products and has been extensively focused by both academics and practitioners during the past two decades. Conceptual framework, mathematical programming and computational algorithms have been developed for decision making at strategic, tactical and operational levels of a reverse supply chain. In this paper, a novel idea for the design and planning of a general reverse logistics network is suggested and formulated through multi-objective mixed integer programming. The reverse logistics system is an independent network and comprises of three echelons for collection, remanufacturing, recycling, energy recovery and disposal of used products. The mathematical model not only takes into account the minimization of system operating costs, but also considers minimization of carbon emissions related to the transportation and processing of used products, and the minimum rate of resource utilization is also required in order to minimize the waste of resources in landfill. Illustration, sensitivity analysis and numerical experimentation are given to show the applicability and computational efficiency of the proposed model. This work provides an alternative approach to account both economic and environmental sustainability of reverse logistics system. The result explicitly shows the trade-off between the costs and carbon emissions, cost effectiveness for improving environmental performance, and influences from resource utilization, all of which have great practical implication on decision making of network configurations and transportation planning of reverse logistics system. For future development of this work, suggestions are also given latter in this paper.
Source at https://doi.org/10.1007/s00170-016-8612-6.
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Published version in: Yu, H. (2019). Optimization models and methods for sustainable reverse logistics network design. (Doctoral thesis). https://hdl.handle.net/10037/14737