A general reverse logistics network design model for product reuse and recycling with environmental considerations

Abstract

Abstract: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. (2) is not monetized, which means the carbon emissions are not measured by the same units of system operating costs, so the…" 5, Page 14 Line 5 Eplain why "the maximum number for landfill is one" Powered by Editorial Manager® and ProduXion Manager® from Aries Systems CorporationThank you very much for the question. The number of facilities in illustrative example is flexible to change, e.g. the maximum number of landfill can be changed according with the requirement of decision maker. The main consideration for setting the maximum number of landfill to "1" is that for the given system, one landfill is able to fulfill the requirement for waste disposal. 6, Page 16Line 57 Do you mean "slop" or "slope"? Response to Reviewer CommentsThank you very much for the correction. We have revised the text from "slop" to "slope". 7, Page 18Line 7 where is "changes, but..." write "changed, but..." State what do you mean by "break -even point" Define RuR Thank you very much for the correction. We have corrected "changes, but…" to "changed, but…"The explanation of break-even point is added in the text at page 18 as "Besides, the break-even points from which the system performance starts to change with the increase or decrease of required utilization rate can...

Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)

“…Reverse logistics refers to the management of various forms of returned flows in a supply chain [21]. The focus of reverse logistics is to maximize the value recovery from end-of-life (EOL) and end-of-use (EOU) products through reuse, re-fabrication, remanufacturing, recycling, and energy recovery [22,23]. Reverse logistics network design determines the configuration and the operational strategy of a reverse logistics system, which has a significant impact on its long-term performance.…”

“…Over the last two decades, quantitative optimization models and computational methods have been extensively investigated in order to improve the decision-making on reverse logistics network design at both strategic and operational levels [22,24]. With the implementation of different techniques, these decision-support models focused mainly on the optimization of economic efficiency [25][26][27][28], environmental impact [23,[28][29][30], potential job creation as well as other socio-economic impact factors [31]. The effectiveness of these optimization models and computational methods have been validated in a large variety of industries and business sectors [32][33][34][35].…”

A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

“…The last part calculates the carbon trading costs. Carbon emission is considered as the most important cause of global warming and climate change, so it has been introduced and formulated as the environmental indicator for sustainable supply chain design in many previous studies (e.g., Yu and Solvang [12], Govindan et al [38], Diabat et al [39], Kannan et al [40], Fahimnia et al [41], and Yu et al [42]). In this paper, both the economic and environmental sustainability of the reverse logistics of WEEE are taken into account, so the carbon emissions of the reverse logistics activities for WEEE management are quantified by a well-established method: carbon trading [39,40] and combined with the cost objective.…”

A Goal Programming Approach for Green Supply Chain Network Optimization

“…In Eq. (20), the random integer is also generated within a given interval which reflects the interactions between processing cost and CO2 emission. Table II presents the relevant parameters of candidate locations of distribution center.…”