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Journal ArticleDOI

Planning of waste electrical and electronic equipment (WEEE) recycling facilities: MILP modelling and case study investigation

21 Feb 2015-Flexible Services and Manufacturing Journal (Springer US)-Vol. 27, Iss: 4, pp 479-508
TL;DR: The model has the potential to enable the decision maker to come with stronger decisions related to both bidding process and operational strategies of the facility, and is presented by presenting a mixed integer linear programming model to determine the maximum bid price offer.
Abstract: Waste electrical and electronic equipment (WEEE) consist of many different substances some of which contain hazardous components and valuable materials. The recovery of WEEE plays a key role on environmental sustainability because it minimizes the negative effects of hazardous materials and helps the efficient use of world’s limited resources. Recovery strategies enable companies to collect reusable components and to recycle the material content of WEEE by using operations like sorting, disassembly and bulk recycling. Usually companies associated with municipals collect WEEE from end-users and/or collection points. Then they sell these items to WEEE recycling facilities through bidding. For recycling facilities, it is important to generate the best operational level decisions to receive and handle WEEE. This study contributes to the fulfillment of this need by presenting a mixed integer linear programming model to determine the maximum bid price offer while determining the best operation planning strategies. In order to demonstrate the potential of the proposed model, a real life case study along with several scenarios is studied. The findings of the case study indicate that the model has the potential to enable the decision maker to come with stronger decisions related to both bidding process and operational strategies of the facility.
Citations
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Journal ArticleDOI
TL;DR: In this paper, a multi-objective genetic algorithm based on non-dominated sorting genetic algorithm II is designed to address the problem of disassembly service in cloud-based disassembly system.

91 citations

Journal ArticleDOI
TL;DR: Open burning practices are revealed as most polluting ‘technology’, followed by mechanical treatment and leaching, and significant levels of pollutants have been detected in human bodies, both children and adults, working in or living in areas with informal WEEE treatment.
Abstract: In the last few decades, the rapid technological evolution has led to a growing generation of waste electrical and electronic equipment (WEEE). Not rarely, it has been exported from industrialized to developing countries, where it represents a secondary source of valuable materials such as gold, copper, and silver. The recycling of WEEE is often carried out without any environmental and health protection. This paper reviews recent literature dealing with the informal treatment of WEEE in developing regions, gathering and analyzing data on concentration of both inorganic and organic pollutants in the environment. Open burning practices are revealed as most polluting ‘technology’, followed by mechanical treatment and leaching. Significant levels of pollutants have been detected in human bodies, both children and adults, working in or living in areas with informal WEEE treatment.

60 citations

Journal ArticleDOI
TL;DR: In this paper, a two-stage stochastic bi-objective mixed integer programming model is proposed for the network design problem of a multi-product multi-echelon sustainable reverse logistics system under uncertainty, which aims at providing a set of Pareto solutions between profitability and environmental performance.

58 citations


Cites background from "Planning of waste electrical and el..."

  • ...In order to provide optimal decisions on the biding price and facility operations, Capraz et al. (2015) proposed a mixed integer linear programming for the recycling system of waste electrical and electronic equipment (WEEE)....

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  • ...In order to simultaneously maximize the profits, fill rate of customer demands and satisfaction level of stakehold rs, Özkır and Başlıgil (2013) developed a fuzzy multi-objective model for planning a closed-loop supply chain with inexact parameters....

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  • ...The latest modelling efforts and computational analysis on sustainable reverse logistics network design under uncertainty have shown a significant improvement on the understanding of the trade-offs among economic, environmental and social sustainability (Feitó-Cespón et al., 2017, Talaei et al., 2016), implications from the customer satisfaction (Özkır and Başlıgil, 2013), on-site/off-site separations (Rahimi and Ghezavati, 2018), as well as computational performance (Govindan et al., 2016b, Soleimani et al., 2017)....

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  • ...M AN US CR IP T AC CE PT ED Table 1 Review of the recent research works on reverse logistics network design Articles Product flow Capacity Network Objectives Parameter Modelling approach Solution Solver Validation Single Multiple Nonflexible Flexible Unspecified Forward Reverse Economic Environmental Social Others Exact Approximation Pishvaee et al. (2009) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MIP ˅ LINGO Experiment El-Sayed et al. (2010) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MIP ˅ XpressSP Experiment Pishvaee et al. (2011) ˅ ˅ ˅ ˅ ˅ Nondeterministic Robust MIP ˅ CPLEX Experiment Kannan et al. (2012) ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ LINGO Experiment Demirel et al. (2016) ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS CPLEX Case Alshamsi and Diabat (2015) ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS CPLEX Case Ghezavati and Beigi (2016) ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ MATLAB GAMS Experiment Yu and Solvang (2016b) ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ LINGO Experiment Govindan et al. (2016b) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Fuzzy MOMIP ˅ ˅ MATLAB MINITAB Experiment Zandieh and Chensebli (2016) ˅ ˅ ˅ ˅ Deterministic MIP ˅ MATLAB Experiment Li et al. (2017) ˅ ˅ ˅ ˅ Deterministic MIP ˅ C++ Experiment Silva et al. (2017) ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ CPLEX Case Guo et al. (2017a) ˅ ˅ ˅ ˅ Deterministic MIP ˅ Case Guo et al. (2017b) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic Two-stage MIP ˅ Case Budak and Ustundag (2017) ˅ ˅ ˅ ˅ Deterministic MIP ˅ Xpress IVE Case Fard and HajaghaeiKeshteli (2018) ˅ ˅ ˅ ˅ ˅ Deterministic Game theoretic trilevel MIP ˅ Experiment Rahimi and Ghezavati (2018) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MOMIP ˅ GAMS Experiment Demirel and Gökçen (2008) ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS CPLEX Experiment Amin and Zhang (2012) ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS Experiment Diabat et al. (2013) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS CPLEX Experiment Özkır and Başlıgil ˅ ˅ ˅ ˅ ˅ ˅ Non- Fuzzy MOMIP ˅ GAMS Experiment M AN US CR IP T AC CE PT ED (2013) deterministic Ramos et al. (2014) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ CPLEX Case Garg et al. (2015) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ LINGO Experiment Ghayebloo et al. (2015) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ GLPK Experiment Capraz et al. (2015) ˅ ˅ ˅ ˅ Deterministic MIP ˅ CPLEX Case Govindan et al. (2016a) ˅ ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ LINGO Experiment Yu and Solvang (2016a) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MIP ˅ LINGO Experiment Kheirkhah and Rezaei (2016) ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS Experiment Talaei et al. (2016) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Robust fuzzy MIP ˅ Experiment Entezaminia et al. (2017) ˅ ˅ ˅ ˅ ˅ Nondeterministic Robust MIP ˅ CPLEX Case Keshavarz Ghorabaee et al. (2017) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Fuzzy MOMIP ˅ Experiment Jindal and Sangwan (2017) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Fuzzy MOMIP ˅ LINGO Experiment John et al. (2017) ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ LINGO Experiment Yilmaz et al. (2017) ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ OPL Case Kannan et al. (2017) ˅ ˅ ˅ ˅ Deterministic MIP ˅ LINGO Experiment Temur and Bolat (2017) ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ GAMS CPLEX Case Fattahi and Govindan (2017) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MIP ˅ GAMS CPLEX Experiment Feitó-Cespón et al. (2017) ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MOMIP ˅ MATLAB Experiment Babaveisi et al. (2017) ˅ ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ Experiment Soleimani et al. (2017) ˅ ˅ ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Fuzzy constrained MOMIP ˅ LINGO Experiment Alshamsi and Diabat (2017) ˅ ˅ ˅ ˅ Deterministic MIP ˅ CPLEX Case Yu and Solvang (2017) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic constrained MIP ˅ LINGO Experiment Coelho and Mateus (2017) ˅ ˅ ˅ ˅ Deterministic MIP ˅ CPLEX Experiment John et al. (2018) ˅ ˅ ˅ ˅ Deterministic MIP ˅ LINGO Case M AN US CR IP T AC CE PT ED Trochu et al. (2018) ˅ ˅ ˅ ˅ Nondeterministic Stochastic MIP ˅ Case Jabbarzadeh et al. (2018) ˅ ˅ ˅ ˅ ˅ Nondeterministic Robust MIP ˅ GAMS Case Haddadsisakht and Ryan (2018) ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic robust MIP ˅ CPLEX Experiment This research ˅ ˅ ˅ ˅ ˅ ˅ Nondeterministic Stochastic MOMIP ˅ LINGO Experiment Note: MIP=Mixed integer programming; MOMIP=Multi-objective mixed integer programming M AN US CR IP T AC CE PT ED 3....

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  • ...…˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS Experiment Diabat et al. (2013) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MIP ˅ GAMS CPLEX Experiment Özkır and Başlıgil ˅ ˅ ˅ ˅ ˅ ˅ Non- Fuzzy MOMIP ˅ GAMS Experiment M AN US CR IP T AC CE PT ED (2013) deterministic Ramos et al. (2014) ˅ ˅ ˅ ˅ ˅ ˅ Deterministic MOMIP ˅ CPLEX…...

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Journal ArticleDOI
TL;DR: This study presents several upper and lower bounding procedures that assign the tasks to the workstations so as to maximize the total net revenue and reveals that the procedures produce satisfactory results.

49 citations

Journal ArticleDOI
TL;DR: In this paper, a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for waste electrical and electronic equipment (WEEE) management under uncertainty is presented.
Abstract: Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE) contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.

42 citations


Cites background from "Planning of waste electrical and el..."

  • ...[28] propose a mixed integer linear programming for decision-making of recycling companies of WEEE, and the model simultaneously determines the maximal bid price offered by the company and the optimal operational plan of the plant....

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References
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01 Jan 1995
TL;DR: In this article, a case study based on the Product Recovery Management (PRM) system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues.
Abstract: textThis article examines strategic production and operations management issues in product recovery management (PRM). PRM encompasses the management of all used and discarded products, components, and materials for which a manufacturing company is legally, contractually, or otherwise responsible. The objective of PRM is to recover as much of the economic (and ecological) value of used and discarded products, components, and materials as reasonably possible, thereby reducing the ultimate quantities of waste to a minimum. This article also discusses the relevance of PRM to durable products manufacturers. It contains a categorization of PRM decisions. A case study based on the PRM system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues. The experiences of two other pro-active manufacturers (BMW and IBM) are also discussed

1,321 citations

Journal ArticleDOI
TL;DR: In this paper, a case study based on the Product Recovery Management (PRM) system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues.
Abstract: This article examines strategic production and operations management issues in product recovery management (PRM). PRM encompasses the management of all used and discarded products, components, and materials for which a manufacturing company is legally, contractually, or otherwise responsible. The objective of PRM is to recover as much of the economic (and ecological) value of used and discarded products, components, and materials as reasonably possible, thereby reducing the ultimate quantities of waste to a minimum. This article also discusses the relevance of PRM to durable products manufacturers. It contains a categorization of PRM decisions. A case study based on the PRM system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues. The experiences of two other pro-active manufacturers (BMW and IBM) are also discussed.

1,275 citations