A mixed-integer linear model for optimal processing and transport of secondary materials

Wang, Chin-Huang; Even, John C.; Adams, S. Keith

doi:10.1016/0921-3449(95)00024-d

Cited by 28 publications

(10 citation statements)

References 9 publications

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“…For this purpose, pre-processing centres need to be installed where collected paper is sorted and compacted and then transported to a production plant (compare Wang et al, 1995). In our model, processing centres play the same role as disassembly centres in Example 5.1.…”

Section: Example 52: Paper Recyclingmentioning

confidence: 99%

Quantitative Models for Reverse Logistics

Fleischmann

2001

Lecture Notes in Economics and Mathematical Systems

272

144

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Section: Example 52: Paper Recyclingmentioning

confidence: 99%

Quantitative Models for Reverse Logistics

Fleischmann

2001

Lecture Notes in Economics and Mathematical Systems

272

144

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“…With a few exceptions [32,33,43], the majority of the existing models focus on the case of deterministic supply and demand [1, 2, 9, 22, 23, 26, 31, 35, 37, 38, 42, 45-47, 50, 51, 58, 60, 61]. A careful examination of the model characteristics reveals that ND models for RSC can be classified as two-stage [22,23,31,38,50,60] or three-stage [1,33,42,43,61] discrete facility location formulations. Similarly, ND models for CLSC can be classified as one-stage [37,45] or twostage [2,9,26,32,35,46,47,51,58] discrete facility location formulations with reverse flows.…”

Section: Discussionmentioning

confidence: 98%

Network design for reverse and closed‐loop supply chains: An annotated bibliography of models and solution approaches

2009

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Historically, both the theory and practice of supply chain management have placed an emphasis on manufacturing and distribution operations, i.e., the forward channel, which consists of suppliers, manufacturers, distributors, retailers, and customers. Recently, increased attention to product recovery practices has extended the scope of traditional supply chain management by drawing attention to collection, demanufacturing, and remanufacturing operations, i.e., the reverse channel, which consists of final-users, collectors, demanufacturers, and remanufacturers. To optimize the performance of the extended supply chain, there is a need to establish an effective and efficient infrastructure via optimal network design. As a result, network design for product recovery has attracted the attention of a growing number of researchers in the past decade. In an attempt to draw more academic attention to this area, this annotated bibliography provides a detailed account of the published literature. The article is organized into two main sections that focus on (i) reverse supply chain network design, which is concerned with establishing an infrastructure to manage the reverse channel only and (ii) closed-loop supply chain network design, which is concerned with establishing an infrastructure to manage both forward and reverse channels in a coordinated manner. Specifically, we describe the operational characteristics of the underlying supply chain system considered in each paper, highlight the features of the network design model proposed therein, and discuss the proposed solution approach along with a brief description of significant computational work, if available. In conclusion, a critical review of the published literature is given and potential areas for future research are identified.

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“…Research on recycling and resource recovery for specific materials such as paper, plastics and sand include Pohlen and Farris (1992), Wang et al (1995), Huttunen (1996) and Barros et al (1998). Examples of product recovery and reuse include copy machines (Theirry et al 1995;Theirry 1997;Krikke 1998), computers and electronics equipment (Jayaraman et al 1997;Hong et al 2006), and reusable transportation containers (Kroon and Vrijens 1995).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Flapper (1995), Fleishmann et al (2000, and Guide and Harrison (2003) give systematic overviews and challenges of the logistic aspects of reuse and recycling in closed-loop supply chains. Much of the research in RPS tends to be product, or system, specific due to the various features and complexities needed to handle the different recycling and reuse scenarios.Research on recycling and resource recovery for specific materials such as paper, plastics and sand include Pohlen and Farris (1992), Wang et al (1995), Huttunen (1996 and Barros et al (1998). Examples of product recovery and reuse include copy machines (Theirry et al 1995; Theirry 1997;Krikke 1998), computers and electronics equipment (Jayaraman et al 1997; Hong 3 et al 2006), and reusable transportation containers (Kroon and Vrijens 1995).…”

mentioning

confidence: 99%

Decentralized decision-making and protocol design for recycled material flows

Hong

Ammons

Park

2008

International Journal of Production Economics

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Reverse logistics networks often consist of several tiers with independent members competing at each tier. This paper develops a methodology to examine the individual entity behavior in reverse production systems where every entity acts to maximize its own benefits. We consider two tiers in the network, collectors and processors. The collectors determine individual flow functions that relate the flow they provide each processor to the overall vector of prices that the processors determine. Because the exact final prices are unknown, each collector solves a robust optimization formulation where the prices paid by the processors are assumed to be within given ranges. The processors compete for the flow from the collectors until the Nash equilibrium is reached in this competitive tier, which sets the vector of prices to be offered to the collectors. To demonstrate the approach, a numerical example is given for a prototypical recycling network.Key words: decentralized decision-making; reverse production systems; the Nash Equilibrium IntroductionMaximizing the efficiency of recycled material flows is growing in urgency due to high demands in many raw material markets and the increasing concern for environmental impact of disposal.Supply chains are evolving from "open loop" unidirectional flows of materials, parts, and products from suppliers to end customers into more complex "closed loop" linked forward and reverse arcs (Fleischmann et al. 2000;Guide and Harrison 2003;Realff et al. 2004). Forward production systems are being expanded to incorporate reverse production systems (RPS) that include sorting, demanufacturing and/or refurbished processes in reverse logistics systems.Most of the research on RPS design views the system in a centralized way; the key assumption is that one planner has the requisite information about all the participating entities and seeks the optimal solution for the entire system (see Ammons et al. 2001;Shih 2001;Barros et al. 1998;Assavapokee et al. 2005). Wang et al. (2004) remark upon the three major drawbacks of centralized supply chain optimization models: (1) By ignoring the independence of the supply chain members, the competitive behavior between entities may lower the system 1 efficiency and hence a centralized model may not capture the appropriate bargaining mechanisms that can mitigate the competitive behavior; (2) The cost of information processing may be expensive and the central decision maker must gather all the information from every entity; and (3) The computation of solutions to centralized optimization models can be very challenging.Many emerging RPS structures consist of several independent entities where individual entrepreneurs have their own profit functions and often are unwilling to reveal their own information to each other or the public. This type of system behavior is decentralized. Often the decision variables for each entity in a decentralized system are also influenced by other entities' decisions, coupling prices between members of the same tier, and flows betw...

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A mixed-integer linear model for optimal processing and transport of secondary materials

Cited by 28 publications

References 9 publications

Quantitative Models for Reverse Logistics

Quantitative Models for Reverse Logistics

Network design for reverse and closed‐loop supply chains: An annotated bibliography of models and solution approaches

Decentralized decision-making and protocol design for recycled material flows

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