Integrating disassembly line balancing in the planning of a reverse logistics network from the perspective of a third party provider

Devika Kannan, Kiran Garg, P. C. Jha, Ali Diabat

    Research output: Contribution to journalArticle

    Abstract

    The increasing pressure due to legislation and various public policies has prompted manufacturers to seriously take into consideration the impact of electronic waste. To overcome this challenge, several manufacturers have incorporated reverse logistics into their business lines. Due to a lack of resources and/or managerial expertise, several companies choose to outsource product recovery activities to third parties. The growing demand has given rise to the number of third party logistics providers, who are assigned the task of efficiently and cost effectively achieving product recovery. The work of the 3PRL’s commences with the collection of returned products from various companies to retrieve maximum value harvested in the form of reusable products, components and materials. Thus, a 3PRLP needs to establish a recovery process able to effectively retrieve value from various types of product. To deal with multiple types of products, the recovery network needs to work with a balanced disassembly line. Thus in this paper we proposes a cost effective reverse logistics network from the perspective of the third party, which integrates the disassembly line balancing in the planning recovery network. This study develops a mixed integer non-linear programming problem for the same. The model is validated using various products from the liquid crystal displays industry.

    Original languageEnglish (US)
    Pages (from-to)353-376
    Number of pages24
    JournalAnnals of Operations Research
    Volume253
    Issue number1
    DOIs
    StatePublished - Jun 1 2017

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    Keywords

    • Disassembly line balancing
    • Product recovery
    • Public policies
    • Reverse logistics
    • Third party logistics provider

    ASJC Scopus subject areas

    • Decision Sciences(all)
    • Management Science and Operations Research

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