AccScience Publishing / IJOCTA / Volume 9 / Issue 2 / DOI: 10.11121/ijocta.01.2019.00718
RESEARCH ARTICLE

A bi-objective model for sustainable logistics and operations planning of WEEE recovery

Emine Nisa Kapukaya1 Alperen Bal2 Sule Itir Satoglu1*
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1 Department of Industrial Engineering, Istanbul Technical University, Turkey
2 Department of Industrial Engineering, Yalova University, Turkey
Submitted: 25 September 2018 | Accepted: 24 December 2018 | Published: 6 February 2019
© 2019 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

The Triple-bottom-line concept suggests that firms must consider the environmental and social impacts of their decisions, beside the economic aspects. Hence, the sustainability of the firms’ operations can be reached. The purpose of this study is to develop a bi-objective, multi-product and multi-period mixed-integer model for the operations planning of electrical-electronic waste (WEEE) recovery facilities, by considering social (workforce) constraints. Main objective is the minimization of net recycling and logistics costs offset by the profit earned by recovered material sales, and second objective is the maximization of hazardous materials recovery.  Collection of used products from the specified regions is decided and the required machine-hours, inventory and workforce decisions are made. Besides, both weight-based and unit-based WEEE recovery targets are separately considered, as a unique aspect. A sensitivity analysis is conducted with various scrap prices to understand operations planning in changing conditions. Results show that weight-based targets enhance recovery amounts.

Keywords
Waste recovery
Sustainable operations planning
Bi-objective model
Waste electrical-electronic equipment
Conflict of interest
The authors declare they have no competing interests.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing