Planning decisions for recycling products containing hazardous and explosive substances: A fuzzy multi-objective model


Dinler E., Gungor Z.

RESOURCES CONSERVATION AND RECYCLING, vol.117, pp.93-101, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 117
  • Publication Date: 2017
  • Doi Number: 10.1016/j.resconrec.2016.11.012
  • Journal Name: RESOURCES CONSERVATION AND RECYCLING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.93-101
  • Keywords: Recycling, Production planning, Fuzzy multi-objective optimization, Hazardous waste management, SUPPLY CHAINS, RECOVERY, RISK
  • Gazi University Affiliated: Yes

Abstract

The rapid development of modern technology leads to the rapid consumption of natural resources, which in turn causes an increasing accumulation of waste materials. Manufacturers must now assume the responsibility for reclamation, recycling and disposal of their products that have reached the end of their life cycles. During the product recycling process, the detection and disposal of explosive substances must be performed with the utmost caution. This study proposes a fuzzy multi-objective linear programming model for use in planning of recycling processes for products that contain hazardous and explosive substances. Application of the proposed model has been carried out in a middle-sized factory, where various products that have completed their life cycles or has become inoperative are delivered to the factory at uncertain times from various warehouses. Results from the proposed model have been obtained using the system data to solve problems on various scales. A hybrid Monte Carlo simulation has been used to obtain Pareto-optimal solutions to solve the model. The planning model is shown to differ from the recycling production planning model in terms of its consideration of the explosion risk and the limitations and goals related to this risk; this model provides considerable flexibility for both the recycling process and the planning decisions taken for this process. (C) 2016 Elsevier B.V. All rights.reserved.