Reverse logistics optimisation for waste collection and disposal in health institutions: the case of Turkey

Waste management in health institutions has become important in recent years because of the increase in population and industrialisation. Waste generated from health institutions has risks for human health and the environment. Therefore, this paper presents a reverse logistics optimisation for waste collection and disposal in Turkish health institutions. A multiperiod, multitype product waste reverse logistics network was designed to build an effective collection and disposal system for waste generated from health institutions in Turkey. A mixed integer linear programming model was developed to determine the optimal number and locations of the facilities for efficient waste management in health care by minimising the total cost. In this context, a sensitivity analysis was conducted to examine the impact of the incremental changes of waste amounts on the optimal reverse logistics network. According to increasing waste amounts, the numbers of changes in facilities are analysed and strategies are specified.

• Record URL:
  https://doi.org/10.1080/13675567.2016.1234595
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13675567
• Supplemental Notes:
  • Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Budak, Aysenur
  • Ustundag, Alp
• Publication Date: 2017-7

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: pp 322-341
• Serial:
  • International Journal of Logistics Research and Applications
  • Volume: 20
  • Issue Number: 4
  • Publisher: Taylor & Francis
  • ISSN: 1367-5567
  • EISSN: 1469-848X
  • Serial URL: http://www.tandfonline.com/toc/cjol20/current

Subject/Index Terms

• TRT Terms: Health care facilities; Logistics; Optimization; Waste disposal
• Geographic Terms: Turkey
• Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01638966
• Record Type: Publication
• Files: TRIS
• Created Date: May 31 2017 3:00PM