Models and Algorithms for the Integrated Planning of Bin Allocation and Vehicle Routing in Solid Waste Management

The efficient organization of waste collection systems based on bins located along the streets involves the solution of several tactical optimization problems. In particular, the bin configuration and sizing at each collection site as well as the service frequency over a given planning horizon have to be decided. In this context, a higher service frequency leads to higher routing costs, but at the same time less or smaller bins are required, which leads to lower bin allocation investment costs. The bins used have different types and different costs and there is a limit on the space at each collection site as well as a limit on the total number of bins of each type that can be used. In this paper the authors consider the problem of designing a collection system consisting of the combination of a vehicle routing and a bin allocation problem in which the trade-off between the associated costs has to be considered. The solution approach combines an effective variable neighborhood search metaheuristic for the routing part with a mixed integer linear programming-based exact method for the solution of the bin allocation part. The authors propose hierarchical solution procedures where the two decision problems are solved in sequence, as well as an integrated approach where the two problems are considered simultaneously. Extensive computational testing on synthetic and real-world instances with hundreds of collection sites shows the benefit of the integrated approaches with respect to the hierarchical ones.

• Record URL:
  • https://doi.org/10.1287/trsc.2013.0459
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767714
• Supplemental Notes:
  • Abstracts reprinted with permission of INFORMS (Institute for Operations Research and the Management Sciences, http://www.informs.org).
• Authors:
  • Hemmelmayr, Vera C
  • Doerner, Karl F
  • Hartl, Richard F
  • Vigo, Daniele
• Publication Date: 2014-2

Language

• English

Media Info

• Media Type: Print
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 103-120
• Serial:
  • Transportation Science
  • Volume: 48
  • Issue Number: 1
  • Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
  • ISSN: 0041-1655
  • Serial URL: http://transci.journal.informs.org/

Subject/Index Terms

• TRT Terms: Linear programming; Logistics; Mixed integer programming; Optimization; Routing; Waste management
• Uncontrolled Terms: Metaheuristics; Vehicle routing problem
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01519660
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 26 2014 10:07AM