A biased-randomized iterated local search for the vehicle routing problem with optional backhauls

Julio C. Londoño ^[1] ; Rafael D. Tordecilla ^[3] ; Leandro do C. Martins ^[2] ; Angel A. Juan ^[2]
1. [1] Universidad del Valle (Colombia)
  
  Universidad del Valle (Colombia)
  
  Colombia
2. [2] Universitat Oberta de Catalunya
  
  Universitat Oberta de Catalunya
  
  Barcelona, España
3. [3] Universitat Oberta de Catalunya, España; Universidad de La Sabana, Colombia
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Localización: Top, ISSN-e 1863-8279, ISSN 1134-5764, Vol. 29, Nº. 2, 2021, págs. 387-416
Idioma: inglés
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Resumen
- The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional—but subject to a penalty cost. Both transportation costs and penalties associated with non-collecting decisions are considered. A mixed-integer linear model is proposed and solved for small instances. Also, a metaheuristic algorithm combining biased randomization techniques with iterated local search is introduced for larger instances. Our approach yields cost savings and is competitive when compared to other state-of-the-art approaches.