Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet

Oscar Dominguez (), Angel Juan, Barry Barrios (), Javier Faulin () and Alba Agustin ()
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Oscar Dominguez: University of Las Palmas de Gran Canaria
Barry Barrios: IN3-Open University of Catalonia
Javier Faulin: Public University of Navarre
Alba Agustin: Public University of Navarre

Annals of Operations Research, 2016, vol. 236, issue 2, No 6, 383-404

Abstract: Abstract This paper discusses the two-dimensional loading capacitated vehicle routing problem (2L-CVRP) with heterogeneous fleet (2L-HFVRP). The 2L-CVRP can be found in many real-life situations related to the transportation of voluminous items where two-dimensional packing restrictions have to be considered, e.g.: transportation of heavy machinery, forklifts, professional cleaning equipment, etc. Here, we also consider a heterogeneous fleet of vehicles, comprising units of different capacities, sizes and fixed/variable costs. Despite the fact that heterogeneous fleets are quite ubiquitous in real-life scenarios, there is a lack of publications in the literature discussing the 2L-HFVRP. In particular, to the best of our knowledge no previous work discusses the non-oriented 2L-HFVRP, in which items are allowed to be rotated during the truck-loading process. After describing and motivating the problem, a literature review on related work is performed. Then, a multi-start algorithm based on biased randomization of routing and packing heuristics is proposed. A set of computational experiments contribute to illustrate the scope of our approach, as well as to show its efficiency.

Keywords: Heterogeneous vehicle routing problem; Two-dimensional bin packing problem; Randomized heuristics; Multi-start algorithms (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (13)

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DOI: 10.1007/s10479-014-1551-4

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