The location routing problem using electric vehicles with constrained distance

Abdullah Almouhanna, Carlos Quintero-Araujo, Javier Panadero, Angel A. Juan, Banafsheh Khosravi, Djamila Ouelhadj

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The introduction of Electric Vehicles (EVs) in modern fleets facilitates a shift towards greener road transportation practices. However, the driving ranges of EVs are limited by the duration of their batteries, which raises some operational challenges. This paper discusses the Location Routing Problem with a Constrained Distance (LRPCD), which is a natural extension of the Location Routing Problem when EVs are utilized. A fast multi-start heuristic and a metaheuristic are proposed to solve the LRPCD. The former combines biased-randomization techniques with the well-known Tillman’s heuristic for the Multi-Depot Vehicle Routing Problem. The latter incorporates the biased-randomized approach into the Variable Neighborhood Search (VNS) framework. A series of computational experiments show that the multi-start heuristic is able to generate good-quality solutions in just a few seconds, while the biased-rendomized VNS metaheuristic provides higher-quality solutions by employing more computational time.
Original languageEnglish
Article number104864
Number of pages16
JournalComputers & Operations Research
Early online date3 Dec 2019
Publication statusPublished - 1 Mar 2020


  • location routing problem
  • green logistics
  • variable neighborhood search
  • biased randomization


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