The Vehicle Routing Problem with Fuzzy Payloads considering Fuel Consumption. Issue 15 (15th December 2021)

• Record Type: Journal Article
• Authors: Zacharia, Paraskevi; Drosos, Christos; Piromalis, Dimitrios; Papoutsidakis, Michail
• Is Part Of: Applied artificial intelligence. Volume 35:Issue 15(2021)
• Page Start: 1755
• Page End: 1776
• Publication Date: 2021-12-15
• Subjects: Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/08839514.2021.1992138
• Languages: English
• ISSNs: 0883-9514

Abstract

ABSTRACT: This paper considers the Vehicle Routing Problem (VRP) with fuzzy payloads with the aim to minimize two criteria: the travel distance and the fuel consumption. VRP with fuzzy payloads is an NP-hard problem, in which a fleet of vehicles with finite capacity leaves from a central depot empty of goods and has to serve a set of geographically dispersed customers associated with fuzzy payloads. Thus, an optimization approach based on a bi-objective Genetic Algorithm is developed that is integrated with fuzziness. This problem differentiates from the classic VRP, since it also considers the fuel consumption to reduce the energy consumption. The efficiency of the developed method is investigated and discussed through a set of test instances. The experimental results highlight the impact of both criteria on the resulted optimum solution and prove that increasing the uncertainty in customers' collection quantities results in more costly solutions.