A genetic algorithm for vehicle routing in logistic networks with practical constraints
A genetic algorithm for vehicle routing in logistic networks with practical constraints
Author(s): Grzegorz Koloch, Michał Lewandowski, Marcin Zientara, Grzegorz Grodecki, Piotr Matuszak, Igor Kantorski, Adam NowackiSubject(s): Economy, Socio-Economic Research
Published by: Główny Urząd Statystyczny
Keywords: rich vehicle routing problem; brownfield; hubs and satellites; genetic algorithm
Summary/Abstract: We optimise a postal delivery problem with time and capacity constraints imposed on vehicles and nodes of the logistic network. Time constraints relate to the duration of routes, whereas capacity constraints concern technical characteristics of vehicles and postal operation outlets. We consider a method which can be applied to a brownfield scenario, in which capacities of outlets can be relaxed and prospective hubs identified. As a solution, we apply a genetic algorithm and test its properties both in small case studies and in a simulated problem instance of a larger (i.e. comparable with real-world instances) size. We show that the genetic operators we employ are capable of switching between solutions based on direct origin-to-destination routes and solutions based on transfer connections, depending on what is more beneficial in a given problem instance. Moreover, the algorithm correctly identifies cases in which volumes should be shipped directly, and those in which it is optimal to use transfer connections within a single problem instance, if an instance in question requires such a selection for optimality. The algorithm is thus suitable for determining hubs and satellite locations. All considerations presented in this paper are motivated by real-life problem instances experienced by the Polish Post, the largest postal service provider in Poland, in it daily plans of delivering postal packages, letters and pallets.
Journal: Przegląd Statystyczny. Statistical Review
- Issue Year: 68/2021
- Issue No: 3
- Page Range: 16-40
- Page Count: 25
- Language: English