Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem

Main Article Content

B J Macias
Universidad de los Andes
http://orcid.org/0000-0002-8752-7061
C A Amaya
Universidad de los Andes
http://orcid.org/0000-0003-1537-1616

Keywords

genetic algorithm, memetic algorithm, multi-objective optimization, CARP, OCARP, MO-OCARP, neural networks, local search

Abstract

The arc routing problem with a variable starting/ending position (Open Capacitated Arc Routing Problem - OCARP), in its classic version, pursues the best strategy to serve a set of customers located in the network arcs using vehicles. Compared to the Capacitated Arc Routing Problem (CARP), the OCARP lacks of constrains that guarantee that each vehicle ought to start and end the tour at a given vertex (also known as a depot). The aim of this paper is to propose a heuristic to find an efficient frontier for the main objective functions: minimize the number of vehicles and the total cost. Additionally, a hybrid algorithm that complements the genetic algorithm with artificial intelligence operator is proposed.

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Published
Feb 22, 2016
DOI https://doi.org/10.17230/ingciencia.12.23.2

Article Details

How to Cite
Macias, B. J., & Amaya, C. A. (2016). Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem. Ingeniería Y Ciencia, 12(23), 25–46. https://doi.org/10.17230/ingciencia.12.23.2
Issue
Vol. 12 No. 23 (2016)
Section
Articles
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Universidad de los Andes

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