Evolutionary algorithms and fuzzy clustering for control of a dynamic vehicle routing problem oriented to user policy

Diego Muñoz-Carpintero, Alfredo Núñez, Doris Sáez, Cristián E. Cortés

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

In this paper, a dynamic vehicle routing problem (DVRP) is solved based on hybrid predictive control strategy with an objective function that includes two dimensions: user and operator costs. To handle some undesired assignments for the users, a new objective function is designed, able to carry out the fact that some users can become particularly annoyed if their service is postponed. Genetic algorithms are proposed for efficiently solving the DVRP. Fuzzy clustering is applied for computing trip patterns from historical data under more realistic scenarios. An illustrative experiment through simulation of the process is presented to show the potential benefits (mainly for users) of the new design.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Number of pages8
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain
Duration: 18 Jul 201023 Jul 2010

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
CountrySpain
CityBarcelona
Period18/07/1023/07/10

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