Memetic Algorithm Based on a Constraint Satisfaction Technique for VRPTW

Authors:
Marco A. Cruz-Chávez;Ocotlán Díaz-Parra;David Juárez-Romero;Martín G. Martínez-Rangel
Affiliations:
CIICAp,;CIICAp,;CIICAp,;FCAeI, Autonomous University of Morelos State, Cuernavaca, Mexico C.P. 62110
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 7
Cited 0

Algorithms for the vehicle routing and scheduling problems with time window constraints

Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability; A Guide to the Theory of NP-Completeness

Computers and Intractability; A Guide to the Theory of NP-Completeness
A New GA Approach for the Vehicle Routing Problem

ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Planning, Scheduling And Constraint Satisfaction: From Theory To Practice

Planning, Scheduling And Constraint Satisfaction: From Theory To Practice
Search Algorithm for the Constraint Satisfaction Problem of VRPTW

CERMA '07 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference
Constrained multi-objective optimization using steady state genetic algorithms

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper a Memetic Algorithm (MA) is proposed for solving the Vehicles Routing Problem with Time Windows (VRPTW) multi-objective, using a constraint satisfaction heuristic that allows pruning of the search space to direct a search towards good solutions. An evolutionary heuristic is applied in order to establish the crossover and mutation between sub-routes. The results of MA demonstrate that the use of Constraints Satisfaction Technique permits MA to work more efficiently in the VRPTW.