Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
A tabu search heuristic for the vehicle routing problem
Management Science
Algorithms for the vehicle routing problems with time deadlines
American Journal of Mathematical and Management Sciences - Special issue: vehicle routing 2000: advances in time windows, optimality, fast bounds, & multi-depot routing
The vehicle routing problem
Practical Handbook of Genetic Algorithms: New Frontiers
Practical Handbook of Genetic Algorithms: New Frontiers
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
An Adaptive Clustering Method Using a Geometric Shape for Vehicle Routing Problems with Time Windows
Proceedings of the 6th International Conference on Genetic Algorithms
A Parallel Hybrid Evolutionary Metaheuristic for the Period Vehicle Routing Problem
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Vehicle Routing Problem: Doing It The Evolutionary Way
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Solving the vehicle routing problem with adaptive memory programming methodology
Computers and Operations Research
A Hybrid Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Time Windows
Computational Optimization and Applications
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers and Operations Research
SR-1: a simulation-based algorithm for the capacitated vehicle routing problem
Proceedings of the 40th Conference on Winter Simulation
The SR-GCWS hybrid algorithm for solving the capacitated vehicle routing problem
Applied Soft Computing
A hybrid genetic - Particle Swarm Optimization Algorithm for the vehicle routing problem
Expert Systems with Applications: An International Journal
A hybrid algorithm for the vehicle routing problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Honey Bees Mating Optimization algorithm for large scale vehicle routing problems
Natural Computing: an international journal
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
A hybrid particle swarm optimization algorithm for the vehicle routing problem
Engineering Applications of Artificial Intelligence
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing Problem
Expert Systems with Applications: An International Journal
Annals of Mathematics and Artificial Intelligence
Journal of Mathematical Modelling and Algorithms
Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm
Expert Systems with Applications: An International Journal
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Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. In this paper, a hybrid genetic algorithm to address the capacitated vehicle routing problem is proposed. The basic scheme consists in concurrently evolving two populations of solutions to minimize total traveled distance using genetic operators combining variations of key concepts inspired from routing techniques and search strategies used for a time-variant of the problem to further provide search guidance while balancing intensification and diversification. Results from a computational experiment over common benchmark problems report the proposed approach to be very competitive with the best-known methods.