Heuristic approaches to vehicle routing with backhauls and time windows
Computers and Operations Research
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
Vehicle Routing Problem: Doing It The Evolutionary Way
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
2-Path Cuts for the Vehicle Routing Problem with Time Windows
Transportation Science
On the influence of GVR in vehicle routing
Proceedings of the 2003 ACM symposium on Applied computing
A genetic algorithm for unmanned aerial vehicle routing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
An evolutionary-based decision support system for vehicle routing: The case of a public utility
Decision Support Systems
Route optimisation using evolutionary approaches for on-demand pickup problem
International Journal of Advanced Intelligence Paradigms
A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands
Computers and Operations Research
Simulation evaluation for on-demand bus system with electrical vehicles
Intelligent Decision Technologies - Special issue on design of intelligent environment
Localized genetic algorithm for vehicle routing problem with time windows
Applied Soft Computing
Combination and comparison of different genetic encodings for the vehicle routing problem
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
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In this paper we analyse a new evolutionary approach to the vehicle routing problem. We present Genetic Vehicle Representation (GVR), a two-level representational scheme designed to deal in an effective way with all the information that candidate solutions must encode. Experimental results show that this method is both effective and robust, allowing the discovery of new best solutions for some well-known benchmarks.