A tabu search heuristic for the vehicle routing problem
Management Science
The vehicle routing problem
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INFORMS Journal on Computing
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Computers and Operations Research
Applying hybrid meta-heuristics for capacitated vehicle routing problem
Expert Systems with Applications: An International Journal
A hybrid genetic algorithm for the capacitated vehicle routing problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Fast genetic programming on GPUs
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
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This paper presents an approach based on Monte Carlo Simulation (MCS) to solve the Capacitated Vehicle Routing Problem (CVRP) with maximum traveling distance per route and additional costs per service, which introduces additional challenges to the classical CVRP. The basic idea behind our approach is to combine direct MCS with an efficient heuristics --e.g. the Clarke and Wright Savings (CWS) algorithm-- and a divide-and-conquer technique. The CWS heuristics provides a constructive methodology which is improved in two ways: (i) a special random behavior is introduced in the methodology --in this case, a geometric distribution is used for this purpose; and (ii) a divide-and-conquer technique is used to decompose the original problem in smaller sub-problems that are easy to deal with. Our approach is then validated using a set of well-known benchmarks. Finally, the paper discusses some advantages and disadvantages of our approach with respect other existing approaches.