Applying the Ant Colony Optimisation Algorithm to the Capacitated Multi-Depot Vehicle Routing Problem

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F16%3A00532805" target="_blank" >RIV/60162694:G42__/16:00532805 - isvavai.cz</a>
Result on the web
<a href="http://vavtest.unob.cz/registr" target="_blank" >http://vavtest.unob.cz/registr</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1504/IJBIC.2016.10000256" target="_blank" >10.1504/IJBIC.2016.10000256</a>

Result language
angličtina
Original language name
Applying the Ant Colony Optimisation Algorithm to the Capacitated Multi-Depot Vehicle Routing Problem
Original language description
The Multi-Depot Vehicle Routing Problem (MDVRP) is an extension of a classic Vehicle Routing Problem (VRP). There are many heuristic and metaheuristic algorithms (e.g. tabu search, simulated annealing, genetic algorithms) as this is an NP-hard problem and, therefore, exact methods are not feasible for more complex problems. Another possibility is to adapt the Ant Colony Optimization (ACO) algorithm to this problem. This article presents an original solution of authors to the MDVRP problem via ACO algorithm. The first part deals with the algorithm including its principles and parameters. Then several examples and experiments are shown.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
KA - Militarism
OECD FORD branch
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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