Genetic Algorithms for Solving Vehicle Routing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F11%3A39894519" target="_blank" >RIV/00216275:25510/11:39894519 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Genetic Algorithms for Solving Vehicle Routing

Popis výsledku v původním jazyce

Author in this paper describes the possibilities of solving some vehicle routing variants by genetic algorithm. Specifically, it is a classical capacitated vehicle routing problem (CVRP), vehicle routing problem with time windows (VRP-TW), vehicle routing problem with simultaneous deliveries and pick-ups (VRPDP) and their mutual combinations. Genetic algorithms are a search method used to find suboptimal solutions of complicated combinatorial problems including vehicle routing. Genetic algorithm (GVR) is quite universal due to the two-level representation of the problem - without major modifications it enables successful solving of CVRP, VRP-TW and possibly also other variants of the problem. GVR enables also fast search for new solutions - operators of crossover and mutations provide solutions whose adjustment is not time demanding, and quality of provided solutions is very good, GVR verified with standard data. Parameters of genetic algorithm can be modified in the program environmen

Název v anglickém jazyce

Genetic Algorithms for Solving Vehicle Routing

Popis výsledku anglicky

Author in this paper describes the possibilities of solving some vehicle routing variants by genetic algorithm. Specifically, it is a classical capacitated vehicle routing problem (CVRP), vehicle routing problem with time windows (VRP-TW), vehicle routing problem with simultaneous deliveries and pick-ups (VRPDP) and their mutual combinations. Genetic algorithms are a search method used to find suboptimal solutions of complicated combinatorial problems including vehicle routing. Genetic algorithm (GVR) is quite universal due to the two-level representation of the problem - without major modifications it enables successful solving of CVRP, VRP-TW and possibly also other variants of the problem. GVR enables also fast search for new solutions - operators of crossover and mutations provide solutions whose adjustment is not time demanding, and quality of provided solutions is very good, GVR verified with standard data. Parameters of genetic algorithm can be modified in the program environmen

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JO - Pozemní dopravní systémy a zařízení

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific Papers of the University of Pardubice, Series B, The Jan Perner Transport Faculty

ISSN

1211-6610

e-ISSN

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Svazek periodika

2010

Číslo periodika v rámci svazku

16

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

75-84

Kód UT WoS článku

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EID výsledku v databázi Scopus

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