Solving VRP Using Genetic Algorithm with Time Constraints in Fitness Function

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F13%3A00208774" target="_blank" >RIV/68407700:21260/13:00208774 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Solving VRP Using Genetic Algorithm with Time Constraints in Fitness Function
Original language description
A modern way of solving logistics problems is using some evolutionary techniques such as genetic algorithm. The best known logistic problems are TSP (Traveler Salesman Problem) and VRP (Vehicle Routing Problem). There are many experiments and approacheswhen genetic algorithms are applied to solve these problems. Genetic algorithms use two basic operators: crossover and mutation. Number of variations of crossover operators are known in genetic algorithm and a special ERX (Edge Recombination Crossover) was developed for this problem [1][2][4]. Classical TSP and VRP try to find an optimal solution by minimization of the length of travelling distances. In this paper, the fitness function contains time constrain as a criterion except of travelling distance. The fitness function is multidimensional and the lexicographical order is defined. Experiments showed that it is very useful to change the priorities of parts of fitness, especially when time constrain is not performable. This paper is
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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