Genetic Algorithm for vehicle routing problem / W.Nurfahizul Ifwah W.Alias, Mohd Shaiful Sharipudin and Shamsunarnie Mohamed Zukri.
The vehicle routing problem (VRP) is the m-Travelling Salesman Problem, where a demand is associated with each city or customer and each vehicle has a certain capacity. Morever.in VRP also the number of vehicles, m, is often considered as a minimization criterion in addition to total travel distance...
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| Main Authors: | , , |
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| Format: | Research Reports |
| Language: | en |
| Published: |
2012
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/42370/1/42370.PDF https://ir.uitm.edu.my/id/eprint/42370/ |
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| Summary: | The vehicle routing problem (VRP) is the m-Travelling Salesman Problem, where a demand is associated with each city or customer and each vehicle has a certain capacity. Morever.in VRP also the number of vehicles, m, is often considered as a minimization criterion in addition to total travel distance. The objective of this research is to present a heuristic method, called Genetic Algorithm (GA), to solve the VRP.
Genetic Algorithms (GA) were developed initially by Holland and his associates at the University of Michigan in the 1960s and 1970s, and the first full, systematic (and mainly theoretical) treatment was contained in Holland’s book Adaptation in Natural and Artificial Systems published in 1975. Goldberg gives an interesting survey of some of the practical work carried out in this era. Among these early applications of GA were those developed by Bagley for a game-playing program, by Rosenberg in simulating biological processes, and by Cavicchio for solving pattern-recognition problems.
In brief, GA is a system developing methods that use the natural principle of a genetic population and involved three main processes that is crossover, mutation and inversion. The GA are adaptive learning heuristic and they are generally referred to in plural, because several versions exist that are adjustments to different problems. They are also robust and effective algorithms that are computationally simple and easy to implement. |
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