Genetic Algorithm for Shortest Path Routing Problem

Authors

  • Charmy Pujara Department of Electronics and Communication, Atmiya Institute of Technology and Science, Rajkot, Gujrat, India
  • AM Kothari Department of Electronics and Communication, Atmiya Institute of Technology and Science, Rajkot, Gujrat, India

DOI:

https://doi.org/10.37591/rrdms.v2i3.578

Keywords:

Shortest path, genetic algorithm, crossover

Abstract

This review paper presents a genetic algorithm approach to the shortest path routing problem. Its variable length chromosomes (string) and their genes (parameters) have been used for encoding the problem. The crossover operation exchanges partial routes.

Cite this Article
Pujara Charmy, Kothari AM. Genetic algorithm for shortest path routing problem. Research & Reviews: Discrete Mathematical Structures. 2015; 2(3): 36–39p.

References

Cherkassky Boris V, Goldberg Andrew V, Radzik Tomasz. Shortest paths algorithms: theory and experimental evaluation. Mathematical Programming.1996; 73 (2): 129–174p. doi:10.1016/0025-5610(95)00021-6.MR 1392160. 2. Thorup Mikkel. Undirected single-source shortest paths with positive integer weights in linear time. Journal of the ACM (JACM). 1999; 46 (3): 362–394p. 3. Schrijver Alexander. Combinatorial Optimization—Polyhedra and Efficiency. Algorithms and Combinatorics. 24. Springer. ISBN 3-540-20456-3. 2004; A(7): 103p. 4. Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms. 2002:267–276p. 5. Theoretical Computer Science. 2004; 312:47–74p. 6. Proceedings of the 27th International Colloquium on Automata, Languages and Programming. 2000:61–72p. 7. Peter Sanders. Fast route planning. Google Tech Talk. 2009. 8. Chen Danny Z .Developing algorithms and software for geometric path planning problems. ACM Computing Surveys. 1996; 28 (4es): 18. DOI:10.1145/242224.242246.

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Published

2015-12-17

Issue

Vol. 2 No. 3 (2015)

Section

Review Articles

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