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A novel approach to route selection in car navigation systems by a multiobjective genetic algorithm

Authors:

Feng Wen,

Xiaohao Gao,

Mitsuo GenAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 767 - 768

https://doi.org/10.1145/1389095.1389246

Published: 12 July 2008 Publication History

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Abstract

This paper considers the multicriteria route selection problem (mRSP) for car navigation systems in traffic road network. A multi-layer hierarchy network method is proposed to substantially reduce the computation time when solving mRSP. We also propose a new multiobjective Genetic Algorithm (moGA) named distance-based nondominated sorting Genetic Algorithm (dnsGA) to generate evolutionary results for mRSP. It attains better convergence to the Pareto-optimal front and gives sufficient emphasis to the diversity consideration. The experiment results showed the effectiveness and the efficiency of our approach.

References

[1]

Gen, M. and Cheng, R., 2000. Genetic Algorithms and Engineering Optimization. Wiley, New York.

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[2]

Gen, M., Cheng, R. and Oren, S.S., 2001. Network Design Techniques using Adapted Genetic Algorithms. Advances in Engineering Software 32 (9), 731--744.

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A novel approach to route selection in car navigation systems by a multiobjective genetic algorithm
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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Published In

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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Association for Computing Machinery

New York, NY, United States

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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A fast Pareto genetic algorithm approach for solving expensive multiobjective optimization problems

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