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Probability simulation optimization approach using orthogonal genetic algorithm

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Wuhan University Journal of Natural Sciences

Abstract

In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach synthesizes the computer simulation technology, orthogonal genetic algorithm and statistical test method faultlessly, which can solve complex optimization problem effectively. In this paper, the author gives the correlative conception of probability simulation optimization and describes the probability simulation optimization approach using orthogonal genetic algorithm in detail. Theoretically speaking, it has a strong rationality and maneuverability that can apply probability method in solving the complex optimization problems with uncertain phenomenon. In demonstration, the optimization performance of this method is better than other traditional methods. Simulation result suggests that the approach referred to this paper is feasible, correct and valid.

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Authors and Affiliations

  1. Engineering and Technology Center, Southwest University of Science and Technology, 621010, Mianyang, Sichuan, China

    Wang Yinling & Yan Shiliang

  2. School of Information System and Management, National University of Defense Technology, 410073, Changsha, Human, China

    Xing Lining

Authors
  1. Wang Yinling
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  2. Xing Lining
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  3. Yan Shiliang
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Corresponding author

Correspondence to Wang Yinling.

Additional information

Foundation item: Supported by the National Natural Science Foundation of China (70272002).

Biography: WANG Yinling (1979-), female, Lecturer, research direction: automation and artificial intelligence.

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Yinling, W., Lining, X. & Shiliang, Y. Probability simulation optimization approach using orthogonal genetic algorithm. Wuhan Univ. J. Nat. Sci. 11, 1481–1484 (2006). https://doi.org/10.1007/BF02831802

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  • DOI: https://doi.org/10.1007/BF02831802

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