An Improved Nested Partitions Algorithm Based on Simulated Annealing in Complex Decision Problem Optimization

  • Authors:
  • Yan Luo;Changrui Yu

  • Affiliations:
  • Institute of System Engineering, Shanghai Jiao Tong University, 200052 Shanghai, China;School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China

  • Venue:
  • ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
  • Year:
  • 2009

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Abstract

This paper introduces the main ideas of the nested partitions (NP) method, analyses its efficiency theoretically and proposes the way to improve the optimization efficiency of the algorithm. Then the paper introduces the simulated annealing (SA) algorithm and incorporates the ideas of SA into two of the arithmetic operators of NP algorithm to form the combined NP/SA algorithm. Moreover, the paper presents the explicit optimization procedure of the combined algorithm NP/SA and explains the feasibility and superiority of it. The NP/SA algorithm adopts the global optimization ability of NP algorithm and the local search ability of SA algorithm so that it improves the optimization efficiency and the convergence rate. This paper also illustrates the NP/SA algorithm through an optimization example.