The parametric design based on organizational evolutionary algorithm

  • Authors:

  • Cao Chunhong;Zhang Bin;Wang Limin;Li Wenhui

  • Affiliations:

  • College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China;College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China;College of Computer Science and Technology, Jilin University, Changchun, P.R. China;College of Computer Science and Technology, Jilin University, Changchun, P.R. China

  • Venue:
  • PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
  • Year:
  • 2006

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Abstract

Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. In this paper we propose a new optimization algorithm--organizational evolutionary algorithm (OEA) and apply it into the geometric constraint solving. In OEA the colony is composed of the organizations. Three organizational evolutionary operators--split operator, merging operator and coordinating operator can lead the colony to evolve. These three kinds of operators have different functions in the algorithm. Split operator limits the scale of the organization, and makes sure a part of organization come into next generation directly, which maintains the variety of the generation. Merging operator makes use of the leader's information fully and acts as a local searching function. Cooperating operator increases the degree of adaptability between the two organizations by the interactions. The experiment shows that OEA has good capability in the geometric constraint solving.