An Evolutionary Programming to Solve Constrained Optimization Problems

Dong Hongbin; Huang Houkuan; He Jun; Hou Wei

Journal of Computer Research and Development > 2006 > 43(5): 841-850.

Dong Hongbin, Huang Houkuan, He Jun, Hou Wei. An Evolutionary Programming to Solve Constrained Optimization Problems[J]. Journal of Computer Research and Development, 2006, 43(5): 841-850.

Citation:

Dong Hongbin, Huang Houkuan, He Jun, Hou Wei. An Evolutionary Programming to Solve Constrained Optimization Problems[J]. Journal of Computer Research and Development, 2006, 43(5): 841-850.

Citation:

Dong Hongbin, Huang Houkuan, He Jun, Hou Wei. An Evolutionary Programming to Solve Constrained Optimization Problems[J]. Journal of Computer Research and Development, 2006, 43(5): 841-850.

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An Evolutionary Programming to Solve Constrained Optimization Problems

1(School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044) 2(Department of Computer Science, Harbin Normal University, Harbin 150080) 3(Department of Computer Science, Northeast Agricultural University, Harbin 150030)

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Published Date: May 14, 2006

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Abstract

Abstract

A mixed strategies evolutionary programming to solve constrained optimization problems is presented in this paper. The approach does not require the use of a penalty function. Instead, it uses a diversity conservation mechanism based on allowing infeasible solutions to remain in the population. A mixed mutation strategy and feasibility-based comparison mechanism is used to guide the process fast toward the feasible region of the search space. This new evolutionary programming has been tested on 13 benchmark functions. The results obtained show that the new approach is a general and effective method.
- constrained optimization,
- mixed strategy,
- diversity conservation mechanism,
- evolutionary programming

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