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| A μ-AEA Constraint Optimization Algorithm Based on AEA |
| WANG Zhen,LI Shao-Jun |
Key Laboratory of Advanced Control and Optimization for Chemical Processes,Ministry of Education,
East China University of Science and Technology,Shanghai 200237 |
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Abstract A constrained handling method based on the Alopex-based evolutionary algorithm(AEA) is proposed. The relatively feasible region is gradually converged to the feasible region by the introducing adaptive relaxation parameter μ in the iteration,which takes into account that different functions have different sizes of feasible regions. Also the relaxation of constraints allows more infeasible individuals which contain some useful information to keep staying in the next generation. And therefore it enhances search ability of the algorithm. At the same time,an adaptive penalty function method is introduced,and it adaptively adjusts the penalty coefficient based on the different constraint satisfactions. Thus,it ensures that the punishment is not too large or too small. 11 standard test function experiments show that the proposed method has satisfactory results and great potential in handling works with constraint optimization problems.
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Received: 23 July 2012
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2013, Vol. 26 
