Establishment of genetic algorithm fitness function \=in reliability-based structural optimization
Received:March 20, 2006  
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DOI:10.7511/jslx20091019
KeyWord:reliability-based structural optimization(RBSO)  genetic algorithm(GA)  constraint  exterior penalty function method  multiplier method
     
AuthorInstitution
严心池 江南大学 环境与土木工程学院,无锡
华渊 江南大学 环境与土木工程学院,无锡
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Abstract:
      The Reliability-based Structural Optimization (RBSO) in this paper includes system reliability index constraints, but it is difficult for genetic algorithm (GA) to solve the optimization issue with constraint, so in this process, how to handle the constraint become sixty-four-dollar question of establishing the fitness function and circulating this algorithm. Based on exterior penalty function method, mathematic model is made, penalty gene is get adaptively according to population’s evolution, and mapping formula of objective function and constraint transformed fitness function is established. Subsequently laxity variable is introduced in primary mathematic model, based on Lagrange multiplier method, a new fitness function mapping formula is made, this method can avoid penalty function morbidity by means of adding a Lagrange multiplier, and has a more quick and stable convergence, genetic algorithm for numerical optimization for constrained problem is successfully solved. The calculation shows that the two equations’ are reasonable, and the multiplier method has better convergence capability.