Research On Considering Effect Of Recessive Inheritance Genetic Algorithms In Structural Optimization

Genetic Algorithms is a global search algorithm based on natural selection ofevolutionism and genetic transmission mechanism of genetics. Dominant inheritanceand recessive inheritance widely exist the evolution of biology. This paper presents anew Genetic Algorithms named Considering effect of Recessive inheritance GeneticAlgorithms, which simulates dominant inheritance and recessive inheritance of theevolution of biology, by the way of introducing the dominant fitness function andrecessive fitness function into Genetic Algorithms. This paper presents the fundamental conception of Considering effect ofRecessive inheritance Genetic Algorithms completely. The flow chart and someessential ingredients including genotype, dominant fitness function, recessive fitnessfunction, selection, crossover and mutation are given in this paper. Some problemsabout the design of algorithm and analysis in theory are discussed in this paper. Considering effect of Recessive inheritance Genetic Algorithms is used to solveconstrained optimization in this paper. Afterward, it is used to solve constrainedoptimization in structural optimization. In chapter 6, this paper integrates thecharacteristic of structural engineering (including engineering experience,traditionaloptimization algorithm etc.) into Genetic Algorithms, which can improve theperformance of algorithm. This paper gives dominant fitness function, recessivefitness function, infeasible region near feasible region F, the process of solvingconstrained optimization and the conversion from engineering experience andtraditional optimization algorithm to recessive fitness function, in accord withdifferent problems. Some analysis in theory is discussed in this paper. Some numerical experiments are performed to compare the performance ofSimple Genetic Algorithms with that of the Considering effect of Recessiveinheritance Genetic Algorithms. According to results of the numerical experiments, itcan be proved that the performance of Considering effect of Recessive inheritanceGenetic Algorithms is better than that of Simple Genetic Algorithms on constrained II摘要optimization and on constrained optimization in structural optimization. Accordingto results of the numerical experiments, it can also be proved that integrating thecharacteristic of structural engineering into Considering effect of Recessiveinheritance Genetic Algorithms can improve the performance of GeneticAlgorithms indeed.