Structural Optimization by Genetic Algorithms with Tournament Selection

A new approach to optimization design concerning the configurations of structures using genetic algorithm (GA) with a tournament selection strategy has been proposed. The tournament selection strategy is used as a replacement for the commonly used fitness-proportional selection strategy to drive the GA so as to improve the fitness of each succeeding generation more efficiently. Numerical results for three examples reveal that a significant reduction of computation cost has been achieved in the newly proposed GA with tournament selection, as compared to the widely used GA with fitness-proportional selection and other hybrid GA approaches. Also, it has verified that the tournament selection performs well over the fitness-proportional selection and other hybrid techniques in enhancing GA search efficiency.

[1]  W. M. Jenkins,et al.  PLANE FRAME OPTIMUM DESIGN ENVIRONMENT BASED ON GENETIC ALGORITHM , 1992 .

[2]  D. Grierson,et al.  Optimal sizing, geometrical and topological design using a genetic algorithm , 1993 .

[3]  Chee Kiong Soh,et al.  Fuzzy Controlled Genetic Algorithm Search for Shape Optimization , 1996 .

[4]  V. K. Koumousis,et al.  Genetic Algorithms in Discrete Optimization of Steel Truss Roofs , 1994 .

[5]  P. Hajela Genetic search - An approach to the nonconvex optimization problem , 1990 .

[6]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[7]  Kalyanmoy Deb,et al.  Optimal design of a welded beam via genetic algorithms , 1991 .

[8]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[9]  H. Adeli,et al.  Integrated Genetic Algorithm for Optimization of Space Structures , 1993 .

[10]  Nostrand Reinhold,et al.  the utility of using the genetic algorithm approach on the problem of Davis, L. (1991), Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York. , 1991 .

[11]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[12]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[13]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[14]  P. Hajela,et al.  GENETIC ALGORITHMS IN OPTIMIZATION PROBLEMS WITH DISCRETE AND INTEGER DESIGN VARIABLES , 1992 .

[15]  Dirk Thierens,et al.  Convergence Models of Genetic Algorithm Selection Schemes , 1994, PPSN.

[16]  Kazuhiro Saitou,et al.  Genetic algorithms as an approach to configuration and topology design , 1994, DAC 1993.

[17]  W. M. Jenkins,et al.  Towards structural optimization via the genetic algorithm , 1991 .

[18]  S. Wu,et al.  Steady-state genetic algorithms for discrete optimization of trusses , 1995 .

[19]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[20]  S. Rajeev,et al.  Discrete Optimization of Structures Using Genetic Algorithms , 1992 .

[21]  James E. Baker,et al.  Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[22]  H. Adeli,et al.  Augmented Lagrangian genetic algorithm for structural optimization , 1994 .

[23]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[24]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .