Torregosa, Ribelito F. creator Worsak Kanok-Nukulchai Chairperson Gupta, Satyendra P. Examination committee Pennung Warnitchai Examination Committee Wijeyewickrema, Anil C. Examination committee Royal Thai Government (King's scholarship) Scholarship donor text th Bangkok Asian Institute of Technology 1998 monographic eng

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50, A4, B35, C3, D3 leaves Genetic algorithm (GA) is a new technique in optimization procedure that works best in design problems with discrete variables. It employs the survival of the fittest philosophy in determining the optimum combination. Genetic algorithm program was developed using Fortran Programming Language. Test was conducted in order to determine the reliability of the program by optimizing a beam using both exact and GA. Genetic algorithm were used to optimize plane frames under different load cases. Database of steel sizes was provided as the discrete variables. Three different search procedures were tested in the study. These are the elitist without mutation, non-elitist and elitist with mutation search. Different crossover types, population sizes, and crossover probabilities were used and the best method was determined. To examine the performance of genetic algorithms, case studies were conducted and the results obtained were compared with the results from other optimization techniques reported by other authors to some engineering journals. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Civil Engineering Thesis (M.Eng.) - Asian Institute of Technology, 1998 Genetic algorithms Structural frames Mathematical models Asian Institute of Technology. http://203.159.5.9/ait-thesis/detail.php?q=B13146 http://203.159.5.9/ait-thesis/detail.php?q=B13146 010998 20260818170836.0