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ADVANCED GENETIC ALGORITHMS FOR ENGINEERING OPTIMIZATION
Gen Ashikaga Institute of Technology JAPAN
Comparative Study of Tree Encodings on Spanning Tree Problems 133
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adaptive agents allele applied approach average behavior binary bits bond graph building blocks cell chromosome circuit cluster complexity components constraints convergence cost crossover crossover operator defined distance distribution dynamic encoding environment evaluation evolution evolution strategies evolutionary algorithms Evolutionary Computation evolutionary programming evolved experiments Figure fitness function fitness value fuzzy gene Genetic Algorithms genetic operators genetic programming genotype global global optimum graph heuristic HPGA IEEE implementation individual initial input iterations learning length Machine Learning matrix maximum method modules mutation operator mutation rate neural networks neurons niche nodes objective function obtained offspring optimal solution optimisation optimization problem optimum output paper parameters parents performance population proposed random randomly representation represents rithm rule runs schedule search space selection shown shows simulated annealing simulation solve Steiner tree step strategy string subprograms Table target techniques tion tree variables vector weights