Genetic Algorithms for Function Optimization and Scheduling
Contents
Information Processing Based on Natural Metaphor
Genetic Algorithms (GAs)
Genotype and Phenotype
Chromosomes Representation in GAs
Basic Flow of Genetic Algorithms
Crossover
Crossover (Binary string)
Crossover (Order string)
Crossover (OX)
Crossover for Real Value Representation
Mutation
Mutation (Binary string)
Inversion
Selection (Proportional Selection)
Other Selection Techniques
Schema Theorem
Applications of Genetic Algorithms
Design of GA
Basic GA Parameters
Parameters of GAUSS (GA Package by Tsutsui)
Function Optimization
Demonstration of Function Optimization
Scheduling Problems
Traveling Salesman Problem
Introduction to our Research
Forking GA
GAs with Robust Solution Searching Scheme
Study on Multi-parent Recombination
Ladder Climbing GAs
Related Techniques
Research Activities
GAs Research Sources
GAs Research Sources(J)
GAs Research Sources(P)
GAs Research Sources(B)
GAs Research Sources(W)
The END
e-mail : tsutsui@hannan-u.ac.jp
ﾎｰﾑ ﾍﾟｰｼﾞ : http://www.hannan-u.ac.jp/~tsutsui/reserch-e.html