文档介绍：1
Introduction to GA
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Synopsis
Synopsis
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2
3
5
Conclusion
Applications and prospects
Mathematics behind
Start from here: SGA
What is GA
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What is GA?
What is GA
GA is the abbreviation of ic Algorithm,
which is a search heuristic that mimics the process
of natural evolution.
Definition:
Generally, GA is used to solve search and optimization problem.
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Information
Intelligence
Idea
1단계(정보수집)
2단계(정보조합)
3단계(정보활용)
Information는가장원시적정보상태
Information들을조합하거나
분석하여보다가치있는정보를생성
Intelligence들을활용하여
대안이나아이디어도출
Basic concepts of SGA
Start from here: SGA
SGA: simplest ic algorithm
A typical ic algorithm requires:
A ic representation of the solution domain
A fitness function to evaluate the solution domain
Simplest operations in ic algorithm:
Selection (with selection operators)
Crossover (with crossover operators)
Mutation (with mutation operators)
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Information
Intelligence
Idea
1단계(정보수집)
2단계(정보조합)
3단계(정보활용)
Information는가장원시적정보상태
Information들을조합하거나
분석하여보다가치있는정보를생성
Intelligence들을활용하여
대안이나아이디어도출
A typical process of SGA
Start from here: SGA
Encode the possible solution domain
Decide the fitness function
Create initial population
Evaluate the fitness of each gene
No
Select the gene with higher fitness
Crossover the selected gene
Mutate a small fraction of the gene
Replace the old population of with the new
Stop?
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Information
Intelligence
Idea
1단계(정보수집)
2단계(정보조합)
3단계(정보활용)
Information는가장원시적정보상태
Information들을조합하거나
분석하여보다가치있는정보를생성
Intelligence들을활용하여
대안이나아이디어도출
An example
Start from here: SGA
7
Information
Intelligence
Idea
1단계(정보수집)
2단계(정보조합)
3단계(정보활용)
Information는가장원시적정보상태
Information들을조합하거나
분석하여보다가치있는정보를생성
Intelligence들을활용하여
대안이나아이디어도출
Advantages
Start from here: SGA
GA starts the solution domain from a series of possible solutions, which performs better than traditional searching process.
GA uses stochastic method to search the solution domain. No deep understanding of the problem is needed to provid