22 Mart 2013 Cuma


The advantages of genetic algorithm includes,

1    Parallelism and liability
2.   Many ways to speed up and improve a GA application as knowledge about problem domain is gained
3.   Solution space is wider
4.   The fitness landscape is complex
5.    Easy to discover global optimum
6.    The problem has multi objective function
7.    Only uses function evaluations.
8     Easily modified for different problems.
9.    Handles noisy functions well.
10.  Handles large, poorly understood search spaces easily
11.  Good for multi-modal problems returns a suite of solutions.
12.  Very robust to difficulties in the evaluation of the objective function. [1]
13.  They require no knowledge or gradient information about the response surface
14.  Discontinuities present on the response surface have little effect on overall optimization performance
15.  They perform very well for large-scale optimization problems
16.  Can be employed for a wide variety of optimization problems [2]
17.  Genetic algorithm is a method which is very easy to understand and it practically does not demand the knowledge of mathematics.[3]

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