Four techniques are described which can help a genetic algorithm to locate multiple approximate solutions to a multi-modal optimization problem. These techniques are: fitness sharing, ‘eliminating’ identical solutions, ‘removing’ acceptable solutions from the reproduction cycle and applying heuristics to improve sub-standard solutions. Essentially, all of these techniques operate by encouraging genetic variety in the potential solution set. The preliminary design of a gearbox is presented as an example to illustrate the effectiveness of the proposed techniques.
Optimization of Multi-Modal Discrete Functions Using Genetic Algorithms
1993-01-01
7 pages
Article (Journal)
Electronic Resource
English
Optimization of multi-modal discrete functions using genetic algorithms
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