Article ID Journal Published Year Pages File Type
1109232 Procedia - Social and Behavioral Sciences 2015 7 Pages PDF
Abstract

Genetic algorithms are optimizing algorithms, inspired by natural evolution. Investigations on genetic algorithms reveal that these algorithms are different from other search-based optimizing methods. In most optimizing techniques based on a point, the analysis is done according to only some of the decision-making regulations. These techniques could yield an incorrect answer in the searching spaces having several maximum points. In other words, it is possible that the local maximum point be obtained as the answer. Hence, genetic algorithms could also be used in mathematical programming. The common techniques utilized in this field are not effective since they need a series of limitations such as functions continuity and differentiation to be optimized. Moreover, there is no originality in these techniques and this is why the genetic algorithm method could be used in these cases, especially for non-linear programing to reach desirable outcomes.

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Social Sciences and Humanities Arts and Humanities Arts and Humanities (General)