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Evolutionary Methods Of Optimization | Open Access Journals
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Global Journal of Technology and Optimization

ISSN: 2229-8711

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Evolutionary Methods Of Optimization

Optimisation is an activity not part of any specific discipline and is used extensively in virtually every field of science, engineering and commerce. Dictionary Chambers describes optimisation as an act for 'making the most or the best of all' theoretically speaking, conducting an optimization function in a problem means finding the solution to the problem most or ideally suited. Studies in mathematical optimisation expend a lot of time attempting to explain the properties of such an optimal solution. On the other hand, engineering or practical optimisation studies thrive in finding a solution that is as similar as possible to such an ideal solution. The job of an evolutionary optimization algorithm is then to avoid the bad solutions in the search space, take hints from good solutions and finally reach near the best solution, similar to the genetic processing in natural systems. The goal in the process of optimisation is to continue from one or only a few random search solutions Space and use the functions and constraints to guide its quest to the feasible area and finally get close to the optimum solution by exploring the smallest possible set of solutions.

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Citations: 664

Global Journal of Technology and Optimization received 664 citations as per Google Scholar report

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