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APPLYING THE GENETIC ALGORITHMS OF SORTING THE ELITIST NON-DECISIVE SOLUTIONS IN THE CASE STUDY "RESOURCE ALLOCATION"

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Author(s): Khashayar Teimoori

Journal: International Journal of Advances in Engineering and Technology
ISSN 2231-1963

Volume: 3;
Issue: 1;
Start page: 300;
Date: 2012;
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Keywords: Energy Policy | Multi-Objective Purpose Optimization | Genetic Algorithms | Resource Allocation.

ABSTRACT
To achieve the purposes of the permanent development, a good energy Policy should take into account the various range of the political, economical, social and environmental considerations. On the other hand, the energy resources and technologies at hand are limited. Due to the complexity of the elements affecting the decision-making process, the usage of modelling methods in the energy sector has major importance. Unfortunately, the old methodologies of the energy systems Modelling are not suitable for multi-objective purposes, and they don’t have the capability to lead the systems to the desirable optimum point. Given the development of multi-objective evolutionary algorithms and the increasing usage of them in engineering problem solving, the motivation for this research in optimizing energy systems based on multi-objective purposes, have been inconsistent and not co-scaled. In this paper, using genetic algorithms of sorting the elitist non-decisive solutions, the resource allocation was considered as a sample, which was modulated and analyzes. The present study shows that applying post-research decision-making methods based on multi-objective optimization, besides developing the possibility of analyzing the balance multi-objective, inconsistent and non-co-scaled purposes in energy systems, will also increase the power of policy-maker and politicians in predicting and improving the results from different decisions and support them in making better decisions. Applying other new optimizing methods in analyzing energy systems is recommended.

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Tangokurs Rapperswil-Jona

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