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Mathematical Optimization Techniques

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Modern Optimization Techniques with Applications in Electric Power Systems

Part of the book series: Energy Systems ((ENERGY))

Abstract

The objectives of this chapter are: Explaining some optimization techniques. Explaining the minimum norm theorem and how it could be used as an optimization algorithm, where a set of equations can be obtained. Introducing the fuzzy system as an optimization technique. Introducing the simulated annealing algorithm (SAA) as an optimization technique. Introducing the tabu search algorithm (TSA) as an optimization technique. Introducing the genetic algorithm (GA) as an optimization technique. Introducing the particle swarm (PS) as an optimization technique.

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Authors and Affiliations

  1. Department of Electrical Power and Machines, Misr University for Science and Technology, 6th of October City, Egypt

    Soliman Abdel-Hady Soliman

  2. Department of Electrical Power and Machines, Ain Shams University, Cairo, Egypt

    Abdel-Aal Hassan Mantawy

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  1. Soliman Abdel-Hady Soliman
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  2. Abdel-Aal Hassan Mantawy
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Soliman, S.AH., Mantawy, AA.H. (2012). Mathematical Optimization Techniques. In: Modern Optimization Techniques with Applications in Electric Power Systems. Energy Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1752-1_2

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