Differential evolution, an alternative approach to evolutionary algorithm

Title: Differential evolution, an alternative approach to evolutionary algorithm
Creator: Wong, Kit Po; Dong, Zhaoyang
Relation: Modern Heuristic Optimization Techniques: Theory and Applications to Power Systems p. 171-187
Publisher Link: http://dx.doi.org/10.1002/9780470225868.ch9
Publisher: Wiley-Blackwell Publishing
Resource Type: book chapter
Date: 2008
Description: As a relatively new population-based optimization technique, differential evolution has been attracting increasing attention for a wide variety of engineering applications including power engineering. Unlike the conventional evolutionary algorithms that depend on predefined probability distribution function for mutation process, differential evolution uses the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently, the object vectors’ differences will pass the objective functions topographical information toward the optimization process and therefore provide more efficient global optimization capability. This chapter aims at providing an overview of differential evolution and presenting it as an alternative to evolutionary algorithms.
Subject: evolutionary algorithm; differential evolution; very-large-scale integration design; virtual population-based acceleration techniques; power engineering
Identifier: http://hdl.handle.net/1959.13/1053185
Identifier: uon:15539
Identifier: ISBN:9780471457114
Language: eng

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