Guided randomness in optimization

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The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

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Title Statements

Full title :Guided randomness in optimization / Maurice Clerc.

Summary

Edition Statements

Publication Date:2015.

Publication Statements

Publisher(s):ISTE Ltd, Wiley
Place of Publication:London
Language:eng
Publication Date:2015.

The Physical Object

Description:1 online resource (320)

Edition Identifiers

ISBN:9781119136439, 1119136431, 111913644X, 9781119136446, 9781848218055, 1848218052, 9781119136453, 1119136458
oclc:ocn909857365
LC Classification:QA76.9.A43
Dewey Decimal:006.3

Cover -- Title Page -- Copyright -- Contents -- Preface -- About this book -- Organization of the book -- Tools -- Key points -- Contact the author -- Introduction -- PART 1: Randomness in Optimization -- 1: Necessary Risk -- 1.1. No better than random search -- 1.1.1. Uniform random search -- 1.1.2. Sequential search -- 1.1.3. Partial gradient -- 1.2. Better or worse than random search -- 1.2.1. Positive correlation problems -- 1.2.2. Negative correlation problems -- 2: Random Number Generators (RNGs) -- 2.1. Generator types -- 2.2. True randomness -- 2.3. Simulated randomness -- 2.3.1. KISS -- 2.3.2. Mersenne-Twister -- 2.4. Simplified randomness -- 2.4.1. Linear congruential generators -- 2.4.2. Additive -- 2.4.3. Multiplicative -- 2.5. Guided randomness -- 2.5.1. Gaussian -- 2.5.2. Bell -- 2.5.3. Cauchy -- 2.5.4. Lévy -- 2.5.5. Log-normal -- 2.5.6. Composite distributions -- 3: The Effects of Randomness -- 3.1. Initialization -- 3.1.1. Uniform randomness -- 3.1.2. Low divergence -- 3.1.3. No Man's Land techniques -- 3.2. Movement -- 3.3. Distribution of the Next Possible Positions (DNPP) -- 3.4. Confinement, constraints and repairs -- 3.4.1. Strict confinement -- 3.4.2. Random…