عنوان
پدید آورنده
موضوع
رده
TJ163.2
TJ163
.
2
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
1523117184
(Number (ISBN
1785615475
(Number (ISBN
9781523117185
(Number (ISBN
9781785615474
Erroneous ISBN
1785615467
Erroneous ISBN
9781785615467
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Metaheuristic optimization in power engineering /
General Material Designation
[Book]
First Statement of Responsibility
Jordan Radosavljević.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
London, United Kingdom :
Name of Publisher, Distributor, etc.
The Institution of Engineering and Technology,
Date of Publication, Distribution, etc.
2018.
Date of Publication, Distribution, etc.
©2018
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xiv, 517 pages) :
Other Physical Details
illustrations
SERIES
Series Title
IET energy engineering series ;
Volume Designation
131
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references (pages 502-504) and index.
CONTENTS NOTE
Text of Note
Intro; Contents; Preface; Acknowledgements; Supplementary files; 1. Overview of metaheuristic optimization; 1.1 Introduction; 1.2 Description of metaheuristics; 1.3 Principle of population-based metaheuristics; 1.3.1 Genetic algorithm; 1.3.2 Differential evolution; 1.3.3 Evolutionary programing; 1.3.4 Backtracking search optimization algorithm; 1.3.5 Particle swarm optimization; 1.3.6 Ant colony optimization; 1.3.7 Artificial bee colony; 1.3.8 Gravitational search algorithm; 1.3.9 Wind-driven optimization; 1.3.10 Colliding bodies optimization; 1.3.11 Black hole algorithm.
Text of Note
1.3.12 Gray wolf optimizer1.3.13 Firefly algorithm; 1.3.14 Cuckoo search algorithm; 1.3.15 Moth swarm algorithm; 1.3.16 Krill herd algorithm; 1.3.17 Shuffled frog-leaping algorithm; 1.3.18 Bacterial colony foraging optimization; 1.3.19 Biogeography-based optimization; 1.3.20 Teaching-learning-based optimization; 1.3.21 League championship algorithm; 1.3.22 Mine blast algorithm; 1.3.23 Sine cosine algorithm; 1.3.24 Harmony search; 1.3.25 Imperialist competitive algorithm; 1.3.26 Differential search algorithm; 1.3.27 Glowworm swarm optimization; 1.3.28 Spiral optimization algorithm.
Text of Note
1.3.29 The Jaya algorithm1.3.30 Creating a ''new'' algorithm; 1.4 Criticism of metaheuristics; 1.5 Educational software-metahopt; 1.6 Conclusion; References; 2. Overview of genetic algorithms; 2.1 Introduction; 2.2 Basic structure of the GA; 2.3 Representation of individuals (encoding); 2.3.1 Binary encoding; 2.3.2 Gray coding; 2.3.3 Real-value encoding; 2.4 Population size and initial population; 2.5 Fitness function; 2.5.1 Relative fitness; 2.5.2 Linear scaling; 2.6 Selection; 2.6.1 Simple selection; 2.6.2 Stochastic universal sampling; 2.6.3 Linear ranking selection.
Text of Note
2.11.5 Optimal placement and sizing of distributed generation in distribution networks2.11.6 Optimal energy and operation management of microgrids; 2.11.7 Optimal coordination of directional overcurrent relays; 2.11.8 Steady-state analysis of self-excited induction generator; 2.12 Conclusion; References; 3. Overview of particle swarm optimization; 3.1 Introduction; 3.2 Description of PSO; 3.2.1 Parameters of PSO; 3.2.2 General remarks about PSO; 3.2.3 MATLAB code of PSO; 3.2.4 Example usage of PSO; 3.3 PSO modifications; 3.3.1 Population topology; 3.3.2 Discrete binary PSO; 3.3.3 Hybrid PSO.
Text of Note
2.6.4 Elitist selection2.6.5 k-Tournament selection schemes; 2.6.6 Simple tournament selection; 2.7 Crossover; 2.7.1 One-point crossover; 2.7.2 Multipoint crossover; 2.7.3 Uniform crossover; 2.7.4 Shuffle crossover; 2.7.5 Arithmetic crossover; 2.7.6 Heuristic crossover; 2.8 Mutation; 2.9 GA control parameters; 2.10 Multiobjective optimization using GA; 2.11 Applications of GA to power system problems-literature overview; 2.11.1 Optimal power flow; 2.11.2 Optimal reactive power dispatch; 2.11.3 Combined economic and emission dispatch; 2.11.4 Optimal power flow in distribution networks.
Text of Note
3.3.4 Adaptive PSO.
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SUMMARY OR ABSTRACT
Text of Note
This book describes the principles of solving various problems in power engineering via the application of selected metaheuristic optimization methods including genetic algorithms, particle swarm optimization, and the gravitational search algorithm.
OTHER EDITION IN ANOTHER MEDIUM
Title
Metaheuristic optimization in power engineering.
International Standard Book Number
1785615467
TOPICAL NAME USED AS SUBJECT
Energy industries-- Mathematical models.
Engineering mathematics.
Mathematical optimization.
Power resources-- Mathematical models.
Energy industries-- Mathematical models.
Engineering mathematics.
Mathematical optimization.
optimisation.
Power resources-- Mathematical models.
power systems.
TECHNOLOGY & ENGINEERING-- Mechanical.
(SUBJECT CATEGORY (Provisional
B0100
B0260
B8110
TEC-- 009070
DEWEY DECIMAL CLASSIFICATION
Number
621
.
042015196
LIBRARY OF CONGRESS CLASSIFICATION
Class number
TJ163
.
2
PERSONAL NAME - PRIMARY RESPONSIBILITY
Radosavljević, Jordan
ORIGINATING SOURCE
Date of Transaction
20200823042010.0
Cataloguing Rules (Descriptive Conventions))
pn
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب [Book]
Y
