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001432164 001__ 1432164
001432164 003__ OCoLC
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001432164 019__ $$a1199127640$$a1225354336$$a1226590496
001432164 020__ $$a9783030581008$$q(electronic book)
001432164 020__ $$a3030581004$$q(electronic book)
001432164 020__ $$z3030580997
001432164 020__ $$z9783030580995
001432164 0247_ $$a10.1007/978-3-030-58100-8$$2doi
001432164 035__ $$aSP(OCoLC)1202464127
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001432164 049__ $$aISEA
001432164 050_4 $$aQA76.9.A43$$bC84 2021
001432164 08204 $$a005.1$$223
001432164 1001_ $$aCuevas, Erik,$$eauthor.
001432164 24510 $$aMetaheuristic computation /$$cErik Cuevas, Primitivo Diaz, Octavio Camarena.
001432164 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2021]
001432164 300__ $$a1 online resource (281 pages)
001432164 336__ $$atext$$btxt$$2rdacontent
001432164 337__ $$acomputer$$bc$$2rdamedia
001432164 338__ $$aonline resource$$bcr$$2rdacarrier
001432164 4901_ $$aIntelligent Systems Reference Library ;$$vvolume195
001432164 504__ $$aIncludes bibliographical references.
001432164 5050_ $$aIntro -- Preface -- Contents -- 1 Introductory Concepts of Metaheuristic Computation -- 1.1 Formulation of an Optimization Problem -- 1.2 Classical Optimization Methods -- 1.3 Metaheuristic Computation Schemes -- 1.3.1 Generic Structure of a Metaheuristic Method -- References -- 2 An Enhanced Swarm Method Based on the Locust Search Algorithm -- 2.1 Introduction -- 2.2 The Locust Search Algorithm -- 2.2.1 LS Solitary Phase -- 2.2.2 LS Social Phase -- 2.3 The LS-II Algorithm -- 2.3.1 Selecting Between Solitary and Social Phases -- 2.3.2 Modified Social Phase Operator
001432164 5058_ $$a2.4 Experiments and Results -- 2.4.1 Benchmark Test Functions -- 2.4.2 Engineering Optimization Problems -- 2.5 Conclusions -- Appendix A -- Appendix B -- B2.1 Pressure Vessel Design Problem -- B2.2 Gear Train Design Problem -- B2.3 Tension/Compression Spring Design Problem -- B2.4 Three-Bar Truss Design Problem -- B2.5 Welded Beam Design Problem -- B2.6. Parameter Estimation for FM Synthesizers -- B2.7 Optimal Capacitor Placement for the IEEE's 69-Bus Radial Distribution Networks -- References -- 3 A Metaheuristic Methodology Based on Fuzzy Logic Principles -- 3.1 Introduction
001432164 5058_ $$a3.2 Fuzzy Logic and Reasoning Models -- 3.2.1 Fuzzy Logic Concepts -- 3.2.2 The Takagi-Sugeno (TS) Fuzzy Model -- 3.3 The Proposed Methodology -- 3.3.1 Optimization Strategy -- 3.3.2 Computational Procedure -- 3.4 Discussion About the Proposed Methodology -- 3.4.1 Optimization Algorithm -- 3.4.2 Modeling Characteristics -- 3.5 Experimental Study -- 3.5.1 Performance Evaluation with Regard to Its Own Tuning Parameters -- 3.5.2 Comparison with Other Optimization Approaches -- 3.6 Conclusions -- Appendix A. List of Benchmark Functions -- References
001432164 5058_ $$a4 A Metaheuristic Computation Scheme to Solve Energy Problems -- 4.1 Introduction -- 4.2 Crow Search Algorithm (CSA) -- 4.3 The Proposed Improved Crow Search Algorithm (ICSA) -- 4.3.1 Dynamic Awareness Probability (DAP) -- 4.3.2 Random Movement-Lévy Flight -- 4.4 Motor Parameter Estimation Formulation -- 4.4.1 Approximate Circuit Model -- 4.4.2 Exact Circuit Model -- 4.5 Capacitor Allocation Problem Formulation -- 4.5.1 Load Flow Analysis -- 4.5.2 Mathematical Approach -- 4.5.3 Sensitivity Analysis and Loss Sensitivity Factor -- 4.6 Experiments -- 4.6.1 Motor Parameter Estimation Test
001432164 5058_ $$a4.6.2 Capacitor Allocation Test -- 4.7 Conclusions -- Appendix A: Systems Data -- References -- 5 ANFIS-Hammerstein Model for Nonlinear Systems Identification Using GSA -- 5.1 Introduction -- 5.2 Background -- 5.2.1 Hybrid ANFIS Models -- 5.2.2 Adaptive Neuro-Fuzzy Inference System (ANFIS) -- 5.2.3 Gravitational Search Algorithm (GSA) -- 5.3 Hammerstein Model Identification by Using GSA -- 5.4 Experimental Study -- 5.4.1 Experiment I -- 5.4.2 Experiment II -- 5.4.3 Experiment III -- 5.4.4 Experiment IV -- 5.4.5 Experiment V -- 5.4.6 Experiment VI -- 5.4.7 Experiment VII
001432164 506__ $$aAccess limited to authorized users.
001432164 520__ $$aThis book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.
001432164 588__ $$aOnline resource; title from digital title page (viewed on December 11, 2020).
001432164 650_0 $$aMetaheuristics.
001432164 650_6 $$aMétaheuristiques.
001432164 655_0 $$aElectronic books.
001432164 7001_ $$aDiaz, Primitivo,$$eauthor.
001432164 7001_ $$aCamarena, Octavio,$$eauthor.
001432164 77608 $$iPrint version:$$aCuevas, Erik.$$tMetaheuristic Computation: a Performance Perspective.$$dCham : Springer International Publishing AG, ©2020$$z9783030580995
001432164 830_0 $$aIntelligent systems reference library ;$$vv. 195.
001432164 852__ $$bebk
001432164 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-58100-8$$zOnline Access$$91397441.1
001432164 909CO $$ooai:library.usi.edu:1432164$$pGLOBAL_SET
001432164 980__ $$aBIB
001432164 980__ $$aEBOOK
001432164 982__ $$aEbook
001432164 983__ $$aOnline
001432164 994__ $$a92$$bISE