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02784nam a22003615i 4500 |
| 001 |
978-3-642-00267-0 |
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20191026052322.0 |
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cr nn 008mamaa |
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100301s2009 gw | s |||| 0|eng d |
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|a 9783642002670
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7 |
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|a 10.1007/978-3-642-00267-0
|2 doi
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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|a Nature-Inspired Algorithms for Optimisation
|c edited by Raymond Chiong.
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| 250 |
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|a 1st ed. 2009.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2009.
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|a XVIII, 516 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Studies in Computational Intelligence,
|v 193
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|a Section I: Introduction -- Why Is Optimization Difficult? -- The Rationale Behind Seeking Inspiration from Nature -- Section II: Evolutionary Intelligence -- The Evolutionary-Gradient-Search Procedure in Theory and Practice -- The Evolutionary Transition Algorithm: Evolving Complex Solutions Out of Simpler Ones -- A Model-Assisted Memetic Algorithm for Expensive Optimization Problems -- A Self-adaptive Mixed Distribution Based Uni-variate Estimation of Distribution Algorithm for Large Scale Global Optimization -- Differential Evolution with Fitness Diversity Self-adaptation -- Central Pattern Generators: Optimisation and Application -- Section III: Collective Intelligence -- Fish School Search -- Magnifier Particle Swarm Optimization -- Improved Particle Swarm Optimization in Constrained Numerical Search Spaces -- Applying River Formation Dynamics to Solve NP-Complete Problems -- Section IV: Social-Natural Intelligence -- Algorithms Inspired in Social Phenomena -- Artificial Immune Systems for Optimization -- Section V: Multi-Objective Optimisation -- Ranking Methods in Many-Objective Evolutionary Algorithms -- On the Effect of Applying a Steady-State Selection Scheme in the Multi-Objective Genetic Algorithm NSGA-II -- Improving the Performance of Multiobjective Evolutionary Optimization Algorithms Using Coevolutionary Learning -- Evolutionary Optimization for Multiobjective Portfolio Selection under Markowitz’s Model with Application to the Caracas Stock Exchange.
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| 650 |
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|a Applied mathematics.
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| 650 |
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|a Engineering mathematics.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Operations research.
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| 650 |
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|a Decision making.
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| 650 |
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4 |
|a Mathematical and Computational Engineering.
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| 650 |
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4 |
|a Artificial Intelligence.
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| 650 |
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4 |
|a Operations Research/Decision Theory.
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| 700 |
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|a Chiong, Raymond.
|e editor.
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| 710 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 856 |
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|u https://doi.org/10.1007/978-3-642-00267-0
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