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020 _a9781475751840
_9978-1-4757-5184-0
024 7 _a10.1007/978-1-4757-5184-0
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
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082 0 4 _a006.3
_223
100 1 _aCoello Coello, Carlos.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931937
245 1 0 _aEvolutionary Algorithms for Solving Multi-Objective Problems
_h[electronic resource] /
_cby Carlos Coello Coello, David A. Van Veldhuizen, Gary B. Lamont.
250 _a1st ed. 2002.
264 1 _aNew York, NY :
_bSpringer US :
_bImprint: Springer,
_c2002.
300 _aXXXV, 576 p. 85 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aGenetic Algorithms and Evolutionary Computation ;
_v5
505 0 _a1. Basic Concepts -- 2. Evolutionary Algorithm MOP Approaches -- 3. Moea Test Suites -- 4. Moea Testing and Analysis -- 5. Moea Theory and Issues -- 6. Applications -- 7. Moea Parallelization -- 8. Multi-Criteria Decision Making -- 9. Special Topics -- 10. Epilog -- Appendix A: Moea Classification and Technique Analysis -- 1 Introduction -- 1.1 Mathematical Notation -- 1.2 Presentation Layout -- 2.1 Lexicographic Techniques -- 2.2 Linear Fitness Combination Techniques -- 2.3 Nonlinear Fitness Combination Techniques -- 2.3.1 Multiplicative Fitness Combination Techniques -- 2.3.2 Target Vector Fitness Combination Techniques -- 2.3.3 Minimax Fitness Combination Techniques -- 3 Progressive MOEA Techniques -- 4.1 Independent Sampling Techniques -- 4.2 Criterion Selection Techniques -- 4.3 Aggregation Selection Techniques -- 4.4 Pareto Sampling Techniques -- 4.4.1 Pareto-Based Selection -- 4.4.2 Pareto Rank- and Niche-Based Selection -- 4.4.3 Pareto Deme-Based Selection -- 4.4.4 Pareto Elitist-Based Selection -- 4.5 Hybrid Selection Techniques -- 5 MOEA Comparisons and Theory -- 5.1 MOEA Technique Comparisons -- 5.2 MOEA Theory and Reviews -- 6 Alternative Multiobjective Techniques -- Appendix B: MOPs in the Literature -- Appendix E: Moea Software Availability -- 1 Introduction -- Appendix F: Moea-Related Information -- 1 Introduction -- 2 Websites of Interest -- 3 Conferences -- 4 Journals -- 5 Researchers -- 6 Distribution Lists -- References.
520 _aResearchers and practitioners alike are increasingly turning to search, op­ timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv­ ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub­ lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen­ tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub­ lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu­ tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be­ tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer science.
_99832
650 0 _aEngineering.
_99405
650 0 _aOperations research.
_912218
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aTheory of Computation.
_931938
650 2 4 _aTechnology and Engineering.
_931939
650 2 4 _aOperations Research and Decision Theory.
_931599
700 1 _aVan Veldhuizen, David A.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931940
700 1 _aLamont, Gary B.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931941
710 2 _aSpringerLink (Online service)
_931942
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781475751864
776 0 8 _iPrinted edition:
_z9781475751857
776 0 8 _iPrinted edition:
_z9780306467622
830 0 _aGenetic Algorithms and Evolutionary Computation ;
_v5
_931943
856 4 0 _uhttps://doi.org/10.1007/978-1-4757-5184-0
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