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020 _a9789819939398
_9978-981-99-3939-8
024 7 _a10.1007/978-981-99-3939-8
_2doi
050 4 _aTA401-492
072 7 _aTGM
_2bicssc
072 7 _aTEC021000
_2bisacsh
072 7 _aTGM
_2thema
100 1 _aZheng, Maosheng.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965722
245 1 0 _aProbability-Based Multi-objective Optimization for Material Selection
_h[electronic resource] /
_cby Maosheng Zheng, Jie Yu, Haipeng Teng, Ying Cui, Yi Wang.
250 _a2nd ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIX, 202 p. 25 illus., 3 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aHistory and Current Status of Material Selection with Multi – objective Optimization -- Introduction to Multi – objective Optimization in Material Selections -- Fundamental Principle of Probability - Based Multi - Objective Optimization and Applications -- Robustness Evaluation with Probability-Based Multi-objective Optimization -- Extension of Probability – based Multi – objective Optimization in Condition of the Utility with Desirable Value -- Hybrids of Probability – Based Multi – Objective Optimization with Experimental Design Methodologies -- Discretization of Simplified Evaluation in Probability-Based Multi-objective Optimization by Means of GLP and Uniform Experimental Design -- Fuzzy- based Probabilistic Multi-objective Optimization -- Cluster Analyses of Multiple Objectives -- Applications of Probability – based Multi – objective Optimization beyond Material Selection -- Treatment of Portfolio Investment by Means of Probability-BasedMulti-objective Optimization -- Treatment of Multi-objective Shortest Path Problem by Means of Probability-Based Multi-objective -- Discussion on preferable probability, discretization, error analysis and hybrid of sequential uniform design with PMOO -- General Conclusions.
520 _aThe second edition of this book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection in viewpoint of system theory, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies (response surface methodology, orthogonal experimental design, and uniform experimental design) are all performed; robustness assessment and performance utility with desirable value are included; discretization treatment in the evaluation is presented; fuzzy-based approach and cluster analysis are involved; applications in portfolio investment and shortest path problem are concerned as well. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone. It is designed to be used as a textbook for postgraduate and advanced undergraduate students in relevant majors, while also serving as a valuable reference book for scientists and engineers involved in related fields. .
650 0 _aMaterials.
_965723
650 0 _aMathematical optimization.
_965522
650 0 _aChemistry.
650 0 _aProbabilities.
_965724
650 1 4 _aMaterials Engineering.
_965725
650 2 4 _aOptimization.
_965528
650 2 4 _aMaterials Chemistry.
_965726
650 2 4 _aApplied Probability.
_965727
700 1 _aYu, Jie.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965728
700 1 _aTeng, Haipeng.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965729
700 1 _aCui, Ying.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965730
700 1 _aWang, Yi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965731
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819939381
776 0 8 _iPrinted edition:
_z9789819939404
776 0 8 _iPrinted edition:
_z9789819939411
856 4 0 _uhttps://doi.org/10.1007/978-981-99-3939-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
999 _c56245
_d56245