LEADER 04353nam 22005775 450 001 9910736005103321 005 20230728155815.0 010 $a3-031-25263-2 024 7 $a10.1007/978-3-031-25263-1 035 $a(MiAaPQ)EBC30668883 035 $a(Au-PeEL)EBL30668883 035 $a(DE-He213)978-3-031-25263-1 035 $a(PPN)272250716 035 $a(CKB)27878834800041 035 $a(EXLCZ)9927878834800041 100 $a20230728d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMany-Criteria Optimization and Decision Analysis $eState-of-the-Art, Present Challenges, and Future Perspectives /$fedited by Dimo Brockhoff, Michael Emmerich, Boris Naujoks, Robin Purshouse 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (364 pages) 225 1 $aNatural Computing Series,$x2627-6461 311 08$aPrint version: Brockhoff, Dimo Many-Criteria Optimization and Decision Analysis Cham : Springer International Publishing AG,c2023 9783031252624 327 $aChapter 1: Introduction to Many-Criteria Optimization and Decision Analysis -- Chapter 2: Key Issues in Real-World Applications of Many-Objective Optimisation and Decision Analysis -- Chapter 3: Identifying Properties of Real-World Optimisation Problems through a Questionnaire -- Chapter 4: Many-Criteria Dominance Relations -- Chapter 5: Many-Objective Quality Measures -- Chapter 6: Benchmarking -- Chapter 7: Visualisation for decision support in many-objective optimisation: state-of-the-art, guidance and future directions -- Chapter 8: Theoretical Aspects of Subset Selection in Multi-Objective Optimisation -- Chapter 9: Identifying Correlations in Understanding and Solving Multi-Objective Problems -- Chapter 10: Bayesian Optimization -- Chapter 11: A game theoretic perspective on Bayesian many-objective optimization -- Chapter 12: Heterogeneous Objectives: State-of-the-Art and Future Research -- Chapter 13: MACODA Ontology and Knowledge Management. 330 $aThis book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously ? such as performance, cost, risk, sustainability, and quality. The field develops theory, methods and tools that can support decision makers in finding appropriate solutions when faced with many (typically more than three) such criteria at the same time. The book consists of two parts: key research topics, and emerging topics. Part I begins with a general introduction to many-criteria optimization, perspectives from research leaders in real-world problems, and a contemporary survey of the attributes of problems of this kind. This part continues with chapters on fundamental aspects of many-criteria optimization, namely on order relations, quality measures, benchmarking, visualization, and theoretical considerations. Part II offers more specialized chapters on correlated objectives, heterogeneous objectives, Bayesian optimization, and game theory. Written by leading experts across the field of many-criteria optimization, this book will be an essential resource for researchers in the fields of evolutionary computing, operations research, multiobjective optimization, and decision science. 410 0$aNatural Computing Series,$x2627-6461 606 $aComputer science 606 $aOperations research 606 $aTheory of Computation 606 $aOperations Research and Decision Theory 615 0$aComputer science. 615 0$aOperations research. 615 14$aTheory of Computation. 615 24$aOperations Research and Decision Theory. 676 $a006.3823 676 $a006.3823 700 $aBrockhoff$b Dimo$01380477 701 $aEmmerich$b Michael$01151656 701 $aNaujoks$b Boris$01380478 701 $aPurshouse$b Robin$01380479 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736005103321 996 $aMany-Criteria Optimization and Decision Analysis$93421914 997 $aUNINA