001461353 000__ 07820cam\a2200685\i\4500
001461353 001__ 1461353
001461353 003__ OCoLC
001461353 005__ 20230503003348.0
001461353 006__ m\\\\\o\\d\\\\\\\\
001461353 007__ cr\cn\nnnunnun
001461353 008__ 230313s2023\\\\sz\a\\\\ob\\\\101\0\eng\d
001461353 019__ $$a1372369138
001461353 020__ $$a9783031272509$$q(electronic bk.)
001461353 020__ $$a3031272501$$q(electronic bk.)
001461353 020__ $$z9783031272493
001461353 020__ $$z3031272498
001461353 0247_ $$a10.1007/978-3-031-27250-9$$2doi
001461353 035__ $$aSP(OCoLC)1372500029
001461353 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dUKAHL$$dOCLCF
001461353 049__ $$aISEA
001461353 050_4 $$aT57.95
001461353 08204 $$a658.4/03$$223/eng/20230313
001461353 1112_ $$aEMO (Conference)$$n(12th :$$d2023 :$$cLeiden, Netherlands)
001461353 24510 $$aEvolutionary multi-criterion optimization :$$b12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023, proceedings /$$cMichael Emmerich [and seven others], editors.
001461353 24630 $$aEMO 2023
001461353 264_1 $$aCham :$$bSpringer,$$c[2023]
001461353 264_4 $$c©2023
001461353 300__ $$a1 online resource (xix, 636 pages) :$$billustrations (chiefly color).
001461353 336__ $$atext$$btxt$$2rdacontent
001461353 337__ $$acomputer$$bc$$2rdamedia
001461353 338__ $$aonline resource$$bcr$$2rdacarrier
001461353 4901_ $$aLecture notes in computer science ;$$v13970
001461353 500__ $$aConference proceedings.
001461353 504__ $$aIncludes bibliographical references and author index.
001461353 5050_ $$aAlgorithm Design and Engineering -- Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization -- A Two-stage Algorithm for Integer Multiobjective Simulation Optimization -- RegEMO: Sacrificing Pareto-Optimality for Regularity in Multi-objective Problem-Solving -- Cooperative coevolutionary NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective Optimization -- Data-Driven Evolutionary Multi-Objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts -- Eliminating Non-dominated Sorting from NSGA-III -- Scalability of Multi-Objective Evolutionary Algorithms for Solving Real-World Complex Optimization Problems -- Machine Learning and Multi-criterion Optimization -- Multi-Objective Learning using HV Maximization -- Sparse Adversarial Attack via Bi-Objective Optimization -- Investigating Innovized Progress Operators with Different Machine Learning Methods -- End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location -- Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms -- Surrogate-assisted Multi-objective Optimization via Genetic Programming based Symbolic Regression -- Learning to Predict Pareto-optimal Solutions From Pseudo-weights -- A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimization -- Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling -- Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling -- Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables -- Feature-based Benchmarking of Distance-based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective -- Benchmarking and Performance Assessment -- Partially Degenerate Multi-Objective Test Problems -- Peak-A-Boo! Generating Multi-Objective Multiple Peaks Benchmark Problems with Precise Pareto Sets -- MACO: A Real-world inspired Benchmark for Multi-objective Evolutionary Algorithms -- A scalable test suite for bi-objective multidisciplinary optimisation -- Performance Evaluation of Multi-Objective Evolutionary Algorithms using Artificial and Real-World Problems -- A Novel Performance Indicator based on the Linear Assignment Problem -- A Test Suite for Multi-objective Multi-fidelity Optimization -- Indicator Design and Complexity Analysis -- Diversity enhancement via magnitude -- Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems -- Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems -- On the Computational Complexity of Efficient Non-Dominated Sort using Binary Search -- Applications in Real World Domains -- Evolutionary Algorithms with Machine Learning Models for Multiobjective Optimization in Epidemics Control -- Joint Price Optimization across a Portfolio of Fashion E-commerce Products -- Improving MOEA/D with Knowledge Discovery. Application to a Bi-Objective Routing Problem -- The Prism-Net Search Space Representation for Multi-Objective Building Spatial Design -- Selection Strategies for a Balanced Multi- or Many-Objective Molecular Optimization and Genetic Diversity: a Comparative Study -- A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules -- A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules. -Multiobjective Optimization of Evolutionary Neural Networks for Animal Trade Movements Prediction -- Transfer of Multi-Objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem -- Multi-Criteria Decision Making and Interactive Algorithms -- Preference-Based Nonlinear Normalization for Multiobjective Optimization -- Incorporating preference information interactively in NSGA-III by the adaptation of reference vectors -- A Systematic Way of Structuring Real-World Multiobjective Optimization Problems -- IK-EMOViz: An Interactive Knowledge-based Evolutionary Multi-objective Optimization Framework -- An Interactive Decision Tree-Based Evolutionary Multi-Objective Algorithm.
001461353 506__ $$aAccess limited to authorized users.
001461353 520__ $$aThis book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023. The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions. The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms.
001461353 588__ $$aDescription based on print version record.
001461353 650_0 $$aMultiple criteria decision making$$vCongresses.
001461353 650_0 $$aMathematical optimization$$vCongresses.
001461353 655_0 $$aElectronic books.
001461353 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001461353 655_7 $$aConference papers and proceedings.$$2lcgft
001461353 7001_ $$aEmmerich, Michael$$c(Associate professor),$$eeditor.$$1https://isni.org/isni/0000000496587685
001461353 77608 $$iPrint version:$$aEMO (Conference) (12th : 2023 : Leiden, Netherlands), creator.$$tEvolutionary multi-criterion optimization.$$dCham : Springer Nature Switzerland, 2023$$z9783031272493$$w(OCoLC)1368274005
001461353 830_0 $$aLecture notes in computer science ;$$v13970.
001461353 852__ $$bebk
001461353 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-27250-9$$zOnline Access$$91397441.1
001461353 909CO $$ooai:library.usi.edu:1461353$$pGLOBAL_SET
001461353 980__ $$aBIB
001461353 980__ $$aEBOOK
001461353 982__ $$aEbook
001461353 983__ $$aOnline
001461353 994__ $$a92$$bISE