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020 _a9783319159348
_9978-3-319-15934-8
024 7 _a10.1007/978-3-319-15934-8
_2doi
050 4 _aQA297-299.4
072 7 _aUYA
_2bicssc
072 7 _aCOM051300
_2bisacsh
082 0 4 _a518
_223
245 1 0 _aEvolutionary Multi-Criterion Optimization
_h[electronic resource] :
_b8th International Conference, EMO 2015, Guimar�aes, Portugal, March 29 --April 1, 2015. Proceedings, Part I /
_cedited by Ant�onio Gaspar-Cunha, Carlos Henggeler Antunes, Carlos Coello Coello.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXXIV, 447 p. 156 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v9018
505 0 _aPlenary Talks -- Interactive Approaches in Multiple Criteria Decision Making and Evolutionary Multi-objective Optimization -- Towards Automatically Configured Multi-objective Optimizers -- A Review of Evolutionary Multiobjective Optimization Applications in Aerospace Engineering -- Performance evaluation of multiobjective optimization algorithms: quality indicators and the attainment function -- Theory and Hyper-Heuristics -- A Multimodal Approach for Evolutionary Multi-objective Optimization (MEMO): Proof-of-Principle Results -- Unwanted Feature Interactions Between the Problem and Search Operators in Evolutionary Multi-objective Optimization -- Neutral but a Winner! How Neutrality helps Multiobjective Local Search Algorithms -- To DE or not to DE? Multi-Objective Differential Evolution Revisited from a Component-Wise Perspective -- Model-Based Multi-Objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark -- Temporal Innovization: Evolution of Design Principles Using Multi-objective  Optimization -- MOEA/D-HH: A Hyper-Heuristic for Multi-objective Problems -- Using hyper-heuristic to select leader and archiving methods for many-objective problems -- Algorithms -- Adaptive Reference Vector Generation for Inverse Model Based Evolutionary Multiobjective Optimization with Degenerate and Disconnected Pareto Fronts -- MOEA/PC: Multiobjective Evolutionary Algorithm Based on Polar Coordinates -- GD-MOEA: A New Multi-Objective Evolutionary Algorithm based on the Generational Distance Indicator -- Experiments on Local Search for Bi-objective Unconstrained Binary Quadratic Programming -- A Bug in the Multiobjective Optimizer IBEA: Salutary Lessons for Code Release and a Performance Re-Assessment -- A Knee-based EMO Algorithm with an Efficient Method to Update Mobile Reference Points -- A Hybrid Algorithm for Stochastic Multiobjective Programming Problem -- Parameter Tuning of MOEAs using a Bilevel Optimization Approach -- Pareto adaptive scalarising functions for decomposition based algorithms -- A bi-level multiobjective PSO algorithm -- An interactive simple indicator-based evolutionary algorithm (I-SIBEA) for multiobjective optimization problems -- Combining Non-dominance, Objective-sorted and Spread Metric to Extend Firefly Algorithm to Multi-objective Optimization -- GACO: a parallel evolutionary approach to multi-objective scheduling -- Kriging Surrogate Model Enhanced by Coordinate Transformation of Design Space Based on Eigenvalue Decomposition -- A Parallel Multi-Start NSGA II Algorithm for Multiobjective Energy Reduction Vehicle Routing Problem -- Evolutionary Inference of Attribute-based Access Control Policies -- Hybrid Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization -- A Comparison of Decoding Strategies for the 0/1 Multi-objective Unit Commitment Problem -- Comparing Decomposition-based and Automatically Component-Wise Designed Multi-objective Evolutionary Algorithms -- Upper Confidence Bound (UCB) Algorithms for Adaptive Operator Selection in MOEA/D -- Towards Understanding Bilevel Multi-objective Optimization with Deterministic Lower Level Decisions.
520 _aThis book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015  held in Guimar�aes, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary talks were carefully reviewed and selected from 90 submissions. The EMO 2015 aims to continue these type of developments, being the papers presented focused in: theoretical aspects, algorithms development, many-objectives optimization, robustness and optimization under uncertainty, performance indicators, multiple criteria decision making and real-world applications.
650 0 _aComputer science.
650 0 _aComputers.
650 0 _aAlgorithms.
650 0 _aNumerical analysis.
650 0 _aArtificial intelligence.
650 0 _aApplication software.
650 1 4 _aComputer Science.
650 2 4 _aNumeric Computing.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aComputation by Abstract Devices.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputer Applications.
700 1 _aGaspar-Cunha, Ant�onio.
_eeditor.
700 1 _aHenggeler Antunes, Carlos.
_eeditor.
700 1 _aCoello, Carlos Coello.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319159331
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v9018
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-15934-8
912 _aZDB-2-SCS
912 _aZDB-2-LNC
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999 _c57157
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