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Evolutionary multi-criterion optimization : 4th international conference, EMO 2007, Matsushima, Japan, March 5-8, 2007 : proceedings

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Cover of 'Evolutionary multi-criterion optimization : 4th international conference, EMO 2007, Matsushima, Japan, March 5-8, 2007 : proceedings'

Table of Contents

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    Book Overview
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    Chapter 1 Aspiration Level Methods in Interactive Multi-objective Programming and Their Engineering Applications (Abstract of Invited Talk)
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    Chapter 2 Improving the Efficacy of Multi-objective Evolutionary Algorithms for Real-World Applications (Abstract of Invited Talk)
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    Chapter 3 Decision Making in Evolutionary Optimization (Abstract of Invited Talk)
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    Chapter 4 MOEAs in the Design of Network Centric Systems (Abstract of Invited Talk)
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    Chapter 5 Controlling Dominance Area of Solutions and Its Impact on the Performance of MOEAs
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    Chapter 6 Designing Multi-objective Variation Operators Using a Predator-Prey Approach
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    Chapter 7 Capabilities of EMOA to Detect and Preserve Equivalent Pareto Subsets
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    Chapter 8 Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization
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    Chapter 9 Reliability-Based Multi-objective Optimization Using Evolutionary Algorithms
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    Chapter 10 Multiobjective Evolutionary Algorithms on Complex Networks
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    Chapter 11 On Gradient Based Local Search Methods in Unconstrained Evolutionary Multi-objective Optimization
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    Chapter 12 Symbolic Archive Representation for a Fast Nondominance Test
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    Chapter 13 Design Issues in a Multiobjective Cellular Genetic Algorithm
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    Chapter 14 FastPGA: A Dynamic Population Sizing Approach for Solving Expensive Multiobjective Optimization Problems
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    Chapter 15 Constraint-Handling Method for Multi-objective Function Optimization: Pareto Descent Repair Operator
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    Chapter 16 Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
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    Chapter 17 A Multi-tiered Memetic Multiobjective Evolutionary Algorithm for the Design of Quantum Cascade Lasers
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    Chapter 18 Local Search in Two-Fold EMO Algorithm to Enhance Solution Similarity for Multi-objective Vehicle Routing Problems
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    Chapter 19 Mechanism of Multi-Objective Genetic Algorithm for Maintaining the Solution Diversity Using Neural Network
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    Chapter 20 Pareto Evolution and Co-evolution in Cognitive Game AI Synthesis
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    Chapter 21 The Development of a Multi-threaded Multi-objective Tabu Search Algorithm
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    Chapter 22 Differential Evolution versus Genetic Algorithms in Multiobjective Optimization
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    Chapter 23 EMOPSO: A Multi-Objective Particle Swarm Optimizer with Emphasis on Efficiency
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    Chapter 24 A Novel Differential Evolution Algorithm Based on ε -Domination and Orthogonal Design Method for Multiobjective Optimization
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    Chapter 25 Molecular Dynamics Optimizer
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    Chapter 26 Sequential Approximation Method in Multi-objective Optimization Using Aspiration Level Approach
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    Chapter 27 Multi-objective Optimisation of a Hybrid Electric Vehicle: Drive Train and Driving Strategy
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    Chapter 28 Multiobjective Evolutionary Neural Networks for Time Series Forecasting
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    Chapter 29 Heatmap Visualization of Population Based Multi Objective Algorithms
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    Chapter 30 Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm
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    Chapter 31 ParadisEO-MOEO: A Framework for Evolutionary Multi-objective Optimization
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    Chapter 32 Multi-objective Evolutionary Algorithms for Resource Allocation Problems
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    Chapter 33 Multi-objective Pole Placement with Evolutionary Algorithms
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    Chapter 34 A Multi-objective Evolutionary Approach for Phylogenetic Inference
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    Chapter 35 Evolutionary Multi-Criterion Optimization
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    Chapter 36 Combinatorial Optimization of Stochastic Multi-objective Problems: An Application to the Flow-Shop Scheduling Problem
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    Chapter 37 Evolutionary Algorithm Based Corrective Process Control System in Glass Melting Process
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    Chapter 38 Bi-objective Combined Facility Location and Network Design
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    Chapter 39 Local Search Guided by Path Relinking and Heuristic Bounds
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    Chapter 40 Rule Induction for Classification Using Multi-objective Genetic Programming
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    Chapter 41 Combining Linear Programming and Multiobjective Evolutionary Computation for Solving a Type of Stochastic Knapsack Problem
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    Chapter 42 Hybridizing Cellular Automata Principles and NSGAII for Multi-objective Design of Urban Water Networks
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    Chapter 43 Using Multiobjective Evolutionary Algorithms to Assess Biological Simulation Models
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    Chapter 44 Improving Computational Mechanics Optimum Design Using Helper Objectives: An Application in Frame Bar Structures
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    Chapter 45 A Multi-objective Approach to the Design of Conducting Polymer Composites for Electromagnetic Shielding
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    Chapter 46 Evolutionary Multiobjective Optimization of Steel Structural Systems in Tall Buildings
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    Chapter 47 Multi Criteria Decision Aiding Techniques to Select Designs After Robust Design Optimization
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    Chapter 48 MOGA-II for an Automotive Cooling Duct Optimization on Distributed Resources
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    Chapter 49 Individual Evaluation Scheduling for Experiment-Based Evolutionary Multi-objective Optimization
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    Chapter 50 A Multiobjectivization Approach for Vehicle Routing Problems
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    Chapter 51 Designing Traffic-Sensitive Controllers for Multi-Car Elevators Through Evolutionary Multi-objective Optimization
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    Chapter 52 On the Interactive Resolution of Multi-objective Vehicle Routing Problems
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    Chapter 53 Radar Waveform Optimisation as a Many-Objective Application Benchmark
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    Chapter 54 Robust Multi-Objective Optimization in High Dimensional Spaces
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    Chapter 55 Substitute Distance Assignments in NSGA-II for Handling Many-objective Optimization Problems
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    Chapter 56 Pareto-, Aggregation-, and Indicator-Based Methods in Many-Objective Optimization
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    Chapter 57 Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization
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    Chapter 58 Non-linear Dimensionality Reduction Procedures for Certain Large-Dimensional Multi-objective Optimization Problems: Employing Correntropy and a Novel Maximum Variance Unfolding
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    Chapter 59 I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods
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    Chapter 60 Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling
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    Chapter 61 Acceleration of Experiment-Based Evolutionary Multi-objective Optimization Using Fitness Estimation
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    Chapter 62 Evolutionary Multi-Criterion Optimization
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    Chapter 63 multi-Multi-Objective Optimization Problem and Its Solution by a MOEA
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    Chapter 64 The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration
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    Chapter 65 The Multiple Multi Objective Problem – Definition, Solution and Evaluation
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    Chapter 66 Adequacy of Empirical Performance Assessment for Multiobjective Evolutionary Optimizer
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    Chapter 67 A Comparative Study of Progressive Preference Articulation Techniques for Multiobjective Optimisation
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    Chapter 68 Test Problems Based on Lamé Superspheres
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    Chapter 69 Overview of Artificial Immune Systems for Multi-objective Optimization
Overall attention for this book and its chapters
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Mentioned by

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Citations

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Title
Evolutionary multi-criterion optimization : 4th international conference, EMO 2007, Matsushima, Japan, March 5-8, 2007 : proceedings
Published by
Springer, January 2007
DOI 10.1007/978-3-540-70928-2
ISBNs
978-3-54-070927-5, 978-3-54-070928-2
Authors

Obayashi, Shigeru

Editors

Shigeru Obayashi, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, Tadahiko Murata

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
United Kingdom 1 2%
Croatia 1 2%
Japan 1 2%
Unknown 48 89%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 30%
Student > Ph. D. Student 11 20%
Student > Bachelor 6 11%
Researcher 6 11%
Student > Postgraduate 3 6%
Other 7 13%
Unknown 5 9%
Readers by discipline Count As %
Computer Science 18 33%
Engineering 18 33%
Business, Management and Accounting 2 4%
Decision Sciences 2 4%
Chemical Engineering 2 4%
Other 7 13%
Unknown 5 9%