## Evolutionary Multi-Criterion Optimization: 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, ProceedingsShigeru Obayashi, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, Tadahiko Murata Multicriterion optimization refers to problems with two or more objectives (normally in conflict with each other) which must be simultaneously satisfied. Evolutionary algorithms have been used for solving multicriterion optimization problems for over two decades, gaining an increasing attention from industry. The 4th International Conference on Evolutionary Multi-criterion Optimization (EMO2007) was held during March 5–8, 2007, in Matsushima/Sendai, Japan. This was the fourth international conference dedicated entirely to this important topic, following the successful EMO 2001, EMO 2003 and EMO 2005 conferences, which were held in Zürich, Switzerland in March 2001, in Faro, Portugal in April 2003, and in Guanajuato, México in March 2005. EMO2007 was hosted by the Institute of Fluid Science, Tohoku University. EMO2007 was co-hosted by the Graduate School of Information Sciences, Tohoku University, the Japan Aerospace Exploration Agency (JAXA), and the Policy Grid Computing Laboratory, Kansai University. The EMO2007 scientific program included four keynote speakers: Hirotaka Nakayama on aspiration level methods, Kay Chen Tan on large and computationally intensive real-world MO optimization problems, Carlos Fonseca on decision making, and Gary B. Lamont on design of large-scale network centric systems. |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

Programming and Their Engineering Applications | 1 |

Improving the Efficacy of Multiobjective Evolutionary Algorithms for RealWorld Applications | 2 |

Decision Making in Evolutionary Optimization | 3 |

MOEAs in the Design of Network Centric Systems | 4 |

Controlling Dominance Area of Solutions and Its Impact on the Performance of MOEAs | 5 |

Designing Multiobjective Variation Operators Using a PredatorPrey Approach | 21 |

Capabilities of EMOA to Detect and Preserve Equivalent Pareto Subsets | 36 |

Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization | 51 |

Evolutionary Algorithm Based Corrective Process Control System in Glass Melting Process | 472 |

Biobjective Combined Facility Location and Network Design | 486 |

Local Search Guided by Path Relinking and Heuristic Bounds | 501 |

Rule Induction for Classiﬁcation Using Multiobjective Genetic Programming | 516 |

Combining Linear Programming and Multiobjective Evolutionary Computation for Solving a Type of Stochastic Knapsack Problem | 531 |

Hybridizing Cellular Automata Principles and NSGAII for Multiobjective Design of Urban Water Networks | 546 |

Using Multiobjective Evolutionary Algorithms to Assess Biological Simulation Models | 560 |

An Application in Frame Bar Structures | 575 |

ReliabilityBased Multiobjective Optimization Using Evolutionary Algorithms | 66 |

Multiobjective Evolutionary Algorithms on Complex Networks | 81 |

On Gradient Based Local Search Methods in Unconstrained Evolutionary Multiobjective Optimization | 96 |

Symbolic Archive Representation for a Fast Nondominance Test | 111 |

Design Issues in a Multiobjective Cellular Genetic Algorithm | 126 |

A Dynamic Population Sizing Approach for Solving Expensive Multiobjective Optimization Problems | 141 |

Pareto Descent Repair Operator | 156 |

SteadyState Selection and Efficient Covariance Matrix Update in the Multiobjective CMAES | 171 |

A Multitiered Memetic Multiobjective Evolutionary Algorithm for the Design of Quantum Cascade Lasers | 186 |

Local Search in TwoFold EMO Algorithm to Enhance Solution Similarity for Multiobjective Vehicle Routing Problems | 201 |

Mechanism of MultiObjective Genetic Algorithm for Maintaining the Solution Diversity Using Neural Network | 216 |

Pareto Evolution and Coevolution in Cognitive Game AI Synthesis | 227 |

The Development of a Multithreaded Multiobjective Tabu Search Algorithm | 242 |

Differential Evolution Versus Genetic Algorithms in Multiobjective Optimization | 257 |

A MultiObjective Particle Swarm Optimizer with Emphasis on Efficiency | 272 |

A Novel Differential Evolution Algorithm Based on ϵDomination and Orthogonal Design Method for Multiobjective Optimization | 286 |

Molecular Dynamics Optimizer | 302 |

Sequential Approximation Method in Multiobjective Optimization Using Aspiration Level Approach | 317 |

Drive Train and Driving Strategy | 330 |

Multiobjective Evolutionary Neural Networks for Time Series Forecasting | 346 |

Heatmap Visualization of Population Based Multi Objective Algorithms | 361 |

Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm | 376 |

A Framework for Evolutionary Multiobjective Optimization | 386 |

Multiobjective Evolutionary Algorithms for Resource Allocation Problems | 401 |

Multiobjective Pole Placement with Evolutionary Algorithms | 417 |

A Multiobjective Evolutionary Approach for Phylogenetic Inference | 428 |

Perturbation Method | 443 |

An Application to the FlowShop Scheduling Problem | 457 |

A Multiobjective Approach to the Design of Conducting Polymer Composites for Electromagnetic Shielding | 590 |

Evolutionary Multiobjective Optimization of Steel Structural Systems in Tall Buildings | 604 |

Multi Criteria Decision Aiding Techniques to Select Designs After Robust Design Optimization | 619 |

MOGAII for an Automotive Cooling Duct Optimization on Distributed Resources | 633 |

Individual Evaluation Scheduling for ExperimentBased Evolutionary Multiobjective Optimization | 645 |

A Multiobjectivization Approach for Vehicle Routing Problems | 660 |

Designing TrafficSensitive Controllers for MultiCar Elevators Through Evolutionary Multiobjective Optimization | 673 |

On the Interactive Resolution of Multiobjective Vehicle Routing Problems | 687 |

Radar Waveform Optimisation as a ManyObjective Application Benchmark | 700 |

Robust MultiObjective Optimization in High Dimensional Spaces | 715 |

Substitute Distance Assignments in NSGAII for Handling ManyObjective Optimization Problems | 727 |

Pareto Aggregation and IndicatorBased Methods in ManyObjective Optimization | 742 |

Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization | 757 |

Employing Correntropy and a Novel Maximum Variance Unfolding | 772 |

An Interactive Multiobjective Optimization and DecisionMaking Using Evolutionary Methods | 788 |

A Case Study on Hydrothermal Power Scheduling | 803 |

Acceleration of ExperimentBased Evolutionary Multiobjective Optimization Using Fitness Estimation | 818 |

PredictionBased Population Reinitialization for Evolutionary Dynamic Multiobjective Optimization | 832 |

multiMultiObjective Optimization Problem and Its Solution by a MOEA | 847 |

On the Design of Paretocompliant Indicators Via Weighted Integration | 862 |

The Multiple Multi Objective Problem Deﬁnition Solution and Evaluation | 877 |

Adequacy of Empirical Performance Assessment for Multiobjective Evolutionary Optimizer | 893 |

A Comparative Study of Progressive Preference Articulation Techniques for Multiobjective Optimisation | 908 |

Test Problems Based on Lamé Superspheres | 922 |

Overview of Artiﬁcial Immune Systems for Multiobjective Optimization | 937 |

952 | |

### Other editions - View all

### Common terms and phrases

analysis applied approach archive assessment binary Coello Computer Science considered constraints convergence crossover deﬁned diﬀerent distance distribution diversity dominated dynamic eﬀect eﬃcient EMO algorithm Engineering evolution evolution strategy Evolutionary Algorithms Evolutionary Computation evolutionary multi-objective FastPGA feasible ﬁgure ﬁnal ﬁnd ﬁnding ﬁrst ﬁtness genetic algorithm hybrid hypervolume implemented indicator individuals linear local search maximum metaheuristics method metric minimization MOEA MOEO multi multi-objective optimization Multiobjective Evolutionary Algorithms mutation nodes non-dominated solutions NSGA-II number of objectives objective functions objective space obtained oﬀspring operator optimisation optimization problem parameters Pareto dominance Pareto front Pareto frontier Pareto optimal Pareto optimal solutions Pareto set performance points procedure proposed random rank reference region search space selection simulation single-objective solving SPEA2 speciﬁc stochastic strategy structural Table target techniques test functions test problems Thiele tion trade-oﬀ values vector vehicle weight ZDT1 ZDT3 Zitzler