Evolutionary Multi-Criterion Optimization

1. Front Matter

   Pages I-XIII

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2. Tutorials

   1. Some Methods for Nonlinear Multi-objective Optimization

      • Kaisa Miettinen

      Pages 1-20

   2. A Short Tutorial on Evolutionary Multiobjective Optimization

      • Carlos A. Coello Coello Coello

      Pages 21-40

3. Invited Talks

   1. An Overview in Graphs of Multiple Objective Programming

      • Ralph E. Steuer

      Pages 41-51

   2. Poor-Definition, Uncertainty, and Human Factors - Satisfying Multiple Objectives in Real-World Decision-Making Environments

      • I. C. Parmee

      Pages 52-66

4. Algorithm Improvements

   1. Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence

      • Kalyanmoy Deb, Tushar Goel

      Pages 67-81

   2. Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms

      • Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen

      Pages 82-95

   3. Adapting Weighted Aggregation for Multiobjective Evolution Strategies

      • Yaochu Jin, Tatsuya Okabe, Bernhard Sendho

      Pages 96-110

   4. Incrementing Multi-objective Evolutionary Algorithms: Performance Studies and Comparisons

      • K. C. Tan, T. H. Lee, E. F. Khor

      Pages 111-125

   5. A Micro-Genetic Algorithm for Multiobjective Optimization

      • Carlos A. Coello Coello Coello, Gregorio Toscano Pulido

      Pages 126-140

   6. Evolutionary Algorithms for Multicriteria Optimization with Selecting a Representative Subset of Pareto Optimal Solutions

      • Andrzej Osyczka, Stanislaw Krenich

      Pages 141-153

   7. Multi-objective Optimisation Based on Relation Favour

      • Nicole Drechsler, Rolf Drechsler, Bernd Becker

      Pages 154-166

5. Performance Assessment and Comparison

   1. Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy

      • Natasa Milickovic, Michael Lahanas, Dimos Baltas, Nikolaos Zamboglou1

      Pages 167-180

   2. On The Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization

      • Marco Laumanns, Eckart Zitzler, Lothar Thiele

      Pages 181-196

   3. Global Multiobjective Optimization with Evolutionary Algorithms: Selection Mechanisms and Mutation Control

      • Thomas Hanne

      Pages 197-212

   4. Inferential Performance Assessment of Stochastic Optimisers and the Attainment Function

      • Viviane Grunert da Fonseca, Carlos M. Fonseca, Andreia O. Hall

      Pages 213-225

   5. A Statistical Comparison of Multiobjective Evolutionary Algorithms Including the MOMGA-II

      • Jesse B. Zydallis, David A. Van Veldhuizen, Gary B. Lamont

      Pages 226-240

   6. Performance of Multiple Objective Evolutionary Algorithms on a Distribution System Design Problem - Computational Experiment

      • Andrzej Jaszkiewicz, Maciej Hapke, Paweł Kominek

      Pages 241-255

6. Constraint Handling and Problem Decomposition

   1. An Infeasibility Objective for Use in Constrained Pareto Optimization

      • Jonathan Wright, Heather Loosemore

      Pages 256-268

   2. Reducing Local Optima in Single-Objective Problems by Multi-objectivization

      • Joshua D. Knowles, Richard A. Watson, David W. Corne

      Pages 269-283

This book constitutes the refereed proceedings of the First International Conference on Multi-Criterion Optimization, EMO 2001, held in Zurich, Switzerland in March 2001.
The 45 revised full papers presented were carefully reviewed and selected from a total of 87 submissions. Also included are two tutorial surveys and two invited papers. The book is organized in topical sections on algorithm improvements, performance assessment and comparison, constraint handling and problem decomposition, uncertainty and noise, hybrid and alternative methods, scheduling, and applications of multi-objective optimization in a variety of fields.

• Approximation
• Evolutionary Algorithms
• Genetic Algorithms
• Multi-Criterion Optimization
• Multiple Criteria Decision Making
• Optimal Solutions
• Pareto-Optimal Solutions
• Scheduling
• algorithms
• evolution
• multi-objective optimization
• optimization
• uncertainty
• algorithm analysis and problem complexity

• Department of Electrical Engineering Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Zurich, Switzerland

  Eckart Zitzler, Lothar Thiele

• Department of Mechanical Engineering Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, Kanpur, India

  Kalyanmoy Deb

• Electrical Engineering Department,Computer Science Section Av.Instituto Politecnico Nacional No.2508, CINVESTAV-IPN, Mexico City, Mexico

  Carlos Artemio Coello Coello

• Department of Computer Science, University of Reading, Whiteknights, UK

  David Corne

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