Title: Evolutionary multi-criterion optimization
Description: Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2001 Zurich, Switzerland, March 7–9, 2001 Proceedings<br />Author: Eckart Zitzler, Lothar Thiele, Kalyanmoy Deb, Carlos Artemio Coello Coello, David Corne<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-41745-3<br /> DOI: 10.1007/3-540-44719-9<br /><br />Table of Contents:<p></p><ul><li>Some Methods for Nonlinear Multi-objective Optimization
</li><li>A Short Tutorial on Evolutionary Multiobjective Optimization
</li><li>An Overview in Graphs of Multiple Objective Programming
</li><li>Poor-Definition, Uncertainty, and Human Factors - Satisfying Multiple Objectives in Real-World Decision-Making Environments
</li><li>Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence
</li><li>Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms
</li><li>Adapting Weighted Aggregation for Multiobjective Evolution Strategies
</li><li>Incrementing Multi-objective Evolutionary Algorithms: Performance Studies and Comparisons
</li><li>A Micro-Genetic Algorithm for Multiobjective Optimization
</li><li>Evolutionary Algorithms for Multicriteria Optimization with Selecting a Representative Subset of Pareto Optimal Solutions
</li><li>Multi-objective Optimisation Based on Relation Favour
</li><li>Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy
</li><li>On The Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization
</li><li>Global Multiobjective Optimization with Evolutionary Algorithms: Selection Mechanisms and Mutation Control
</li><li>Inferential Performance Assessment of Stochastic Optimisers and the Attainment Function
</li><li>A Statistical Comparison of Multiobjective Evolutionary Algorithms Including the MOMGA-II
</li><li>Performance of Multiple Objective Evolutionary Algorithms on a Distribution System Design Problem - Computational Experiment
</li><li>An Infeasibility Objective for Use in Constrained Pareto Optimization
</li><li>Reducing Local Optima in Single-Objective Problems by Multi-objectivization
</li><li>Constrained Test Problems for Multi-objective Evolutionary Optimization</li></ul>
Subjects: Mathematical optimization, Congresses, Multiple criteria decision making