Evolutionary Multi-Criterion Optimization [electronic resource] : Second International Conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings / edited by Carlos M. Fonseca, Peter J. Fleming, Eckart Zitzler, Lothar Thiele, Kalyanmoy Deb.

By: Fonseca, Carlos M [editor.]Contributor(s): Fleming, Peter J [editor.] | Zitzler, Eckart [editor.] | Thiele, Lothar [editor.] | Deb, Kalyanmoy [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Computer Science: 2632Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2003Description: XVI, 820 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540369707Subject(s): Computer science | Computer software | Electronic data processing | Computational complexity | Artificial intelligence | Information systems | Mathematical optimization | Computer Science | Algorithm Analysis and Problem Complexity | Numeric Computing | Discrete Mathematics in Computer Science | Artificial Intelligence (incl. Robotics) | Computer Appl. in Administrative Data Processing | OptimizationAdditional physical formats: Printed edition:: No titleDDC classification: 005.1 LOC classification: QA76.9.A43Online resources: Click here to access online
Contents:
Objective Handling and Problem Decomposition -- The Maximin Fitness Function; Multi-objective City and Regional Planning -- Conflict, Harmony, and Independence: Relationships in Evolutionary Multi-criterion Optimisation -- Is Fitness Inheritance Useful for Real-World Applications? -- Use of a Genetic Heritage for Solving the Assignment Problem with Two Objectives -- Fuzzy Optimality and Evolutionary Multiobjective Optimization -- IS-PAES: A Constraint-Handling Technique Based on Multiobjective Optimization Concepts -- A Population and Interval Constraint Propagation Algorithm -- Multi-objective Binary Search Optimisation -- Covering Pareto Sets by Multilevel Evolutionary Subdivision Techniques -- An Adaptive Divide-and-Conquer Methodology for Evolutionary Multi-criterion Optimisation -- Multi-level Multi-objective Genetic Algorithm Using Entropy to Preserve Diversity -- Solving Hierarchical Optimization Problems Using MOEAs -- Multiobjective Meta Level Optimization of a Load Balancing Evolutionary Algorithm -- Algorithm Improvements -- Schemata-Driven Multi-objective Optimization -- A Real-Coded Predator-Prey Genetic Algorithm for Multiobjective Optimization -- Towards a Quick Computation of Well-Spread Pareto-Optimal Solutions -- Trade-Off between Performance and Robustness: An Evolutionary Multiobjective Approach -- Online Adaptation -- The Micro Genetic Algorithm 2: Towards Online Adaptation in Evolutionary Multiobjective Optimization -- Self-Adaptation for Multi-objective Evolutionary Algorithms -- MOPED: A Multi-objective Parzen-Based Estimation of Distribution Algorithm for Continuous Problems -- Test Problem Construction -- Instance Generators and Test Suites for the Multiobjective Quadratic Assignment Problem -- Dynamic Multiobjective Optimization Problems: Test Cases, Approximation, and Applications -- No Free Lunch and Free Leftovers Theorems for Multiobjective Optimisation Problems -- Performance Analysis and Comparison -- A New MOEA for Multi-objective TSP and Its Convergence Property Analysis -- Convergence Time Analysis for the Multi-objective Counting Ones Problem -- Niche Distributions on the Pareto Optimal Front -- Performance Scaling of Multi-objective Evolutionary Algorithms -- Searching under Multi-evolutionary Pressures -- Minimal Sets of Quality Metrics -- A Comparative Study of Selective Breeding Strategies in a Multiobjective Genetic Algorithm -- An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms -- Alternative Methods -- Using Simulated Annealing and Spatial Goal Programming for Solving a Multi Site Land Use Allocation Problem -- Solving Multi-criteria Optimization Problems with Population-Based ACO -- A Two-Phase Local Search for the Biobjective Traveling Salesman Problem -- Implementation -- PISA — A Platform and Programming Language Independent Interface for Search Algorithms -- A New Data Structure for the Nondominance Problem in Multi-objective Optimization -- The Measure of Pareto Optima Applications to Multi-objective Metaheuristics -- Distributed Computing of Pareto-Optimal Solutions with Evolutionary Algorithms -- Applications -- Multiobjective Capacitated Arc Routing Problem -- Multi-objective Rectangular Packing Problem and Its Applications -- Experimental Genetic Operators Analysis for the Multi-objective Permutation Flowshop -- Modification of Local Search Directions for Non-dominated Solutions in Cellular Multiobjective Genetic Algorithms for Pattern Classification Problems -- Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems -- Identification of Multiple Gene Subsets Using Multi-objective Evolutionary Algorithms -- Non-invasive Atrial Disease Diagnosis Using Decision Rules: A Multi-objective Optimization Approach -- Intensity Modulated Beam Radiation Therapy Dose Optimization with Multiobjective Evolutionary Algorithms -- Multiobjective Evolutionary Algorithms Applied to the Rehabilitation of a Water Distribution System: A Comparative Study -- Optimal Design of Water Distribution System by Multiobjective Evolutionary Methods -- Evolutionary Multiobjective Optimization in Watershed Water Quality Management -- Different Multi-objective Evolutionary Programming Approaches for Detecting Computer Network Attacks -- Safety Systems Optimum Design by Multicriteria Evolutionary Algorithms -- Applications of a Multi-objective Genetic Algorithm to Engineering Design Problems -- A Real-World Test Problem for EMO Algorithms -- Genetic Methods in Multi-objective Optimization of Structures with an Equality Constraint on Volume -- Multi-criteria Airfoil Design with Evolution Strategies -- Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map.
In: Springer eBooksSummary: The 2nd International Conference on Evolutionary Multi-Criterion Optimi- tion (EMO 2003) was held on April 8–11, 2003, at the University of the Algarve in Faro, Portugal. This was the second international conference dedicated en- rely to this important topic, following the very successful EMO 2001 conference, whichwasheldinZuric ¨ h,Switzerland,inMarch2001.EMO2003wasco-located with the IFAC International Conference on Intelligent Control Systems and S- nal Processing (ICONS 2003), exposing EMO to a wider audience of scientists and engineers. The EMO 2003 scienti?c program included two keynote addresses, one given byDavidScha?eronoptimizationandmachinelearninginindustry,andanother delivered by Pekka Korhonen on multiple-criteria decision making. In addition, three tutorials were presented, one on multicriterion decision analysis by - lerie Belton, another on multiobjective evolutionary algorithms by Kalyanmoy Deb, and a third on multiple objective metaheuristics by Andrzej Jaszkiewicz. The President of the Portuguese Innovation Agency, Prof. Jo˜ ao Silveira Lobo, and the President of the Portuguese Foundation for Science and Technology, Prof. Fernando Ramoa Ribeiro, attended the opening ceremony and the closing ceremony, respectively. In response to the call for papers, 100 full-length papers were submitted from 27 countries. Fifty-six papers were accepted for presentation at the conference after thorough reviewing by members of the program committee and they are contained in this volume. April 2003 Carlos M. Fonseca, Peter J. Fleming, Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele Organization EMO 2003 was organized by CSI (Centre for Intelligent Systems, University of the Algarve, Portugal) with the support of EvoNet (European Network of Excellence in Evolutionary Computing).
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Objective Handling and Problem Decomposition -- The Maximin Fitness Function; Multi-objective City and Regional Planning -- Conflict, Harmony, and Independence: Relationships in Evolutionary Multi-criterion Optimisation -- Is Fitness Inheritance Useful for Real-World Applications? -- Use of a Genetic Heritage for Solving the Assignment Problem with Two Objectives -- Fuzzy Optimality and Evolutionary Multiobjective Optimization -- IS-PAES: A Constraint-Handling Technique Based on Multiobjective Optimization Concepts -- A Population and Interval Constraint Propagation Algorithm -- Multi-objective Binary Search Optimisation -- Covering Pareto Sets by Multilevel Evolutionary Subdivision Techniques -- An Adaptive Divide-and-Conquer Methodology for Evolutionary Multi-criterion Optimisation -- Multi-level Multi-objective Genetic Algorithm Using Entropy to Preserve Diversity -- Solving Hierarchical Optimization Problems Using MOEAs -- Multiobjective Meta Level Optimization of a Load Balancing Evolutionary Algorithm -- Algorithm Improvements -- Schemata-Driven Multi-objective Optimization -- A Real-Coded Predator-Prey Genetic Algorithm for Multiobjective Optimization -- Towards a Quick Computation of Well-Spread Pareto-Optimal Solutions -- Trade-Off between Performance and Robustness: An Evolutionary Multiobjective Approach -- Online Adaptation -- The Micro Genetic Algorithm 2: Towards Online Adaptation in Evolutionary Multiobjective Optimization -- Self-Adaptation for Multi-objective Evolutionary Algorithms -- MOPED: A Multi-objective Parzen-Based Estimation of Distribution Algorithm for Continuous Problems -- Test Problem Construction -- Instance Generators and Test Suites for the Multiobjective Quadratic Assignment Problem -- Dynamic Multiobjective Optimization Problems: Test Cases, Approximation, and Applications -- No Free Lunch and Free Leftovers Theorems for Multiobjective Optimisation Problems -- Performance Analysis and Comparison -- A New MOEA for Multi-objective TSP and Its Convergence Property Analysis -- Convergence Time Analysis for the Multi-objective Counting Ones Problem -- Niche Distributions on the Pareto Optimal Front -- Performance Scaling of Multi-objective Evolutionary Algorithms -- Searching under Multi-evolutionary Pressures -- Minimal Sets of Quality Metrics -- A Comparative Study of Selective Breeding Strategies in a Multiobjective Genetic Algorithm -- An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms -- Alternative Methods -- Using Simulated Annealing and Spatial Goal Programming for Solving a Multi Site Land Use Allocation Problem -- Solving Multi-criteria Optimization Problems with Population-Based ACO -- A Two-Phase Local Search for the Biobjective Traveling Salesman Problem -- Implementation -- PISA — A Platform and Programming Language Independent Interface for Search Algorithms -- A New Data Structure for the Nondominance Problem in Multi-objective Optimization -- The Measure of Pareto Optima Applications to Multi-objective Metaheuristics -- Distributed Computing of Pareto-Optimal Solutions with Evolutionary Algorithms -- Applications -- Multiobjective Capacitated Arc Routing Problem -- Multi-objective Rectangular Packing Problem and Its Applications -- Experimental Genetic Operators Analysis for the Multi-objective Permutation Flowshop -- Modification of Local Search Directions for Non-dominated Solutions in Cellular Multiobjective Genetic Algorithms for Pattern Classification Problems -- Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems -- Identification of Multiple Gene Subsets Using Multi-objective Evolutionary Algorithms -- Non-invasive Atrial Disease Diagnosis Using Decision Rules: A Multi-objective Optimization Approach -- Intensity Modulated Beam Radiation Therapy Dose Optimization with Multiobjective Evolutionary Algorithms -- Multiobjective Evolutionary Algorithms Applied to the Rehabilitation of a Water Distribution System: A Comparative Study -- Optimal Design of Water Distribution System by Multiobjective Evolutionary Methods -- Evolutionary Multiobjective Optimization in Watershed Water Quality Management -- Different Multi-objective Evolutionary Programming Approaches for Detecting Computer Network Attacks -- Safety Systems Optimum Design by Multicriteria Evolutionary Algorithms -- Applications of a Multi-objective Genetic Algorithm to Engineering Design Problems -- A Real-World Test Problem for EMO Algorithms -- Genetic Methods in Multi-objective Optimization of Structures with an Equality Constraint on Volume -- Multi-criteria Airfoil Design with Evolution Strategies -- Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map.

The 2nd International Conference on Evolutionary Multi-Criterion Optimi- tion (EMO 2003) was held on April 8–11, 2003, at the University of the Algarve in Faro, Portugal. This was the second international conference dedicated en- rely to this important topic, following the very successful EMO 2001 conference, whichwasheldinZuric ¨ h,Switzerland,inMarch2001.EMO2003wasco-located with the IFAC International Conference on Intelligent Control Systems and S- nal Processing (ICONS 2003), exposing EMO to a wider audience of scientists and engineers. The EMO 2003 scienti?c program included two keynote addresses, one given byDavidScha?eronoptimizationandmachinelearninginindustry,andanother delivered by Pekka Korhonen on multiple-criteria decision making. In addition, three tutorials were presented, one on multicriterion decision analysis by - lerie Belton, another on multiobjective evolutionary algorithms by Kalyanmoy Deb, and a third on multiple objective metaheuristics by Andrzej Jaszkiewicz. The President of the Portuguese Innovation Agency, Prof. Jo˜ ao Silveira Lobo, and the President of the Portuguese Foundation for Science and Technology, Prof. Fernando Ramoa Ribeiro, attended the opening ceremony and the closing ceremony, respectively. In response to the call for papers, 100 full-length papers were submitted from 27 countries. Fifty-six papers were accepted for presentation at the conference after thorough reviewing by members of the program committee and they are contained in this volume. April 2003 Carlos M. Fonseca, Peter J. Fleming, Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele Organization EMO 2003 was organized by CSI (Centre for Intelligent Systems, University of the Algarve, Portugal) with the support of EvoNet (European Network of Excellence in Evolutionary Computing).

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