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Evolutionary Multi-Criterion Optimization

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Cover of 'Evolutionary Multi-Criterion Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 The Maximin Fitness Function; Multi-objective City and Regional Planning
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    Chapter 2 Conflict, Harmony, and Independence: Relationships in Evolutionary Multi-criterion Optimisation
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    Chapter 3 Is Fitness Inheritance Useful for Real-World Applications?
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    Chapter 4 Use of a Genetic Heritage for Solving the Assignment Problem with Two Objectives
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    Chapter 5 Fuzzy Optimality and Evolutionary Multiobjective Optimization
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    Chapter 6 IS-PAES: A Constraint-Handling Technique Based on Multiobjective Optimization Concepts
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    Chapter 7 A Population and Interval Constraint Propagation Algorithm
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    Chapter 8 Multi-objective Binary Search Optimisation
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    Chapter 9 Covering Pareto Sets by Multilevel Evolutionary Subdivision Techniques
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    Chapter 10 An Adaptive Divide-and-Conquer Methodology for Evolutionary Multi-criterion Optimisation
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    Chapter 11 Multi-level Multi-objective Genetic Algorithm Using Entropy to Preserve Diversity
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    Chapter 12 Solving Hierarchical Optimization Problems Using MOEAs
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    Chapter 13 Multiobjective Meta Level Optimization of a Load Balancing Evolutionary Algorithm
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    Chapter 14 Schemata-Driven Multi-objective Optimization
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    Chapter 15 A Real-Coded Predator-Prey Genetic Algorithm for Multiobjective Optimization
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    Chapter 16 Towards a Quick Computation of Well-Spread Pareto-Optimal Solutions
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    Chapter 17 Evolutionary Multi-Criterion Optimization
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    Chapter 18 The Micro Genetic Algorithm 2: Towards Online Adaptation in Evolutionary Multiobjective Optimization
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    Chapter 19 Self-Adaptation for Multi-objective Evolutionary Algorithms
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    Chapter 20 MOPED: A Multi-objective Parzen-Based Estimation of Distribution Algorithm for Continuous Problems
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    Chapter 21 Instance Generators and Test Suites for the Multiobjective Quadratic Assignment Problem
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    Chapter 22 Dynamic Multiobjective Optimization Problems: Test Cases, Approximation, and Applications
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    Chapter 23 No Free Lunch and Free Leftovers Theorems for Multiobjective Optimisation Problems
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    Chapter 24 A New MOEA for Multi-objective TSP and Its Convergence Property Analysis
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    Chapter 25 Convergence Time Analysis for the Multi-objective Counting Ones Problem
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    Chapter 26 Niche Distributions on the Pareto Optimal Front
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    Chapter 27 Performance Scaling of Multi-objective Evolutionary Algorithms
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    Chapter 28 Searching under Multi-evolutionary Pressures
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    Chapter 29 Minimal Sets of Quality Metrics
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    Chapter 30 A Comparative Study of Selective Breeding Strategies in a Multiobjective Genetic Algorithm
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    Chapter 31 An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms
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    Chapter 32 Using Simulated Annealing and Spatial Goal Programming for Solving a Multi Site Land Use Allocation Problem
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    Chapter 33 Solving Multi-criteria Optimization Problems with Population-Based ACO
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    Chapter 34 A Two-Phase Local Search for the Biobjective Traveling Salesman Problem
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    Chapter 35 PISA — A Platform and Programming Language Independent Interface for Search Algorithms
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    Chapter 36 A New Data Structure for the Nondominance Problem in Multi-objective Optimization
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    Chapter 37 The Measure of Pareto Optima Applications to Multi-objective Metaheuristics
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    Chapter 38 Distributed Computing of Pareto-Optimal Solutions with Evolutionary Algorithms
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    Chapter 39 Multiobjective Capacitated Arc Routing Problem
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    Chapter 40 Multi-objective Rectangular Packing Problem and Its Applications
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    Chapter 41 Experimental Genetic Operators Analysis for the Multi-objective Permutation Flowshop
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    Chapter 42 Modification of Local Search Directions for Non-dominated Solutions in Cellular Multiobjective Genetic Algorithms for Pattern Classification Problems
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    Chapter 43 Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems
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    Chapter 44 Identification of Multiple Gene Subsets Using Multi-objective Evolutionary Algorithms
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    Chapter 45 Non-invasive Atrial Disease Diagnosis Using Decision Rules: A Multi-objective Optimization Approach
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    Chapter 46 Intensity Modulated Beam Radiation Therapy Dose Optimization with Multiobjective Evolutionary Algorithms
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    Chapter 47 Multiobjective Evolutionary Algorithms Applied to the Rehabilitation of a Water Distribution System: A Comparative Study
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    Chapter 48 Optimal Design of Water Distribution System by Multiobjective Evolutionary Methods
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    Chapter 49 Evolutionary Multiobjective Optimization in Watershed Water Quality Management
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    Chapter 50 Different Multi-objective Evolutionary Programming Approaches for Detecting Computer Network Attacks
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    Chapter 51 Safety Systems Optimum Design by Multicriteria Evolutionary Algorithms
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    Chapter 52 Applications of a Multi-objective Genetic Algorithm to Engineering Design Problems
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    Chapter 53 A Real-World Test Problem for EMO Algorithms
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    Chapter 54 Genetic Methods in Multi-objective Optimization of Structures with an Equality Constraint on Volume
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    Chapter 55 Multi-criteria Airfoil Design with Evolution Strategies
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    Chapter 56 Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map
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Title
Evolutionary Multi-Criterion Optimization
Published by
Springer Science & Business Media, April 2003
DOI 10.1007/3-540-36970-8
ISBNs
978-3-54-001869-8, 978-3-54-036970-7
Editors

Fonseca, Carlos M., Fleming, Peter J., Zitzler, Eckart, Thiele, Lothar, Deb, Kalyanmoy

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 7%
Researcher 3 7%
Professor 1 2%
Student > Postgraduate 1 2%
Unknown 36 82%
Readers by discipline Count As %
Engineering 3 7%
Mathematics 2 5%
Computer Science 2 5%
Business, Management and Accounting 1 2%
Unknown 36 82%

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