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Evolutionary Multi-Criterion Optimization

Overview of attention for book
Cover of 'Evolutionary Multi-Criterion Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 The Evolution of Optimality: De Novo Programming
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    Chapter 2 Many-Objective Optimization: An Engineering Design Perspective
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    Chapter 3 1984-2004 – 20 Years of Multiobjective Metaheuristics. But What About the Solution of Combinatorial Problems with Multiple Objectives?
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    Chapter 4 Omni-optimizer: A Procedure for Single and Multi-objective Optimization
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    Chapter 5 An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
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    Chapter 6 The Combative Accretion Model – Multiobjective Optimisation Without Explicit Pareto Ranking
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    Chapter 7 Parallelization of Multi-objective Evolutionary Algorithms Using Clustering Algorithms
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    Chapter 8 An Efficient Multi-objective Evolutionary Algorithm: OMOEA-II
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    Chapter 9 Path Relinking in Pareto Multi-objective Genetic Algorithms
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    Chapter 10 Dynamic Archive Evolution Strategy for Multiobjective Optimization
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    Chapter 11 Searching for Robust Pareto-Optimal Solutions in Multi-objective Optimization
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    Chapter 12 Multi-objective MaxiMin Sorting Scheme
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    Chapter 13 Multiobjective Optimization on a Budget of 250 Evaluations
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    Chapter 14 Initial Population Construction for Convergence Improvement of MOEAs
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    Chapter 15 Multi-objective Go with the Winners Algorithm: A Preliminary Study
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    Chapter 16 Exploiting Comparative Studies Using Criteria: Generating Knowledge from an Analyst’s Perspective
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    Chapter 17 A Multiobjective Evolutionary Algorithm for Deriving Final Ranking from a Fuzzy Outranking Relation
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    Chapter 18 Exploring the Performance of Stochastic Multiobjective Optimisers with the Second-Order Attainment Function
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    Chapter 19 Recombination of Similar Parents in EMO Algorithms
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    Chapter 20 A Scalable Multi-objective Test Problem Toolkit
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    Chapter 21 Extended Multi-objective fast messy Genetic Algorithm Solving Deception Problems
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    Chapter 22 Comparing Classical Generating Methods with an Evolutionary Multi-objective Optimization Method
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    Chapter 23 A New Analysis of the LebMeasure Algorithm for Calculating Hypervolume
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    Chapter 24 Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm
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    Chapter 25 Selection, Drift, Recombination, and Mutation in Multiobjective Evolutionary Algorithms on Scalable MNK-Landscapes
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    Chapter 26 Comparison Between Lamarckian and Baldwinian Repair on Multiobjective 0/1 Knapsack Problems
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    Chapter 27 The Value of Online Adaptive Search: A Performance Comparison of NSGAII, ε-NSGAII and εMOEA
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    Chapter 28 Fuzzy-Pareto-Dominance and its Application in Evolutionary Multi-objective Optimization
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    Chapter 29 Multi-objective Optimization of Problems with Epistemic Uncertainty
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    Chapter 30 The Naive ${\mathbb M}$ ID ${\mathbb E}$ A: A Baseline Multi–objective EA
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    Chapter 31 New Ideas in Applying Scatter Search to Multiobjective Optimization
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    Chapter 32 A MOPSO Algorithm Based Exclusively on Pareto Dominance Concepts
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    Chapter 33 Clonal Selection with Immune Dominance and Anergy Based Multiobjective Optimization
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    Chapter 34 A Multi-objective Tabu Search Algorithm for Constrained Optimisation Problems
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    Chapter 35 Improving PSO-Based Multi-objective Optimization Using Crowding, Mutation and ∈-Dominance
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    Chapter 36 DEMO: Differential Evolution for Multiobjective Optimization
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    Chapter 37 Multi-objective Model Selection for Support Vector Machines
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    Chapter 38 Evolutionary Multi-Criterion Optimization
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    Chapter 39 Extraction of Design Characteristics of Multiobjective Optimization – Its Application to Design of Artificial Satellite Heat Pipe
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    Chapter 40 Gray Coding in Evolutionary Multicriteria Optimization: Application in Frame Structural Optimum Design
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    Chapter 41 Multi-objective Genetic Algorithms to Create Ensemble of Classifiers
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    Chapter 42 Multi-objective Model Optimization for Inferring Gene Regulatory Networks
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    Chapter 43 High-Fidelity Multidisciplinary Design Optimization of Wing Shape for Regional Jet Aircraft
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    Chapter 44 Photonic Device Design Using Multiobjective Evolutionary Algorithms
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    Chapter 45 Multiple Criteria Lot-Sizing in a Foundry Using Evolutionary Algorithms
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    Chapter 46 Multiobjective Shape Optimization Using Estimation Distribution Algorithms and Correlated Information
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    Chapter 47 Evolutionary Multi-objective Environmental/Economic Dispatch: Stochastic Versus Deterministic Approaches
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    Chapter 48 A Multi-objective Approach to Integrated Risk Management
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    Chapter 49 An Approach Based on the Strength Pareto Evolutionary Algorithm 2 for Power Distribution System Planning
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    Chapter 50 Proposition of Selection Operation in a Genetic Algorithm for a Job Shop Rescheduling Problem
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    Chapter 51 A Two-Level Evolutionary Approach to Multi-criterion Optimization of Water Supply Systems
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    Chapter 52 Evolutionary Multi-objective Optimization for Simultaneous Generation of Signal-Type and Symbol-Type Representations
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    Chapter 53 A Multi-objective Memetic Algorithm for Intelligent Feature Extraction
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    Chapter 54 Solving the Aircraft Engine Maintenance Scheduling Problem Using a Multi-objective Evolutionary Algorithm
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    Chapter 55 Finding Pareto-Optimal Set by Merging Attractors for a Bi-objective Traveling Salesmen Problem
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    Chapter 56 Multiobjective EA Approach for Improved Quality of Solutions for Spanning Tree Problem
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    Chapter 57 Developments on a Multi-objective Metaheuristic (MOMH) Algorithm for Finding Interesting Sets of Classification Rules
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    Chapter 58 Preliminary Investigation of the ‘Learnable Evolution Model’ for Faster/Better Multiobjective Water Systems Design
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    Chapter 59 Particle Evolutionary Swarm for Design Reliability Optimization
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    Chapter 60 Multiobjective Water Pinch Analysis of the Cuernavaca City Water Distribution Network
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    Chapter 61 Multi-objective Vehicle Routing Problems Using Two-Fold EMO Algorithms to Enhance Solution Similarity on Non-dominated Solutions
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    Chapter 62 Multi-objective Optimisation of Turbomachinery Blades Using Tabu Search
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

patent
1 patent
wikipedia
1 Wikipedia page

Citations

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48 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Evolutionary Multi-Criterion Optimization
Published by
Lecture notes in computer science, January 2005
DOI 10.1007/b106458
ISBNs
978-3-54-024983-2, 978-3-54-031880-4
Authors

Carlos A. Coello Coello, Arturo Hernández Aguirre, Eckart Zitzler

Editors

Coello Coello, Carlos A., Hernández Aguirre, Arturo, Zitzler, Eckart

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 86%
Student > Master 1 14%
Readers by discipline Count As %
Engineering 4 57%
Computer Science 2 29%
Social Sciences 1 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 August 2014.
All research outputs
#4,709,254
of 22,846,662 outputs
Outputs from Lecture notes in computer science
#1,575
of 8,126 outputs
Outputs of similar age
#16,893
of 139,783 outputs
Outputs of similar age from Lecture notes in computer science
#25
of 132 outputs
Altmetric has tracked 22,846,662 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 139,783 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.