Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms

Studies in Computational Intelligence - Evolutionary Computation in Dynamic and Uncertain Environments ◽

10.1007/978-3-540-49774-5_20 ◽

2007 ◽

pp. 457-478 ◽

Cited By ~ 10

Author(s):

Chi Keong Goh ◽

Kay Chen Tan

Keyword(s):

Evolutionary Algorithms ◽

Pareto Optimality ◽

Multi Objective

How Genetic Algorithms Handle Pareto-Optimality in Design and Manufacturing

Handbook of Research on Nature-Inspired Computing for Economics and Management ◽

10.4018/978-1-59140-984-7.ch031 ◽

2007 ◽

pp. 465-482

Author(s):

N. Chakraborti

Keyword(s):

Genetic Algorithms ◽

Evolutionary Algorithms ◽

Pareto Optimality ◽

Multi Objective Optimization ◽

Recent Past ◽

Multi Objective ◽

Manufacturing Sectors ◽

Design And Manufacturing ◽

Basic Concepts

An informal analysis is provided for the basic concepts associated with multi-objective optimization and the notion of Pareto-optimality, particularly in the context of genetic algorithms. A number of evolutionary algorithms developed for this purpose are also briefly introduced, and finally, a number of paradigm examples are presented from the materials and manufacturing sectors, where multi-objective genetic algorithms have been successfully utilized in the recent past.

Land-use planning via enhanced multi-objective evolutionary algorithms: optimizing the land value of major Greenfield initiatives

Journal of Land Use Science ◽

10.1080/1747423x.2016.1223187 ◽

2016 ◽

Vol 11 (5) ◽

pp. 595-617 ◽

Cited By ~ 2

Author(s):

Spiros M. Karakostas

Keyword(s):

Land Use ◽

Evolutionary Algorithms ◽

Land Use Planning ◽

Land Value ◽

Multi Objective

Automated Test Input Generation for Convolutional Neural Networks by Implementing Multi-objective Evolutionary Algorithms

2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW) ◽

10.1109/candarw51189.2020.00040 ◽

2020 ◽

Author(s):

Lingfeng ZHANG ◽

Hiroyuki SATO

Keyword(s):

Neural Networks ◽

Evolutionary Algorithms ◽

Convolutional Neural Networks ◽

Multi Objective ◽

Test Input ◽

Automated Test

An interactive method for surrogate-assisted multi-objective evolutionary algorithms

2020 12th International Conference on Knowledge and Systems Engineering (KSE) ◽

10.1109/kse50997.2020.9287862 ◽

2020 ◽

Author(s):

Dinh Nguyen Duc ◽

Long Nguyen ◽

Kien Thai Trung

Keyword(s):

Evolutionary Algorithms ◽

Interactive Method ◽

Multi Objective

Visual mapping of multi-objective optimization problems and evolutionary algorithms

Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion ◽

10.1145/3377929.3398104 ◽

2020 ◽

Author(s):

Kohei Yamamoto ◽

Tomoaki Takagi ◽

Keiki Takadama ◽

Hiroyuki Sato

Keyword(s):

Evolutionary Algorithms ◽

Optimization Problems ◽

Multi Objective Optimization ◽

Multi Objective ◽

Visual Mapping

Multilayered composite structure design optimisation using distributed/parallel multi-objective evolutionary algorithms

Composite Structures ◽

10.1016/j.compstruct.2011.10.009 ◽

2012 ◽

Vol 94 (3) ◽

pp. 1087-1096 ◽

Cited By ~ 30

Author(s):

D.S. Lee ◽

C. Morillo ◽

G. Bugeda ◽

S. Oller ◽

E. Onate

Keyword(s):

Evolutionary Algorithms ◽

Composite Structure ◽

Structure Design ◽

Design Optimisation ◽

Multi Objective ◽

Multilayered Composite

Reference point based multi-objective optimization using evolutionary algorithms

Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06 ◽

10.1145/1143997.1144112 ◽

2006 ◽

Cited By ~ 142

Author(s):

Kalyanmoy Deb ◽

J. Sundar

Keyword(s):

Evolutionary Algorithms ◽

Reference Point ◽

Multi Objective Optimization ◽

Multi Objective

A performance comparison of multi-objective optimization evolutionary algorithms for all-optical networks design

2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM) ◽

10.1109/smdcm.2011.5949265 ◽

2011 ◽

Cited By ~ 12

Author(s):

Danilo R. B. Araujo ◽

Carmelo J. A. Bastos-Filho ◽

Erick A. Barboza ◽

Daniel A. R. Chaves ◽

Joaquim F. Martins-Filho

Keyword(s):

Evolutionary Algorithms ◽

Optical Networks ◽

Performance Comparison ◽

Multi Objective Optimization ◽

Multi Objective ◽

All Optical ◽

A Performance

Parallel Library of Multi-objective Evolutionary Algorithms

2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing ◽

10.1109/pdp.2009.38 ◽

2009 ◽

Cited By ~ 2

Author(s):

Coromoto Leon ◽

Gara Miranda ◽

Eduardo Segredo ◽

Carlos Segura

Keyword(s):

Evolutionary Algorithms ◽

Multi Objective ◽

Parallel Library

Performance comparison of generational and steady-state asynchronous multi-objective evolutionary algorithms for computationally-intensive problems

Knowledge-Based Systems ◽

10.1016/j.knosys.2015.05.029 ◽

2015 ◽

Vol 87 ◽

pp. 47-60 ◽

Cited By ~ 20

Author(s):

Alexandru-Ciprian Zăvoianu ◽

Edwin Lughofer ◽

Werner Koppelstätter ◽

Günther Weidenholzer ◽

Wolfgang Amrhein ◽

...

Keyword(s):

Steady State ◽

Evolutionary Algorithms ◽

Performance Comparison ◽

Multi Objective ◽

Computationally Intensive