Sciweavers

Share
TEC
2002
161views more  TEC 2002»
8 years 6 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
TEC
2008
98views more  TEC 2008»
8 years 7 months ago
A Fast Incremental Hypervolume Algorithm
When hypervolume is used as part of the selection or archiving process in a multiobjective evolutionary algorithm, it is necessary to determine which solutions contribute the least...
Lucas Bradstreet, R. Lyndon While, Luigi Barone
GECCO
2008
Springer
363views Optimization» more  GECCO 2008»
8 years 8 months ago
Towards high speed multiobjective evolutionary optimizers
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
8 years 8 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
8 years 8 months ago
Testing parallelization paradigms for MOEAs
In this paper, we report on our investigation of factors affecting the performance of various parallelization paradigms for multiobjective evolutionary algorithms. Different paral...
Sadeesha Gamhewa, Philip Hingston
GECCO
2010
Springer
248views Optimization» more  GECCO 2010»
8 years 10 months ago
Integrating decision space diversity into hypervolume-based multiobjective search
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Tamara Ulrich, Johannes Bader, Eckart Zitzler
EMO
2001
Springer
209views Optimization» more  EMO 2001»
8 years 11 months ago
Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy
We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachythera...
Natasa Milickovic, Michael Lahanas, Dimos Baltas, ...
EMO
2001
Springer
150views Optimization» more  EMO 2001»
8 years 11 months ago
On the Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization
This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
Marco Laumanns, Eckart Zitzler, Lothar Thiele
ICIC
2007
Springer
9 years 1 months ago
On the Convergence Properties of Quantum-Inspired Multi-Objective Evolutionary Algorithms
Abstract. In this paper, a general framework of quantum-inspired multiobjective evolutionary algorithms is proposed based on the basic principles of quantum computing and general s...
Zhiyong Li, Zhe Li, Günter Rudolph
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
9 years 1 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
books