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EMO
2006
Springer
117views Optimization» more  EMO 2006»
13 years 8 months ago
Multiplex PCR Assay Design by Hybrid Multiobjective Evolutionary Algorithm
Abstract. Multiplex Polymerase Chain Reaction (PCR) assay is to amplify multiple target DNAs simultaneously using different primer pairs for each target DNA. Recently, it is widely...
In-Hee Lee, Soo-Yong Shin, Byoung-Tak Zhang
EMO
2006
Springer
120views Optimization» more  EMO 2006»
13 years 8 months ago
Rule Induction for Classification Using Multi-objective Genetic Programming
Multi-objective metaheuristics have previously been applied to partial classification, where the objective is to produce simple, easy to understand rules that describe subsets of a...
Alan P. Reynolds, Beatriz de la Iglesia
EMO
2006
Springer
172views Optimization» more  EMO 2006»
13 years 10 months ago
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
Christian Igel, Thorsten Suttorp, Nikolaus Hansen
EMO
2006
Springer
107views Optimization» more  EMO 2006»
13 years 10 months ago
Designing Multi-objective Variation Operators Using a Predator-Prey Approach
In this paper, we propose a new conceptual method for the design, investigation, and evaluation of multi-objective variation operators for evolutionary multi-objective algorithms. ...
Christian Grimme, Joachim Lepping
EMO
2006
Springer
124views Optimization» more  EMO 2006»
13 years 10 months ago
I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods
With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO ...
Kalyanmoy Deb, Shamik Chaudhuri
EMO
2006
Springer
161views Optimization» more  EMO 2006»
13 years 10 months ago
Design Issues in a Multiobjective Cellular Genetic Algorithm
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm fol...
Antonio J. Nebro, Juan José Durillo, Franci...
EMO
2006
Springer
68views Optimization» more  EMO 2006»
13 years 10 months ago
Multi-objective Evolutionary Algorithms for Resource Allocation Problems
Dilip Datta, Kalyanmoy Deb, Carlos M. Fonseca
EMO
2006
Springer
110views Optimization» more  EMO 2006»
13 years 10 months ago
Capabilities of EMOA to Detect and Preserve Equivalent Pareto Subsets
Recent works in evolutionary multiobjective optimization suggest to shift the focus from solely evaluating optimization success in the objective space to also taking the decision s...
Günter Rudolph, Boris Naujoks, Mike Preuss
EMO
2006
Springer
173views Optimization» more  EMO 2006»
13 years 10 months ago
Differential Evolution versus Genetic Algorithms in Multiobjective Optimization
This paper presents a comprehensive comparison between the performance of state-of-the-art genetic algorithms NSGA-II, SPEA2 and IBEA and their differential evolution based variant...
Tea Tusar, Bogdan Filipic