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TNN
2010
171views Management» more  TNN 2010»
13 years 6 months ago
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
Juan Carlos Fernández Caballero, Francisco ...
SEAL
2010
Springer
13 years 9 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
14 years 18 days ago
Integrating user preferences with particle swarms for multi-objective optimization
This paper proposes a method to use reference points as preferences to guide a particle swarm algorithm to search towards preferred regions of the Pareto front. A decision maker c...
Upali K. Wickramasinghe, Xiaodong Li
CEC
2008
IEEE
14 years 1 months ago
Automated solution selection in multi-objective optimisation
This paper proposes an approach to the solution of multi-objective optimisation problems that delivers a single, preferred solution. A conventional, population-based, multiobjectiv...
Andrew Lewis, David Ireland
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 3 months ago
Epsilon-constraint with an efficient cultured differential evolution
In this paper we present the use of a previously developed single-objective optimization approach, together with the -constraint method, to provide an approximation of the Pareto ...
Ricardo Landa Becerra, Carlos A. Coello Coello
EMO
2001
Springer
125views Optimization» more  EMO 2001»
14 years 4 months ago
Adapting Weighted Aggregation for Multiobjective Evolution Strategies
The conventional weighted aggregation method is extended to realize multi-objective optimization. The basic idea is that systematically changing the weights during evolution will l...
Yaochu Jin, Tatsuya Okabe, Bernhard Sendhoff
PPSN
2004
Springer
14 years 4 months ago
Multi-objective Optimisation by Co-operative Co-evolution
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-ob...
Kuntinee Maneeratana, Kittipong Boonlong, Nachol C...
GECCO
2007
Springer
161views Optimization» more  GECCO 2007»
14 years 5 months ago
Alternative techniques to solve hard multi-objective optimization problems
In this paper, we propose the combination of different optimization techniques in order to solve “hard” two- and threeobjective optimization problems at a relatively low comp...
Ricardo Landa Becerra, Carlos A. Coello Coello, Al...
IPPS
2007
IEEE
14 years 5 months ago
Parallel Processing for Multi-objective Optimization in Dynamic Environments
This paper deals with the use of parallel processing for multi-objective optimization in applications in which the objective functions, the restrictions, and hence also the soluti...
Mario Cámara, Julio Ortega, Francisco de To...
EVOW
2009
Springer
14 years 6 months ago
Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm
We apply evolutionary computation to calibrate the parameters of a morphogenesis model of Drosophila early development. The model aims to describe the establishment of the steady g...
Rui Dilão, Daniele Muraro, Miguel Nicolau, ...