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TNN
2010
171views Management» more  TNN 2010»
13 years 5 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 8 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 3 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, ...