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GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
15 years 6 months ago
Using performance fronts for parameter setting of stochastic metaheuristics
In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called “performance fronts” pres...
Johann Dréo
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 5 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
15 years 5 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
15 years 2 months ago
Structure and parameter estimation for cell systems biology models
In this work we present a new methodology for structure and parameter estimation in cell systems biology modelling. Our modelling framework is based on P systems, an unconl comput...
Francisco José Romero-Campero, Hongqing Cao...
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
15 years 2 months ago
Optinformatics for schema analysis of binary genetic algorithms
Given the importance of optimization and informatics which are the two broad fields of research, we present an instance of Optinformatics which denotes the specialization of info...
Minh Nghia Le, Yew-Soon Ong, Quang Huy Nguyen 0001