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GECCO
2006
Springer
155views Optimization» more  GECCO 2006»
15 years 10 months ago
Comparison of genetic representation schemes for scheduling soft real-time parallel applications
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Yoginder S. Dandass, Amit C. Bugde
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 10 months ago
Innovization: innovating design principles through optimization
This paper introduces a new design methodology (we call it "innovization") in the context of finding new and innovative design principles by means of optimization techni...
Kalyanmoy Deb, Aravind Srinivasan
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
15 years 10 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 10 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 10 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...
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