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» A Genetic Algorithm Applied to the Maximum Flow Problem
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CEC
2009
IEEE
14 years 2 months ago
Optimization of the sizing of a solar thermal electricity plant: Mathematical programming versus genetic algorithms
— Genetic algorithms (GAs) have been argued to constitute a flexible search thereby enabling to solve difficult problems which classical optimization methodologies may find ha...
Jose M. Cabello, Jose M. Cejudo, Mariano Luque, Fr...
IC3
2009
13 years 5 months ago
A Hybrid Grouping Genetic Algorithm for Multiprocessor Scheduling
Abstract. This paper describes a hybrid grouping genetic algorithm for a multiprocessor scheduling problem, where a list of tasks has to be scheduled on identical parallel processo...
Alok Singh, Marc Sevaux, André Rossi
CEC
2007
IEEE
14 years 1 months ago
A cost benefit operator for efficient multi level genetic algorithm searches
— In this paper we present a novel cost benefit operator that assists multi level genetic algorithm searches. Through the use of the cost benefit operator, it is possible to dyna...
George G. Mitchell, Barry McMullin, James Decraene
ISPAN
2002
IEEE
14 years 16 days ago
A New Parallel Genetic Algorithm
One problem of propagating the globally fittest individual via neighbourhood evolving in both island model and cellular model of existing parallel genetic algorithms (PGA) is that...
Ling Tan, David Taniar, Kate A. Smith
GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
13 years 11 months ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi