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GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 7 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2007
Springer
189views Optimization» more  GECCO 2007»
15 years 5 months ago
A genetic algorithm with exon shuffling crossover for hard bin packing problems
A novel evolutionary approach for the bin packing problem (BPP) is presented. A simple steady-state genetic algorithm is developed that produces results comparable to other approa...
Philipp Rohlfshagen, John A. Bullinaria
EMO
2006
Springer
161views Optimization» more  EMO 2006»
15 years 5 months ago
Design Issues in a Multiobjective Cellular Genetic Algorithm
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm fol...
Antonio J. Nebro, Juan José Durillo, Franci...
GECCO
2006
Springer
182views Optimization» more  GECCO 2006»
15 years 5 months ago
Distributed genetic algorithm for energy-efficient resource management in sensor networks
In this work we consider energy-efficient resource management in an environment monitoring and hazard detection sensor network. Our goal is to allocate different detection methods...
Qinru Qiu, Qing Wu, Daniel J. Burns, Douglas Holzh...
WSC
2007
15 years 4 months ago
Optimal scheduling of probabilistic repetitive projects using completed unit and genetic algorithms
In this paper we introduce the completed unit algorithm (CU-AL), a probabilistic scheduling methodology for repetitive projects. The algorithm has two main advantages, simplicity ...
Chachrist Srisuwanrat, Photios G. Ioannou