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CISIM
2008
IEEE
15 years 11 months ago
Tuning Struggle Strategy in Genetic Algorithms for Scheduling in Computational Grids
Job Scheduling on Computational Grids is gaining importance due to the need for efficient large-scale Grid-enabled applications. Among different optimization techniques addressed ...
Fatos Xhafa, Bernat Duran, Ajith Abraham, Keshav P...
ISPDC
2003
IEEE
15 years 9 months ago
OCEAN: The Open Computation Exchange and Arbitration Network, A Market Approach to Meta Computing
— Rapid advancements in processor and networking technologies have led to the evolution of cluster and grid computing frameworks. These high-performance computing environments ex...
Pradeep Padala, Cyrus Harrison, Nicholas Pelfort, ...
IJCAI
1993
15 years 5 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
125
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CEC
2010
IEEE
15 years 4 months ago
Parallel hybrid evolutionary algorithms on GPU
Abstract— Over the last years, interest in hybrid metaheuristics has risen considerably in the field of optimization. Combinations of methods such as evolutionary algorithms and...
Thé Van Luong, Nouredine Melab, El-Ghazali ...
SC
2000
ACM
15 years 9 months ago
Landing CG on EARTH: A Case Study of Fine-Grained Multithreading on an Evolutionary Path
We report on our work in developing a fine-grained multithreaded solution for the communicationintensive Conjugate Gradient (CG) problem. In our recent work, we developed a simpl...
Kevin B. Theobald, Gagan Agrawal, Rishi Kumar, Ger...