Efficient computation of optimal assignments for distributed tasks
Journal of Parallel and Distributed Computing
On mapping parallel algorithms into parallel architectures
Journal of Parallel and Distributed Computing
Incorporating heuristic information into genetic search
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Implicit parallelism in genetic algorithms
Artificial Intelligence
Models of machines and computation for mapping in multicomputers
ACM Computing Surveys (CSUR)
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Communications of the ACM - Special issue on object-oriented experiences and future trends
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
P-Complete Approximation Problems
Journal of the ACM (JACM)
Parallel Genetic Algorithms: Theory and Applications
Parallel Genetic Algorithms: Theory and Applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parallel Genetic Algorithms Population Genetics and Combinatorial Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
A machine learning application for human resource data mining problem
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Fuzzy logic experience model in human resource management
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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In this paper we describe an hybrid heuristic approach, whichcombines Genetic Algorithms and Tabu Thresholding, for the staticallocation of interacting processes onto a parallel target system,where the number of processes is greater than the number of availableprocessors. This problem is known to be NP-hard and finds manypractical applications, given the increasing diffusion of distributedand parallel computing systems.The algorithm faces infeasibilities due to processors overload byincorporating them into the objective function and by adapting themutation operator. Global search is performed on the set of localoptima obtained by a repair search operator based on a TabuThresholding procedure.Extensive computational testing on randomly generated instances withup to 100 processes characterized by different target networktopologies with 4 to 25 processors, shows that the algorithmfavorably compares with other approaches from the literature.The proposed approach has also been extended to the allocation ofparallel objects and classes, where an additional co-residenceconstraint between each parallel object and the associated classarises.