Heuristic Hybrid Genetic and Simulated Annealing Algorithms with Neural Networks for Task Assignment in Heterogeneous Computing Systems, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
In this thesis, we want to present methods that are able to solve the assignment tasks problem in a heterogeneous computing system. These methods are two hybrid methods that are constructed by composing Hopefield Neural Networks with Genetic Algorithms and the Simulated Annealing. First, we solve the relaxed problem by applying Genetic Algorithms and the Simulated Annealing and we compare the results of these ways with other traditional methods. Then, we solve the constrained problem with mentioned hybrid methods. The definition of the problem is as following: Consider a distributed computing system which is comprised of set of processors with different speeds but the same structure. We want...
Cataloging briefHeuristic Hybrid Genetic and Simulated Annealing Algorithms with Neural Networks for Task Assignment in Heterogeneous Computing Systems, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
In this thesis, we want to present methods that are able to solve the assignment tasks problem in a heterogeneous computing system. These methods are two hybrid methods that are constructed by composing Hopefield Neural Networks with Genetic Algorithms and the Simulated Annealing. First, we solve the relaxed problem by applying Genetic Algorithms and the Simulated Annealing and we compare the results of these ways with other traditional methods. Then, we solve the constrained problem with mentioned hybrid methods. The definition of the problem is as following: Consider a distributed computing system which is comprised of set of processors with different speeds but the same structure. We want...
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