Multiprocessor scheduling and neural network training methods using shuffled frog-leaping algorithm |
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| Affiliation: | 1. KIIT University, Bhubaneswar, Odisha, India;2. SOA University, Bhubaneswar, Odisha, India;3. National Institute of Technology, Patna, India;1. AIDS Immunopathogenesis Unit, Division of Immunology, Transplantation and Infectious Diseases, San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milano, Italy;2. Reproductive Sciences Laboratory, Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milano, Italy;3. Viral Pathogens and Biosafety Unit, Division of Immunology, Transplantation and Infectious Diseases, San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milano, Italy;4. Department of Obstetrics and Gynecology, San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milano, Italy;5. Vita-Salute San Raffaele University, School of Medicine, Via Olgettina 58, 20132, Milano, Italy;6. Pathology Unit, San Raffaele Scientific Institute, Via Olgettina 58, 20132, Milano, Italy;7. AIDS Immunopathology Department, National Centre of Microbiology, Instituto de Salud Carlos III. Cra Majadahonda a Pozuelo, 28220, Majadahonda, Madrid, Spain;1. Inter-University Accelerator Center (IUAC), New Delhi, India;2. Department of Earth Sciences, Indian Institute of Science Education and Research Kolkata, Nadia, WB, India;1. Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran;2. Department of Chemical Engineering, Sahand University of Technology, Tabriz, Iran;3. Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran;4. Institut de Recherche en Génie Chimique et Pétrolier (IRGCP), Paris Cedex, France;5. Thermodynamics Research Unit, School of Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa;1. Intestinal Failure Unit, Salford Royal NHS Foundation Trust, Stott Lane, Salford, M6 8HD, UK;2. Department of Microbiology, Salford Royal NHS Foundation Trust, Stott Lane, Salford, M6 8HD, UK |
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| Abstract: | In this paper, we designed novel methods for Neural Network (NN) and Radial Basis function Neural Networks (RBFNN) training using Shuffled Frog-Leaping Algorithm (SFLA). This paper basically deals with the problem of multi-processor scheduling in a grid environment. We, in this paper, introduce three novel approaches for the task scheduling problem using a recently proposed Shuffled Frog-Leaping Algorithm (SFLA). In a first attempt, the scheduling problem is structured as a problem of optimization and solved by SFLA. Next, this paper makes use of SFLA trained Artificial Neural Network (ANN) and Radial Basis function Neural Networks (RBFNN) for the problem of task scheduling. Interestingly, the proposed methods yield better performance than contemporary algorithms as evidenced by simulation results. |
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| Keywords: | Multiprocessor scheduling Neural network training Shuffled frog-leaping algorithm |
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