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Multi objective bee colony optimization framework for grid job scheduling
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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Bee foraging behaviour techniques for grid scheduling problem
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm
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Reduced Galloping Column Algorithm For Memory Testing
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Analysis and Modification of Grain - 128 Stream Cipher Algorithm
Published 2024thesis::master thesis -
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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A fault syndromes simulator for random access memories
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.…”
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Hybrid flower pollination algorithm strategies for t-way test suite generation
Published 2018“…The application of meta-heuristic algorithms for t-way testing has recently become prevalent. …”
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An efficient fault syndromes simulator for SRAM memories
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An improved algorithm in test case generation from UML activity diagram using activity path
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Test suite generation based on hybrid flower pollination algorithm and hill climbing
Published 2021“…The application of meta-heuristic algorithms in t-way tests generation, as an example of SBST, has as of late gotten to be predominant. …”
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Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization
Published 2024“…More precisely, our work intents to investigate the algorithms' performance in terms of test reduction percentage and execution time. …”
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Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation
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Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test
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A multi-objective Spiral Dynamic algorithm and its application for PD design
Published 2017“…On the other hand, NS is a fast strategy to develop good Pareto Front (PF) characteristics for MO type algorithm. The proposed algorithm is tested with various benchmark functions used to test a newly developed MO algorithm. …”
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