Search Results - (( job application using algorithm ) OR ( _ application ((bees algorithm) OR (ant algorithm)) ))
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Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Monograph -
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Ant colony algorithm for job scheduling in grid computing
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Scheduling jobs in computational grid using hybrid ACS and GA approach
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New heuristic function in ant colony system for job scheduling in grid computing
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Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
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Optimal design of step – cone pulley problem using the bees algorithm
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Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing
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Load balancing using enhanced ant algorithm in grid computing
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Resource management in grid computing using enhanced ant colony optimization
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Grid load balancing using enhance ant colony optimization
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Enhanced ant colony optimization for grid load balancing
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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Thesis -
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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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Job online scheduling within dynamic grid environment
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