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Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization
Published 2025“…Harmony search algorithm (HSA) is extensively utilized in engineering optimization. …”
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Hybrid harmony search algorithm integrating differential evolution and lévy flight for engineering optimization
Published 2025“…Harmony search algorithm (HSA) is extensively utilized in engineering optimization. …”
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3
Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization
Published 2025“…Harmony search algorithm (HSA) is extensively utilized in engineering optimization. …”
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4
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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6
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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8
A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization
Published 2018“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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An algorithmic framework for multiobjective optimization
Published 2013“…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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12
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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15
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method
Published 2016“…The multi-objective function, which represents the summation of product five indices by corresponding weights, was utilized to identify the candidate buses to reduce the search space of the algorithm. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…Specifically, the downlink frequency domain scheduler will reconfigure the criteria priorities such that the EE is maximized as long as the QoS is guaranteed.On the other hand, the partial feedback algorithm will search for the threshold value that minimizes the uplink overhead given that the QoS is achieved at the downlink.Otherwise, optimizing QoS parameters will be targeted at the cost of other system parameters. …”
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20
Economic power dispatch solutions incorporating stochastic wind power generators by moth flow optimizer
Published 2023“…According to the facts, MFO is superior to the other algorithms and might be utilized to address the OPF problem.…”
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