Search Results - (( a distribution a algorithm ) OR ( peer evaluation ((based algorithm) OR (swarm algorithm)) ))

Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

“…Firstly, to detect the source, a Source Detection Algorithm (SDA) known as a Distributed Lévy Flight (DLF) is proposed. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…The DG units have to be allocated with optimal sizes in the network to reach maximum efficacy. A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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Reliability-aware swarm based multi-objective optimization for controller placement in distributed SDN architecture by Ibrahim, Abeer A.Z., Hashim, Fazirulhisyam, Sali, Aduwati, Noordin, Nor K., Navaie, Keivan, Fadul, Saber M.E.

“…A metaheuristic Particle Swarm Optimization (PSO) algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and cost-effectiveness. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…One of the main problems of this method is premature convergence and to improve this problem, the compound of the particle swarm algorithm and genetic algorithm were evaluated. The basis of this compound is in such a way that the advantages of the Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) have been applied simultaneously. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…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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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

“…Location information is a required concern for localization-based service application in the field of wireless sensor networks (WSNs). …”
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Chaotic ant swarm optimization to economic dispatch / Mohd Syafiq Md Salleh by Md Salleh, Mohd Syafiq

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Controller placement problem in the optimization of 5G based SDN and NFV architecture by Ibrahim, Abeer Abdalla Zakaria

“…A heuristic called dynamic mapping and multi-stage CPP algorithm (DMMCPP) was developed to solve CPP as resource allocation in a distributed 5G-SDN-NFV-based network. …”
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Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

“…The results indicate that proposed algorithm has succeeded in finding a reasonable placement and sizing of distributed generation with adequate feeder path. …”
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

“…Simulations were conducted to evaluate the proposed algorithms compared to the PSO algorithm, Cloud-Fog Cooperation Scheduling algorithm, and Task offloading algorithm. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Mohd Falfazli, Mat Jusof, Kian, Sheng Lim

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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…One of the challenging issues for a grid-connected distributed generation is to find a suitable technique to detect an islanding problem. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

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Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

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Optimum MV Feeder Routing and Substation siting and rating in Distribution Network by Hasan, Ihsan Jabbar, Ab Ghani, Mohd Ruddin, Gan, Chin Kim

“…The results showed the effectiveness of the proposed algorithm to find the acceptable location and sizing of distribution substations with a proper routing of the feeder.…”
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Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

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Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders by Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Mohd Ibrahim, Shapiai, Marizan, Mubin, Dong, Hwa Kim

“…However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept ofmultiple nondominated leaders is incorporated to further improve the VEPSO algorithm. …”
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