Search Results - (( java implication based algorithm ) OR ( based operations bees algorithm ))

Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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The Application of Artificial Bee Colony and Gravitational Search Algorithm in Reservoir Optimization by Ahmad, A., Razali, S.F.M., Mohamed, Z.S., El-Shafie, Ahmed

“…ABC is an algorithm based on the foraging behaviour of bee while GSA imitates the gravitational processes. …”
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Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

“…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm by Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.

Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid by Sukumar S., Marsadek M., Ramasamy A., Mokhlis H.

Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

“…In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). …”

Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm by Hossain, Md Shabbir, El-Shafie, Ahmed, Mahzabin, Mst Sadia, Zawawi, Mohd Hafiz

“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. …”
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Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

“…The final operation involves the mobile node sharing the current information with its neighbours’ nodes based on its current location. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

“…This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”

Average concept of crossover operator in real coded genetic algorithm by Abd Rahman, Rosshairy, Ramli, Razamin

“…As the most important search operator in a Genetic Algorithm (GA) approach, many procedures have been proposed to accomplish the idea of a crossover.As a result, knowledge in crossover has incorporated special features such as statistical elements (i.e. arithmetic crossover) and natural observation (i.e. queen bee crossover) to name a few.Thus, this paper proposed a mean or average concept of crossover for finer parents to produce a new offspring in a GA based approach in an animal diet formulation problem.Experiments using real data were carried out involving GA models with average crossover and one-point crossover.Subsequently, the incorporation of power heuristics as a repair operator was investigated to find the best combination of ingredients, while removing the unwanted ones.Comparisons were made between GA models incorporating repair operator with different crossovers: average crossover and one point crossover.The results show that the performance of average crossover is comparable with that of the one point crossover.The inclusion of the repair operator provides an advantage that shows interesting solution for the tested problem.…”
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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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Hybrid or modified optimization algorithms for dam reservoir water operation: A review by Nurhikmah F., Hossain M.S., Zawawi M.H.

“…It gave birth to most of population-based Metaheuristics such as Evolutionary Algorithms (EAs), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) etc. � 2018 Author(s).…”

A guided artificial bee colony (GABC) heuristic for permutation flowshop scheduling problem (PFSP) by Sidek, Noor Azizah

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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy by Hossain Md.S., El-Shafie A., Mohtar W.H.M.W.

“…The effect of the optimization algorithms was also investigated in terms of reservoir size and operational complexities. …”