Search Results - (( based optimization strategy algorithm ) OR ( based optimisation based algorithm ))

A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

“…Flower pollination algorithm (FPA) is a biomimicry optimisation algorithm inspired by natural pollination. …”
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Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

“…This strategy, which is based on the improved pelican optimization algorithm (IPOA), involves the development of a multi-objective optimization (MOA) equation with several constraints, while taking into account the Malaysian grid purchasing and selling prices. …”

Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables by Abdullah S., Shaker K., Shaker H.

“…In this study, we apply three algorithms, that is, Great Deluge, Simulated Annealing and Hill Climbing where the Round Robin algorithm is used as control strategy in choosing the algorithm to be employed at the current stage. …”

Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS by Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani, Tokhi, M. O.

“…Moreover, based on the statistical result, non-parametric Friedman and Wilcoxon signed rank tests and parametric t-test are performed to check the significant difference in the performance of the algorithms. …”
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Optimal design of low-voltage distribution networks for CO2 emission minimisation. Part II: Discrete optimisation of radial networks and comparison with alternative design strategi... by Gan, Chin Kim

“…The results found are compared to two benchmark networks designed according to a peak-based minimum investment strategy and an optimal economic strategy that minimises the network life-cycle cost. …”
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A performance of AFIRO among asynchronous iteration strategy metaheuristic algorithms by Ab Rahman, Tasiransurini, Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim

“…In the original paper, AFIRO was compared with the Particle Swarm Optimisation algorithm, Genetic Algorithm, and Grey Wolf Optimizer. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system by Roslan M.F., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Zuhdi A.W.M.

Priority-based vehicle-to-grid scheduling for minimization of power grid load variance by Hashim M.S., Yong J.Y., Ramachandaramurthy V.K., Tan K.M., Mansor M., Tariq M.

Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Malaysia residential load profile management based on time of use tariff using ant colony optimization algorithm by Dahlan, Nofri Yenita, Sulaima, Mohamad Fani, Wan Hanapi, Wan Noor Azzyati, Noor Din, Muhamad Muhtazam

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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Several solutions proposed in the literature are limited to addressing the cooperation problem and resource management issues. The joint optimisation problem of user association and power allocation has been studied extensively; however, conventional optimisation techniques still have room for improvement in distributed resource management strategies that evolve based on network dynamics. …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

“…This study investigates strategies for enhancing the performance of dual-star induction generators in wind power systems by optimizing the full control algorithm. …”

Development of a scalable video compression algorithm by Khalifa, Othman Omran, Issa, Sinzobakwira, Olanweraju, Rashidah Funke, Al Khazmi, El Mahdi A

“…The result shows that the managed complexity algorithm based on Lagrangian Multiplier function outperforms the normal encoder. …”
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A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

“…While gas detector technology has improved significantly, adopting a methodology for optimal placement of gas detectors is still an issue, especially when integrated with a risk-based approach. …”
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