Search Results - (( simulation optimization window algorithm ) OR ( evolution optimisation based algorithm ))*

An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Simulation for dynamic patients scheduling based on many objective optimization and coordinator by Mahmed, Ali Nader, Mohd Nizam, Mohmad Kahar

“…Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization by Tri Basuki, Kurniawan, Misinem, ., Astried, ., Joan Angelina, Widians

“…The Travelling Salesman Problem (TSP) is a well-known algorithmic problem its main objective is optimization. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…The developed simulator incorporated particle swarm optimizations (PSO) to solve the ED problems. …”
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Simulation of identifying shortest path walkway in library by using ant colony optimization by Chui Teng, Chan

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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks by Qureshi, Barkatullah, Othman, Mohamed, K. Subramaniam, Shamala, Abdul Hamid, Nor Asilah Wati

“…To overcome these problems Quick Transport Control Protocol (QTCP) algorithm based on optimizations of HS-TCP slow start algorithm and Additive Increase and Multiplicative Decrease (AIMD) algorithm have been proposed. …”
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Performance enhancement of DCCP TCP - like over long delay link networks by Awang Nor, Shahrudin, Hassan, Suhaidi, Ghazali, Osman, M. Kadhum, Mohammed, Omar, Mohd Hasbullah

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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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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…Simulation results show that optimal current channel occupancy and price is well tracked by ADRP. …”
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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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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Orthogonal Frequency Division Multiple Access resource unit allocation algorithms for IEEE 802.11AX medium access control protocol by Zazali, Azyyati Adiah

“…The simulation results demonstrated that the proposed algorithms significantly outperformed the benchmark algorithms across several metrics. …”
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An efficient unknown detection approach for RFID data stream management system by Siti Salwani, Yaacob, Hairulnizam, Mahdin, Wijayanto, Inung, Muhammad Aamir, -, Mohd Izham, Mohd Jaya, Nabilah Filzah, Mohd Radzuan, Al Fahim, Mubarak Ali

“…The materials and methods employed include comprehensive simulations and real-world RFID data streams to validate the algorithm's effectiveness. …”
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Mathematical model of energy saving glass coating shape design using binary harmony search for better signal transmission by Jasmi, Muhammad Izzuddin

“…A well-designed algorithm is able to generate an optimized irregular shape design that can result in less attenuation on the transmission signal. …”
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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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