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

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  1. 1

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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    Thesis
  2. 2

    A self‐configured link adaptation for green LTE downlink transmission by Salman, Mustafa Ismael, Ng, Chee Kyun, Noordin, Nor Kamariah, Mohd Ali, Borhanuddin, Sali, Aduwati

    Published 2015
    “…Then, a self‐configured link adaptation (SCLA) algorithm is developed to ensure that the priority weights related to EE and SE are adapted according to network load with the use of real‐time cross‐layer optimization. …”
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    Article
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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

    Published 2014
    “…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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    Article
  5. 5

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

    Published 2026
    “…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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    Article
  6. 6

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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    Conference or Workshop Item
  7. 7

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  8. 8

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…There is also the case where the Ant-miner cannot find any optimal solution for some data sets. Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
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    An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

    Published 2005
    “…Both algorithms are compared. Simulation is used as a method in this study. …”
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    Thesis
  12. 12

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…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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    Article
  13. 13

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…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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    Article
  14. 14

    Simulated annealing algorithm for scheduling divisible load in large scale data grids. by Abdullah, Monir, Othman, Mohamad, Ibrahim, Hamidah, Subramaniam, Shamala

    Published 2009
    “…Many Scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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    Article
  15. 15

    Underwater Acoustic Communications: Optimizing Data Packet Size With Respect to Throughput Efficiency, BER, and Energy Efficiency by Jung, L.T., Azween, Abdullah

    Published 2011
    “…Based on the results of the simulation the authors have proposed an algorithm/framework to determine the optimal packet size for UWA data transmission. …”
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    Conference or Workshop Item
  16. 16

    Optimization of handover algorithms in 3GPP long term evolution system by Lin, Cheng-Chung, Sandrasegaran, Kumbesan, Mohd. Ramli, Huda Adibah, Basukala, Riyaj, Patachaianand, Rachod, Chen, Lu, Afrin, Toyoba Sohana

    Published 2011
    “…Simulation results show that this optimization outperforms non-optimized algorithms by minimizing the average number of handovers per UE per second while maximizing average system throughput.…”
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    Proceeding Paper
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    Application of the Whale Optimization Algorithm (WOA) in Reservoir Optimization Operation Under Investigation of Climate Change Impact: A Case Study at Klang Gate Dam, Malaysia by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., El-Shafie A.

    Published 2024
    “…The Whale Optimization Algorithm (WOA) is a swarm intelligence algorithm derived following animal-behaviour-based concepts. …”
    Conference Paper
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    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…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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    Book Section
  20. 20

    Simulated annealing algorithm for scheduling divisible load in large scale data grids by Abdullah, Monir, Othman, Mohamed, Ibrahim, Hamidah, K. Subramaniam, Shamala

    Published 2008
    “…Many scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel simulated annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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    Conference or Workshop Item