Search Results - (( knowledge solution search algorithm ) OR ( java application reoptimize algorithm ))

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  1. 1

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. …”
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    Monograph
  2. 2

    The impact of population size on knowledge acquisition in genetic algorithms paradigm: Finding solutions in the game of Sudoku by Abu Bakar, Nordin, Mahadzir, Muhammad Fadhil

    Published 2010
    “…Population size is an important component in genetic algorithms (GAs).The concept of population in GAs has contributed to a unique searching strategy which empower its search process through the massive volume of the data in a population.The purpose of this study is to see how the impact of population size on genetic algorithms in producing correct solution for a Sudoku puzzle.Sudoku is a Japanese number puzzle game that has become a worldwide phenomenon.The puzzle involves completing a grid of cells by assigning a single number to each cell.The numbers in a row or a column must consist of any one of the numbers from 1 to 9; no repetition is allowed.GA will be used to generate the correct solution of Sudoku puzzles.The mechanism to produce legal Sudoku grid will follow the requirements needed and meet all the constraints.A fitness function is designed to evaluate legal grids and GA will be tested for performance and time efficiency.The challenges lie on how GA will represent a Sudoku grid in the process and the effectiveness of its operators such as crossover and mutation.The results show how different population size can produce different solutions.The best performance is observed at 500 population size.The paper will conclude with an insight of this value and its significance to the knowledge acquisition in GA paradigm..…”
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    Conference or Workshop Item
  3. 3

    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
    “…The proposed algorithm is designed by improving the exploration knowledge of onlooker bee from meta-heuristic concept in search space. …”
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    Article
  4. 4
  5. 5

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
  6. 6

    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

    Published 2008
    “…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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    Article
  7. 7

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…In addition, it is considered that existing solutions do not provide a feature driftaware solution to the concept drift adaptable solution, which exploits the fact that many of the original features are non-relevant. …”
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    Thesis
  8. 8

    Tasks Distribution In Driver Scheduling Using Dynamic Set Of Bandwidth In Harmony Search Algorithm With 2-Opt by Shaffiei, Zatul Alwani

    Published 2021
    “…Knowledge on the problem is needed to assist the searching process and to strengthen the exploitation. …”
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    Thesis
  9. 9

    An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation by Soong, Cai Juan, Abd Rahman, Rosshairy, Ramli, Razamin, Abd Manaf, Mohammed Suhaimee, Chek-Choon, Ting

    Published 2022
    “…*e novelty of the proposed SD tournament selection is compared with BT selection in terms of searching for an efficient but not myopic algorithm. …”
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    Article
  10. 10

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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    Thesis
  11. 11
  12. 12

    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

    Published 2022
    “…On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. Furthermore, this thesis contributes to the body of knowledge by introducing a novel method called Fuzzy Rough set Genetic Algorithm (FRGA) that take on efficiency of metaheuristics while reducing search space by leveraging the data mining aspect of rough set theory. …”
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    Thesis
  13. 13

    An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation by Kamal Z., Zamli, Fakhrud, Din, Kendall, Graham, Ahmed, Bestoun S.

    Published 2017
    “…Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. …”
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    Article
  14. 14

    Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2007
    “…Thus, this new level of pheromone updates which manipulating and empowering the searching experiences of individual ants can improve the current ACS algorithm. …”
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  15. 15

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…This problem remains an active area of research and, to the authors' knowledge, has not been adequately addressed by the WOA algorithm. …”
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    Article
  16. 16

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…This problem remains an active area of research and, to the authors’ knowledge, has not been adequately addressed by the WOA algorithm. …”
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    Article
  17. 17

    The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

    Published 2012
    “…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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  18. 18

    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…GAs are search algorithms which are based on the principles of natural selection and genetics. …”
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    Article
  19. 19

    Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

    Published 2003
    “…It complements the process of searching done. By giving more consideration to the initial problem space and not just the searching of the solution, the performance of SIP/DRIP has been humbly improved.…”
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    Thesis
  20. 20

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Much of these algorithms have adopted elegant metaphors (e.g. heating and cooling of metals in the case of SA and swarming of flocking birds in the case of PSO) from nature in order to derive the mathematical models for generating the solution as well as provides control over their exploration (i.e. sufficient roaming of the search space) and exploitation (i.e. using known knowledge of the surroundings). …”
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