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  1. 1
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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  2. 2
    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem

    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2017
    “…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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  3. 3
    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics

    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2016
    “…The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution.This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions.The graph heuristics were set as single and combination of two heuristics.In addition, several ways of assigning courses into room and timeslot are implemented.All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced.The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions.The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions…”
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  4. 4
    Enhancing the Sorting Layers in the Initial Stage of High School Timetabling

    Enhancing the Sorting Layers in the Initial Stage of High School Timetabling by Arbaoui, Billel, Wahid, Juliana, Abdul-Rahman, Syariza

    Published 2020
    “…KHE is an algorithm that generates initial solution of HSTP. …”
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  5. 5
    Constructing population of initial solutions for curriculum – based course timetabling problem

    Constructing population of initial solutions for curriculum – based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2012
    “…This paper presents an investigation of a combination of graph coloring heuristics in construction approach in University course timetabling problem (UCTP) to produce a population of initial solutions. …”
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  6. 6
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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  7. 7
    Solving computational algorithm using CLONALNet technique based on artificial clonal selection

    Solving computational algorithm using CLONALNet technique based on artificial clonal selection by Samy J.A.L.A., Krishnan P.S.A.L., Kiong T.S.

    Published 2023
    “…This paper discusses the approach of CLONALNet in determining the optimum fitness function and mean population by benchmarking it with CLONALG. By using this algorithm the steps to obtain the fitness function is optimized and processing time is reduced. …”
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  8. 8
    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment

    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment by Suwoyo, Heru, Adriansyah, Andi, Andika, Julpri, Ubaidillah, Abu

    Published 2023
    “…The use of sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  9. 9
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, ANDIKA, JULFRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  10. 10
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Suwayo, Heri, Adrishah, Andi, Andika, Juleri, Shamdudin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  11. 11
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSHAH, ANDI, ANDIKA, JULPRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  12. 12
    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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  13. 13
    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…Subsequently, a novel approach that combines the hybrid rescheduling strategy with an initial robust schedule which is generated using random fuzzy variables is presented. …”
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  14. 14
    Fuzzy clustering method and evaluation based on multi criteria decision making technique

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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  15. 15
    A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem

    A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem by WATADA, J., ROY, A., LI, J., WANG, B., WANG, S.

    Published 2020
    “…The current paper presents a neural network-based hybrid strategy that combines a Genetic Algorithm (GA) and a Dual Recurrent Neural Network (DRNN) for efficiently and accurately solving the quadratic-Bi-level Programming Problem (BLPP). …”
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  16. 16
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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  17. 17
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by HERU SUWOYO, HERU SUWOYO, ANDI ADRIANSYAH, ANDI ADRIANSYAH, JULPRI ANDIKA, JULPRI ANDIKA, SHAMSUDIN, A LT UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  18. 18
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Heru Sowoyo, Heru Sowoyo, Andi Adrianshah, Andi Adrianshah, Julpri Andika, Julpri Andika, Shamsuddin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  19. 19
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, JULI RI ANDIKA, JULI RI ANDIKA, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…The use o = sampling-based algorithms such as Rapidly-Exploring Random Tree Star (RRT*) has been widely applied in robot path planning. …”
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  20. 20
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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