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  1. 1
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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  2. 2
    Overview of metaheuristic: classification of population and trajectory

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

    Published 2010
    “…Algorithms are used to find the solutions through the computer program. …”
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    Monograph
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  3. 3
    An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints

    An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints by Noraini, Mohd Razali

    Published 2015
    “…In order to obtain feasible solution which does not violate precedence constraints, a route repair based topological sort technique is used and integrated in the genetic algorithm procedure. …”
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  4. 4
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…Multi-objective Genetic Algorithms (MOGA) are an extension of Genetic Algorithms (GA) that does not require multiple objectives to be aggregated to one value. …”
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  5. 5
    Multi-population Genetic Algorithm for Rich Vehicle Routing Problems

    Multi-population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, Joseph Mabor

    Published 2020
    “…However, genetic algorithm is stochastic in nature and does not guarantee optimal solution in an application all the time, a problem referred to as premature convergence in literature. …”
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  6. 6
    Adopting Jaya Algorithm for Team Formation Problem

    Adopting Jaya Algorithm for Team Formation Problem by Kader, Md. Abdul, Kamal Z., Zamli

    Published 2020
    “…To evaluate the efficiency of the Jaya Algorithm (JA) against another metaheuristic algorithm, Sine-Cosine Algorithm (SCA), both algorithms are tested and assessed for the TF problem solution using an ACM dataset containing experts and their skills. …”
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  7. 7
    Vehicle routing problem with pick-up and delivery using genetic algorithm / Muhammad Shahfiq Zazali and Wan Muhamad Nasrin Aiman Mat Soti

    Vehicle routing problem with pick-up and delivery using genetic algorithm / Muhammad Shahfiq Zazali and Wan Muhamad Nasrin Aiman Mat Soti by Zazali, Muhammad Shahfiq, Mat Soti, Wan Muhamad Nasrin Aiman

    Published 2022
    “…The most optimal solution for the data used is 233641.009 calculated using a software that uses the Ruin and Recreate principle. …”
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  8. 8
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. …”
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  9. 9
    A modified technique in RFID networking planning and optimization

    A modified technique in RFID networking planning and optimization by Nawawi, Azli

    Published 2015
    “…In this research, PSO algorithm was used in the optimization process as it was considered as a very useful, efficient and well known algorithm. …”
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  10. 10
    Genetic algorithm to optimize routing problem modelled as the travelling salesman problem

    Genetic algorithm to optimize routing problem modelled as the travelling salesman problem by Muhammad Azrul Faiz , Nor Adzmi

    Published 2013
    “…The salesman needs to visit all the cities, but does not to travel so much. This study will use PCB component placement which is modelled as TSP. …”
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  11. 11
    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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  12. 12
    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints

    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints by Masitah, Jusop

    Published 2016
    “…Later, the optimisation algorithm will be tested and verified using test problems from literature. …”
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  13. 13
    Malay cuisine cooking recipe recommendation system using Genetic Algorithm (GA) / Nur Nazihah Ismail

    Malay cuisine cooking recipe recommendation system using Genetic Algorithm (GA) / Nur Nazihah Ismail by Ismail, Nur Nazihah

    Published 2017
    “…For this recommendation system, Genetic Algorithm (GA) is used as a technique to find the optimal results. …”
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  14. 14
    Multi-Population Genetic Algorithm for Rich Vehicle Routing Problems

    Multi-Population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, J.M., Kwang Hooi, Y., Zakaria, M.N.B.

    Published 2021
    “…However, GA is stochastic in nature and does not guarantee a good solution all the time, a problem primarily due to premature convergence. …”
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  15. 15
    Gps solution for active queue management using android platform

    Gps solution for active queue management using android platform by Liu, Yu Yao

    Published 2021
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  16. 16
    Single-agent finite impulse response optimizer for numerical optimization problems

    Single-agent finite impulse response optimizer for numerical optimization problems by Tasiransurini, Ab Rahman, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Zhao, Shunyi, Nor Hidayati, Abdul Aziz

    Published 2018
    “…The performance of the SAFIRO algorithm is evaluated using the CEC 2014 Benchmark Test Suite for single-objective optimization and statistically compared with the several well-known metaheuristic optimization algorithms, such as Particle Swarm Optimization algorithm, Genetic Algorithm, and Grey Wolf Optimization algorithm. …”
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  17. 17
    An improved bees algorithm local search mechanism for numerical dataset

    An improved bees algorithm local search mechanism for numerical dataset by Al-Dawoodi, Aras Ghazi Mohammed

    Published 2015
    “…Furthermore, in this study the feature selection algorithm is implemented and tested using most popular dataset from Machine Learning Repository (UCI). …”
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  18. 18
    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution

    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

    Published 2017
    “…The structure of the algorithm is designed so that the program does not require a large database to store the population, which speeds up the implementation of the program execution to obtain the solution; secondly, the algorithm has proven its success in solving the problem and finds a shortest route. …”
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  19. 19
    Development of a scheduling tool for constructing a Malaysian school timetable using genetic algorithms / Salihin Farag Shoeeb

    Development of a scheduling tool for constructing a Malaysian school timetable using genetic algorithms / Salihin Farag Shoeeb by Salihin Farag , Shoeeb

    Published 2003
    “…A recent approach to derive a near-optimal solution is to use evolutionary or genetic algorithms. …”
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  20. 20
    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling

    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…The IEEE RTS 26, 32 and 36-unit dataset systems were used in the performance evaluation of the PACS algorithm. …”
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