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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2
    Automated study plan generator using rule-based and knapsack problem

    Automated study plan generator using rule-based and knapsack problem by Salahuddin, Lizawati, Hashim, Ummi Rabaah, Salahuddin, Lizawati

    Published 2022
    “…A combination of rule-based and knapsack problem were proposed to generate an automated study plan. …”
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  3. 3
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
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  4. 4
    Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning

    Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

    Published 2017
    “…The RFID network planning (RNP) problem belongs to the large-scale multi-objective hard optimization problems. …”
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  5. 5
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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  6. 6
    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem

    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem by M. F. F., Ab Rashid

    Published 2017
    “…Purpose – This paper aims to optimize the assembly sequence planning (ASP) problem using a proposed hybrid algorithm based on Ant Colony Optimization (ACO) and Gray Wolf Optimizer (GWO). …”
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  7. 7
    An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm

    An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm by Ibrahim, I., Ibrahim, Z., Ahmad, Hamzah, Jusof, M.F.M., Yusof, Z.M., Nawawi, S.W., Mubin, M.

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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  8. 8
    An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm

    An Assembly Sequence Planning Approach with a Rule-based Multi-state Gravitational Search Algorithm by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

    Published 2015
    “…In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. …”
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  9. 9
    Path planning for constant speed robot

    Path planning for constant speed robot by Abdullah @ Idris, Ahmad Takiyuddin

    Published 2006
    “…The purpose of this thesis is initially to present an implementation of a guidance algorithm based on the geometrical analysis for the adoption of path planning problem. …”
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  10. 10
    RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review

    RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review by YEJIAO, WANG, KAMALUDIN, HAZALILA, MOHAMMED ALDUAIS, NAYEF ABDULWAHAB, MOHD SAFAR, NOOR ZURAIDIN, ZHONGCHAO, HAO

    Published 2024
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  11. 11
    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…When compared to the Ant Colony Optimization algorithm, Simulated Annealing and Genetic Algorithm, the results obtained from African Buffalo Optimization show that the algorithm works well and can be extended to solving problems like: path planning, scheduling, vehicle routing in addition to other constraint-driven problems.…”
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  12. 12
    A genetic algorithm for solving single level lotsizing problems

    A genetic algorithm for solving single level lotsizing problems by Zenon, Nasaruddin, Ahmad, Ab. Rahman, Ali, Rosmah

    Published 2003
    “…In this paper a genetic algorithm for solving single level lot-sizing problems is proposed and the results of applying the algorithm toexample problems are discussed. …”
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  13. 13
    Optimization of RFID network planning using MDB-FA method

    Optimization of RFID network planning using MDB-FA method by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

    Published 2017
    “…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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  14. 14
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Later, this algorithm was used to solve bi-objective Production Planning (PP) and Scheduling Problem (Sch.P). …”
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  15. 15
    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm

    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

    Published 2019
    “…On the other hand, the recent ASP research tends to explore the potential of a relatively new algorithm to optimise ASP. Therefore, the aim of this research is to establish a methodology and implement the relatively new algorithm to optimise the Energy Efficient Assembly Sequence Planning (EE-ASP) problem. …”
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  16. 16
    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…Subsequently, both algorithms were applied to the test environments. Finally, the performances of both algorithms were analyzed and evaluated based on the required criteria. …”
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  17. 17
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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  18. 18
    Autonomous path planning robot using geographical information

    Autonomous path planning robot using geographical information by Ismail Ishaq Ibrahim

    Published 2008
    “…The purpose of this project is initially to present an implementation of a guidance algorithm based on the geometrical analysis for the adoption of path planning problem. …”
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  19. 19
    Application of Shuffled Frog Leaping Algorithm (SFLA) to long term generation expansion planning / Nurul Ulya Ibrahim

    Application of Shuffled Frog Leaping Algorithm (SFLA) to long term generation expansion planning / Nurul Ulya Ibrahim by Ibrahim, Nurul Ulya

    Published 2016
    “…This thesis presents a solution to generation expansion planning problem based on Shuffled Frog Leaping Algorithm (SFLA). …”
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  20. 20
    A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning.

    A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning. by Rajendran, Piraviendran, Othman, Muhaini

    Published 2024
    “…Objectives include analyzing features of mobile robot planning and representing them in ACO and GA, implementation ACO and GA algorithms for solving routing problems using dataset, and evaluating their performance. …”
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