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  1. 1
    Reactive approach for automating exploration and exploitation in ant colony optimization

    Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

    Published 2016
    “…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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  2. 2
    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches

    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…Ant colony optimization (ACO) is a stochastic search method for solving NP-hard problems. The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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  3. 3
    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm by M. H., Sulaiman, Muhammad Ikram, Mohd Rashid, Omar, Aliman, Mohd Rusllim, Mohamed, Abu Zaharin, Ahmad, Mohd. Shafie, Bakar

    Published 2014
    “…This paper presents a Swarm Intelligence (SI) technique namely Cuckoo Search Algorithm (CSA) which is inspired by parasitic behaviour of Cuckoo birds in reproduction strategy to obtain loss minimisation by solving the Optimal Reactive Power Dispatch (ORPD) problem. …”
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  4. 4
    Reactive memory model for ant colony optimization and its application to TSP

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…The exploration and exploitation are the main mechanisms in controlling search within the ACO. Reactive search is a framework for automating the exploration and exploitation in stochastic algorithms.Restarting the search with the aid of memorizing the search history is the soul of reaction.It is to increase the exploration only when needed.This paper proposes a reactive memory model to overcome the limitation of the random exploration after restart because of losing the previous history of search.The proposed model is utilized to record the previous search regions to be used as reference for ants after restart. …”
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  5. 5
    Modified reactive tabu search for the symmetric traveling salesman problems

    Modified reactive tabu search for the symmetric traveling salesman problems by Lim, Yai Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan

    Published 2013
    “…Reactive tabu search (RTS) is an improved method of tabu search (TS) and it dynamically adjusts tabu list size based on how the search is performed.RTS can avoid disadvantage of TS which is in the parameter tuning in tabu list size. …”
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  6. 6
    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index

    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

    Published 2023
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  7. 7
    GENETIC ALGORITHM FOR THE REDUCTION OF REACTIVE POWER LOSSES IN RADIAL DISTRIBUTION SYTEM

    GENETIC ALGORITHM FOR THE REDUCTION OF REACTIVE POWER LOSSES IN RADIAL DISTRIBUTION SYTEM by THIN, LO THIN

    Published 2006
    “…The objective and goal towards the end of the project is to achieve the reduction of reactive power loss using genetic algorithm. The final results of the project successfully provide solutions to the reduction of reactive power losses, which eventually further contribute to the entire electrical power system in achieving superior performance in the context of operational, economical and quality of service.…”
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  8. 8
    Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability

    Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability by Raizal N.I., Mansor M.H., Musirin I., Shaaya S.A., Ismail S.A., Ismail N.L.

    Published 2024
    “…This paper presents an approach to enhance the economic efficiency of power systems through tap settings optimization using Cuckoo Search Algorithm (CSA), while ensuring voltage stability. …”
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  9. 9
    Application of Genetic Algorithm for the Reduction of Reactive Power Losses in Radial Distribution System

    Application of Genetic Algorithm for the Reduction of Reactive Power Losses in Radial Distribution System by Perumal, Nallagownden, Lo, Thin Thin, Ng, Chin Guan, Mahmud, Che Mat Hadzer

    Published 2006
    “…The result is then compared with the heuristic search strategies to evaluate the performance of genetic algorithm.…”
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  10. 10
    Optimal placement of static VAR compensator using genetic algorithms

    Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

    Published 2008
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  11. 11
    Nature-inspired parameter controllers for ACO-based reactive search

    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
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  12. 12
    Mathematical formulation of tabu search in combinatorial optimization

    Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

    Published 2008
    “…This study is to develop Reactive Tabu Search (RTS) heuristics for solving CARP. …”
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  13. 13
    Optimized processing of satellite signal via evolutionary search algorithm

    Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

    Published 2000
    “…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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  14. 14
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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  15. 15
    Application-Programming Interface (API) for Song Recognition Systems

    Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

    Published 2024
    “…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”
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  16. 16
    Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin.

    Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin. by Musirin, Ismail

    Published 2004
    “…Finally, a novel Reactive Power Planning R.PP) algorithm using the state-of-the-art of EP for voltage stability improvement was developed. …”
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  17. 17
    Unified strategy for intensification and diversification balance in ACO metaheuristic

    Unified strategy for intensification and diversification balance in ACO metaheuristic by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2017
    “…This intensification and diversification in Ant Colony Optimization (ACO) is the search strategy to achieve a trade-off between learning a new search experience (exploration) and earning from the previous experience (exploitation).The automation between the two processes is maintained using reactive search. …”
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  18. 18
    Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine

    Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine by Mohd Wazir, Mustafa, Prof. Dr., Mohd Herwan, Sulaiman, Hussain, Shareef, Dr., Siti Nur Hidayah, Abd Khalid

    Published 2013
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  19. 19
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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  20. 20
    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)

    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS) by Lim, Yai Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan

    Published 2011
    “…The objective of the TSP is to find the shortest path that reaches all the cities which are interconnected with each other by straight lines.The symmetric TSP is used and the distance between two cities is calculated by using Euclidean equation.In this study, three heuristic methods, namely simulated annealing (SA), tabu search (TS) and reactive tabu search (RTS) are used to solve TSP.SA is a generic probabilistic meta-algorithm for the global optimization problem and TS is a meta-heuristic search technique that guides a local search procedure to explore the solution space beyond local optimality. …”
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