Search Results - optimal ((((bus algorithm) OR (((acs algorithm) OR (ant algorithm))))) OR (new algorithm))

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  1. 1
    Ant colony optimization in dynamic environments

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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  2. 2
    New heuristic function in ant colony system for the travelling salesman problem

    New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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  3. 3
    New heuristic function in ant colony system algorithm

    New heuristic function in ant colony system algorithm by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza, Yusof, Yuhanif, Mahmuddin, Massudi, Alobaedy, Mustafa Muwafak

    Published 2012
    “…NP-hard problem can be solved by Ant Colony System (ACS) algorithm.However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node.However, the heuristic value is not updated throughout the process to reflect new information discovered by the ants.This paper proposes a new heuristic function for the Ant Colony System algorithm that can reflect new information discovered by ants.The credibility of the new function was tested on travelling salesman and grid computing problems.Promising results were obtained when compared to classical ACS algorithm in terms of best tour length for the travelling sales-man problem. …”
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  4. 4
    Adaptive parameter control strategy for ant-miner classification algorithm

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
    “…Pruning is the popular framework for preventing the dilemma of over fitting noisy data. This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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  5. 5
    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems

    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

    Published 2017
    “…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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  6. 6
    Interacted multiple ant colonies optimization framework: An experimental study of the evaluation and the exploration techniques to control the search stagnation

    Interacted multiple ant colonies optimization framework: An experimental study of the evaluation and the exploration techniques to control the search stagnation by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita

    Published 2010
    “…The performance of IMACO was demonstrated by comparing it with the best performing ant algorithms like Ant Colony System (ACS) and Max-Min Ant System (MMAS). …”
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  7. 7
    Applying DACS3 in the Capacitated Vehicle Routing Problem

    Applying DACS3 in the Capacitated Vehicle Routing Problem by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2010
    “…Several versions of Ant Colony Optimization (ACO) algorithms have been proposed which aim to achieve an optimum solution includes Dynamic Ant Colony System with Three Level Updates (DACS3). …”
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  8. 8
    Modified ACS centroid memory for data clustering

    Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2019
    “…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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  9. 9
    Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method

    Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method by Noor Zaihah, Jamal, Mohd Herwan, Sulaiman, Abdul, Nasir, Jabbar, Waheb A.

    Published 2024
    “…The algorithms are tested to three test systems which are IEEE 3 bus, 8 bus and 15 bus system to validate the efficiency and superiority of the proposed algorithms. …”
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  10. 10
    Optimum tuning of Unified Power Flow Controller (UPFC) via Ant Colony Optimization (ACO) technique / Zulkiffli Abdul Hamid

    Optimum tuning of Unified Power Flow Controller (UPFC) via Ant Colony Optimization (ACO) technique / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2010
    “…The algorithm was implemented in MATLAB applied to the IEEE-30 Bus Reliability Test System (RTS). …”
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  11. 11
    An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem

    An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem by Modhi Lafta Mutar, Mohd Aboobaider, Burhanuddin, Asaad Shakir Hameed, Yusof, Norzihani, Hussein Jameel Mutashar

    Published 2020
    “…The proposed study seeks to find the best solution of CVRP by using improvement ACS with the accompanying targets: (1) To decrease the distance as long distances negatively affect the course of the process since it consumes a great time to visit all customers. (2) To implement the improvement of ACS algorithm on new data from the database of CVRP. …”
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  12. 12
    Optimization of reactive power pricing by using ant colony algorithm / Nur Azzammudin Rahmat

    Optimization of reactive power pricing by using ant colony algorithm / Nur Azzammudin Rahmat by Rahmat, Nur Azzammudin

    Published 2011
    “…The algorithm is based on ant's behaviour. Ant tends to use the shortest routes between their nest and food source. …”
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  13. 13
    Ant colony optimization (ACO) technique for reactive power planning in power system stability assessment / Mohd Rozely Kalil

    Ant colony optimization (ACO) technique for reactive power planning in power system stability assessment / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 2008
    “…The ACO algorithm is written in MATLAB and tested on IEEE 30-bus Reliability Test System (RTS) in order to verify the proposed technique. …”
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  14. 14
    Economic power dispatch of power system with pollution control using ant colony optimization / Ahmad Mat Saad

    Economic power dispatch of power system with pollution control using ant colony optimization / Ahmad Mat Saad by Mat Saad, Ahmad

    Published 2010
    “…The problem of economic dispatch has been forwarded and solved by numerous methods such as dynamic programming, tabu search, simulated annealing and genetic algorithm (GA).In this project, Ant Colony Optimization (ACO) is used to solve the problem of economic dispatch with pollution control. …”
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  15. 15
    Optimal Unit Commitment for Minimizing Total Operating Cost using Ant Lion Optimizer

    Optimal Unit Commitment for Minimizing Total Operating Cost using Ant Lion Optimizer by Yasin Z.M., Sam'On I.N., Salim N.A., Ab Aziz N.F., Zakaria Z.

    Published 2023
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  16. 16
    Optimal placement and sizing of a DG based on a new power stability index and line losses

    Optimal placement and sizing of a DG based on a new power stability index and line losses by Aman, M.M., Jasmon, G.B., Mokhlis, Hazlie, Bakar, A.H.A.

    Published 2012
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  17. 17
    An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system

    An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system by Jordehi, Ahmad Rezaee

    Published 2014
    “…The results of applying improved leader PSO to IEEE 14 bus power system shows its significant outperformance over six other optimisation algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,genetic algorithm and gravitational search algorithm. …”
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  18. 18
    Ant lion optimizer for solving unit commitment with solar photovoltaic integration / Izni Nadhirah Sam’on

    Ant lion optimizer for solving unit commitment with solar photovoltaic integration / Izni Nadhirah Sam’on by Sam’on, Izni Nadhirah

    Published 2020
    “…A new technique of Ant Lion Optimizer (ALO) is proposed to solve the unit commitment problem. …”
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  19. 19
    Balancing exploration and exploitation in ACS algorithms for data clustering

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Ant colony optimization (ACO) is a swarm algorithm inspired by different behaviors of ants. …”
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  20. 20
    A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism

    A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
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