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  1. 1

    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

    Published 2025
    “…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
    Article
  2. 2

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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    Article
  3. 3

    Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions by Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.

    Published 2024
    “…By analysing objectives and simulation outcomes, the study provides insights for system refinement. The research strategically applies advanced algorithms to elevate PV-battery system performance and compares outcomes with Particle Swarm Optimization (PSO) and other studies, offering a comprehensive benchmark for evaluation…”
    Conference Paper
  4. 4

    Particle swarm optimization in multi-user orthogonal frequency-division multiplexing systems by Lye, Scott Carr Ken

    Published 2013
    “…To minimize the power consumption, Particle Swarm Optimization (PSO) is utilized to find the exact or near optimal resource allocation for the users. …”
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    Thesis
  5. 5

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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    Thesis
  6. 6

    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

    Published 2023
    “…Thereafter, the Multi-Leader Particle Swarm Optimization algorithm (MLPSO), which is a novel evolutionary optimization technique in the field of power systems was developed and employed in the optimization process. …”
    text::Thesis
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    Optimal Location of Electric Vehicle Fast Charging Station Using Grasshopper Optimization Algorithm by Yasin Z.M., Salim N.A., Noor S.Z.M., Aziz N.F.A., Mohamad H.

    Published 2024
    “…This paper proposes the Grasshopper Optimization Algorithm (GOA) as a technique for strategically locating FCS to minimize costs. …”
    Article
  9. 9

    Hybrid Harris Hawks with Sine Cosine for Optimal Node Placement and Congestion Reduction in an Industrial Wireless Mesh Network by Abdulrab, H.Q.A., Hussin, F.A., Ismail, I., Assaad, M., Awang, A., Shutari, H., Devan, P.A.M.

    Published 2023
    “…It was compared against four well-known algorithms including Sine Cosine Algorithm (SCA), Harris Hawks optimization (HHO), Gray Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). …”
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    Article
  10. 10

    Advances in metaheuristics: Applications in engineering systems by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2016
    “…It also includes discussions on the potential improvement of algorithmic characteristics via strategic algorithmic enhancements. …”
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    Book
  11. 11

    Double Deep RL-based strategy for UAV-assisted energy harvesting optimization in disaster-resilient IoT networks by Elmadina, Nahla Nur, Saeed, Rashid A, Saeid, Elsadig, Ali, Elmustafa Sayed, Nafea, Ibtehal, Ahmed, Mayada A, Mokhtar, Rania A, Khalifa, Othman Omran

    Published 2024
    “…Extensive simulations and comparisons with Deep RL and DDPG algorithms demonstrate the superior performance of DDRL in enhancing EH, covering strategic locations effectively, and achieving high satisfaction and accuracy rates.…”
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    Proceeding Paper
  12. 12

    Data driven hybrid evolutionary analytical approach for multi objective location allocation decisions: Automotive green supply chain empirical evidence by Doolun, Ian Shivraj, Ponnambalam, S. G., Subramanian, Nachiappan, Kanagaraj, G.

    Published 2018
    “…Five variants of the hybrid algorithm are evaluated in addition to comparing the performance with the existing Multi-Objective Hybrid Particle Swarm Optimization (MOHPSO) algorithm. …”
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    Article
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    Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology by ALAhmad A.K., Verayiah R., Shareef H., Ramasamy A.

    Published 2025
    “…Moreover, to ensure realism, the model incorporates uncertainties related to stochastic variables such as the intermittent nature of RESs, EV energy and time variables, loads, and energy price fluctuations, using Monte Carlo Simulation (MCS) and the backward reduction method (BRM). A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
    Article
  19. 19

    A novel HGBBDSA-CTI approach for subcarrier allocation in heterogeneous network by Hasan, Mohammad Kamrul, Ismail, Ahmad Fadzil, Islam, Shayla, Hashim, Wahidah, Ahmed, Musse Mohamud, Memon, Imran

    Published 2019
    “…This paper also analyses the time complexity for the proposed HGBBDSA algorithm and also compares it with the Genetic Algorithm-based Dynamic Subcarrier Allocation (DSA), and Particle Swarm Optimization-based DSA as well. …”
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    Article