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  1. 1

    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

    Published 2012
    “…Results indicate that “earliest available vehicle” is the best heuristic rule for the integrated scheduling method. Moreover, it is shown that on average, the best objective values obtained by the GA and SA algorithm, are only 6.4% and 3.7% worse than the optimal ones found by the MIP model, respectively; demonstrating that both algorithms are able to achieve near optimal solutions. …”
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    Thesis
  2. 2

    Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin by Wan Mohd Zakirudin, Wan Nur Athirah

    Published 2023
    “…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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    Thesis
  3. 3

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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    Thesis
  4. 4

    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries by Fadzli, S.A., Abdulkadir, S.I., Makhtar, M., Jamal, A.A.

    Published 2016
    “…The adjacency matrix is the naive storage structure of the algorithm. This storage structure has limited the use of the algorithm as it expands large storage space. …”
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    Conference or Workshop Item
  5. 5

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…The efficiency of the usual QN methods is improved by accelerating the performance of the algorithms without causing more storage demand. …”
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    Thesis
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    Globalization of Barzilai and Borwein Method for Unconstrained Optimization by Farid, Mahboubeh

    Published 2009
    “…A review of the minimization methods currently available that can be used to solve unconstrained optimization is also given. …”
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    Thesis
  8. 8

    Quasi-Newton methods based on ordinary differential equation approach for unconstrained nonlinear optimization by Khiyabani, Farzin Modarres, Leong, Wah June

    Published 2014
    “…Fundamentally this is a gradient system based on the first order optimality conditions of the optimization problem. To further extend the methods for solving large-scale problems, a feature incorporated to the proposed methods is that a limited memory setting for matrix–vector multiplications is used, thus avoiding the computational and storage issues when computing Jacobian information. …”
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    Article
  9. 9
  10. 10

    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

    Published 2023
    “…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
    text::Thesis
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    Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar by Shivashankar , Sukumar

    Published 2017
    “…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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    Thesis
  13. 13

    Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

    Published 2021
    “…The convergence analysis is presented for these memoryless methods under some standard assumptions. Numerical experiments are carried out using standard test problems and show that the proposed methods are superior to some existing conjugate gradient methods, in terms of iterations and function evaluations required to reach the optimal solutions. …”
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    Thesis
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  15. 15

    Evaluation of Search Result of Document Search Based GA (DSEGA) by Kamal Norfarid, Kamaruddin

    Published 2004
    “…It is composed by a series of module that using information retrieval method and genetic algorithm. …”
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    Thesis
  16. 16

    Multiple and solid data background scheme for testing static single cell faults on SRAM memories by Zakaria, Nor Azura

    Published 2013
    “…This method is evaluated in terms of function and performance differences between the proposed MTA and existing MTA using the User Defined Algorithm (UDA) available in the MBISTArchitect tool. …”
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    Thesis
  17. 17

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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    Thesis
  18. 18

    Development of an integrated scheduling model for handling equipment in automated port container terminals by Sadeghian, Syed Hamidreza

    Published 2014
    “…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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    Thesis
  19. 19

    Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method by Liu, Lihua, Lee, Lai Soon, Seow, Hsin Vonn, Chen, Chuei Yee

    Published 2022
    “…When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. …”
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    Article
  20. 20

    Sizing and placement of battery-coupled distributed photovoltaic generations by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

    Published 2017
    “…To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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    Article