Yazar "Abiyev, Rahib H." seçeneğine göre listele

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  • Küçük Resim
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    Improved Hypercube Optimisation Search Algorithm for Optimisation of High Dimensional Functions
    (HINDAWI LTD, ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON W1T 5HF, ENGLAND, 2022) Tunay, Mustafa; Abiyev, Rahib H.
    This paper proposes a stochastic search algorithm called improved hypercube optimisation search (HOS+) to find a better solution for optimisation problems. This algorithm is an improvement of the hypercube optimisation algorithm that includes initialization, displacement-shrink and searching area modules. The proposed algorithm has a new random parameters (RP) module that uses two control parameters in order to prevent premature convergence and slow finishing and improve the search accuracy considerable. Many optimisation problems can sometimes cause getting stuck into an interior local optimal solution. HOS+ algorithm that uses a random module can solve this problem and find the global optimal solution. A set of experiments were done in order to test the performance of the algorithm. At first, the performance of the proposed algorithm is tested using low and high dimensional benchmark functions. The simulation results indicated good convergence and much better performance at the lowest of iterations. The HOS+ algorithm is compared with other meta heuristic algorithms using the same benchmark functions on different dimensions. The comparative results indicated the superiority of the HOS+ algorithm in terms of obtaining the best optimal value and accelerating convergence solutions.
  • Küçük Resim
    Öğe
    Optimization Search Using Hypercubes
    (Institute of Electrical and Electronics Engineers Inc., 2020) Abiyev, Rahib H.; Tunay, Mustafa
    An optimization search algorithm for multivariate systems is proposed. The proposed optimization search algorithm includes initialization-, displacement-shrink- and searching areas stages. The initialization stage generates initial solutions in the search area that represented by hypercube and then evaluates the function inside this hypercube; the displacement-shrink stage calculates the displacement and updates the parameters of the hypercube; the searching areas stage using certain rules find the next hypercube. The design stages of the proposed hypercube optimization search (HOS) algorithm are presented. The proposed HOS algorithm is tested on specific benchmark functions. The experimental results on different test functions demonstrate that the HOS algorithm has shown to be a promising approach for finding the solutions of a set of optimization problems. © 2020 IEEE.