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    Adaptive Flower Pollination Algorithm Based on Spatial Dispersal
    (Institute of Electrical and Electronics Engineers Inc., 2020) Ustun, Deniz; Toktas, Abdurrahim
    An adaptive flower pollination algorithm (AFPA) is evolved with respect to the accuracy and stability performance. AFPA is developed by modifying both global and local search operators. The exploration and exploitation abilities of the algorithm are thus improved by integrating a spatial dispersal mechanism adapting with the number of iterations to the global search and the best solution to the local search. Its performance is well corroborated through several benchmark functions with respect to various measuring parameters. AFPA is exhibited the distinguished accuracy and stability performance better than FPA for most benchmark functions. The obtained results show that AFPA has the better global and local search abilities over FPA. © 2020 IEEE.
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    An enhanced adaptive butterfly optimization algorithm rigorously verified on engineering problems and implemented to ISAR image motion compensation
    (Emerald Group Publishing Ltd, 2020) Ustun, Deniz
    Purpose This study aims to evolve an enhanced butterfly optimization algorithm (BOA) with respect to convergence and accuracy performance for numerous benchmark functions, rigorous constrained engineering design problems and an inverse synthetic aperture radar (ISAR) image motion compensation. Design/methodology/approach Adaptive BOA (ABOA) is thus developed by incorporating spatial dispersal strategy to the global search and inserting the fittest solution to the local search, and hence its exploration and exploitation abilities are improved. Findings The accuracy and convergence performance of ABOA are well verified via exhaustive comparisons with BOA and its existing variants such as improved BOA (IBOA), modified BOA (MBOA) and BOA with Levy flight (BOAL) in terms of various precise metrics through 15 classical and 12 conference on evolutionary computation (CEC)-2017 benchmark functions. ABOA has outstanding accuracy and stability performance better than BOA, IBOA, MBOA and BOAL for most of the benchmarks. The design optimization performance of ABOA is also evaluated for three constrained engineering problems such as welded beam design, spring design and gear train design and the results are compared with those of BOA, MBOA and BOA with chaos. ABOA, therefore, optimizes engineering designs with the most optimal variables. Furthermore, a validation is performed through translational motion compensation (TMC) of the ISAR image for an aircraft, which includes blurriness. In TMC, the motion parameters such as velocity and acceleration of target are optimally predicted by the optimization algorithms. The TMC results are elaborately compared with BOA, IBOA, MBOA and BOAL between each other in view of images, motion parameter and numerical image measuring metrics. Originality/value The outperforming results reflect the optimization and design successes of ABOA which is enhanced by establishing better global and local search abilities over BOA and its existing variants.
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    Pioneer Pareto artificial bee colony algorithm for three-dimensional objective space optimization of composite-based layered radar absorber
    (Elsevier, 2020) Toktas, Abdurrahim; Ustun, Deniz; Erdogan, Nursev
    A three-dimensional objective space (3DOS) optimization strategy using an enhanced multi-objective artificial bee colony (ABC) algorithm for the design optimization of layered radar absorbing material (LRAM) is presented in this study. The multi-objective exploitation ability of ABC is improved with regard to the convergence and diversity by integrating a pioneer Pareto (PP) solution to the onlooker bee phase, which is selected from the Pareto optimal set. Initially, the performance of PP-ABC is successfully verified by a comparison with ABC and the well-known multi-objective counterparts like particle swarm optimization (PSO) and differential evolution (DE) algorithms. The comparison is carried out through five multi-objective benchmark functions with respect to three favorable and reliable multi-objective indicators such as hypervolume (HV), HV ratio and Pareto sets proximity (PSP). The employed three objective functions to be the dimensions of 3DOS are weighted bandwidth-based total reflection coefficient involving sub-reflection waves of a wide oblique incident angular range 0 degrees-75 degrees, the total thickness and the number of layers. By using PP-ABC, a 3D designed LRAM operating at a large frequency band of 2-18 GHz is then designed for synchronously minimizing the three objective vectors by finding out the design variables: thickness and material types. Meanwhile, the material types of the proposed LRAM are optimally picked up from a composite material database with 51 specimens from 9 previously reported studies (51 /9#database). In order to point out the effectiveness of the proposed 3DOS optimization strategy, three LRAMs are also compared with respective reported designs whose material type is selected from a database with 6 specimens (6/1#database). The results show that the proposed LRAMs are hence the global optimal designs in terms of all objective functions thanks to the proposed 3DOS optimization strategy based on PP-ABC. (C) 2020 Elsevier B.V. All rights reserved.
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    Surrogate-based computational analysis and design for H-shaped microstrip antenna
    (Taylor & Francis Ltd, 2021) Ustun, Deniz; Toktas, Feyza
    A conceptual Kriging surrogate model (KSM) for the computational analysis and design of H-shaped microstrip antennas (HMAs) is proposed in this study. A dataset contains 216 simulated HMAs with different physical/electrical parameters of the HMAs and the respective resonant frequency (RF) values are employed in construction and test processes of the KSM. The performance of the KSM is tested and verified through 20 and 13 HMAs by an extensive comparison with the state-of-the-art models. The results illustrate that KSM computes the most accurate RF values of 20 and 13 HMAs with absolute percent error (APE) of 0.48% and 0.76%, respectively. Moreover, a miniaturized HMA is optimally designed through the KSM as 27% smaller than the smallest design in the dataset for operating at about 2.40 GHz. Therefore, the performance of the proposed method is validated by means of the fabrication of the miniaturized HMA.