• Title/Summary/Keyword: gravitational search algorithm

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Comparison of Global Optimization Methods for Insertion Maneuver into Earth-Moon L2 Quasi-Halo Orbit Considering Collision Avoidance

  • Lee, Sang-Cherl;Kim, Hae-Dong;Yang, Do-Chul;Cho, Dong-Hyun;Im, Jeong-Heum;No, Tae-Soo;Kim, Seungkeun;Suk, Jinyoung
    • International Journal of Aeronautical and Space Sciences
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    • v.15 no.3
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    • pp.267-280
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    • 2014
  • A spacecraft placed in an Earth-Moon L2 quasi-halo orbit can maintain constant communication between the Earth and the far side of the Moon. This quasi-halo orbit could be used to establish a lunar space station and serve as a gateway to explore the solar system. For a mission in an Earth-Moon L2 quasi-halo orbit, a spacecraft would have to be transferred from the Earth to the vicinity of the Earth-Moon L2 point, then inserted into the Earth-Moon L2 quasi-halo orbit. Unlike the near Earth case, this orbit is essentially very unstable due to mutually perturbing gravitational attractions by the Earth, the Moon and the Sun. In this paper, an insertion maneuver of a spacecraft into an Earth-Moon L2 quasi-halo orbit was investigated using the global optimization algorithm, including simulated annealing, genetic algorithm and pattern search method with collision avoidance taken into consideration. The result shows that the spacecraft can maintain its own position in the Earth-Moon L2 quasi-halo orbit and avoid collisions with threatening objects.

A study on estimating the interlayer boundary of the subsurface using a artificial neural network with electrical impedance tomography

  • Sharma, Sunam Kumar;Khambampati, Anil Kumar;Kim, Kyung Youn
    • Journal of IKEEE
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    • v.25 no.4
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    • pp.650-663
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    • 2021
  • Subsurface topology estimation is an important factor in the geophysical survey. Electrical impedance tomography is one of the popular methods used for subsurface imaging. The EIT inverse problem is highly nonlinear and ill-posed; therefore, reconstructed conductivity distribution suffers from low spatial resolution. The subsurface region can be approximated as piece-wise separate regions with constant conductivity in each region; therefore, the conductivity estimation problem is transformed to estimate the shape and location of the layer boundary interface. Each layer interface boundary is treated as an open boundary that is described using front points. The subsurface domain contains multi-layers with very complex configurations, and, in such situations, conventional methods such as the modified Newton Raphson method fail to provide the desired solution. Therefore, in this work, we have implemented a 7-layer artificial neural network (ANN) as an inverse problem algorithm to estimate the front points that describe the multi-layer interface boundaries. An ANN model consisting of input, output, and five fully connected hidden layers are trained for interlayer boundary reconstruction using training data that consists of pairs of voltage measurements of the subsurface domain with three-layer configuration and the corresponding front points of interface boundaries. The results from the proposed ANN model are compared with the gravitational search algorithm (GSA) for interlayer boundary estimation, and the results show that ANN is successful in estimating the layer boundaries with good accuracy.

Finite element model updating of a cable-stayed bridge using metaheuristic algorithms combined with Morris method for sensitivity analysis

  • Ho, Long V.;Khatir, Samir;Roeck, Guido D.;Bui-Tien, Thanh;Wahab, Magd Abdel
    • Smart Structures and Systems
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    • v.26 no.4
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    • pp.451-468
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    • 2020
  • Although model updating has been widely applied using a specific optimization algorithm with a single objective function using frequencies, mode shapes or frequency response functions, there are few studies that investigate hybrid optimization algorithms for real structures. Many of them did not take into account the sensitivity of the updating parameters to the model outputs. Therefore, in this paper, optimization algorithms and sensitivity analysis are applied for model updating of a real cable-stayed bridge, i.e., the Kien bridge in Vietnam, based on experimental data. First, a global sensitivity analysis using Morris method is employed to find out the most sensitive parameters among twenty surveyed parameters based on the outputs of a Finite Element (FE) model. Then, an objective function related to the differences between frequencies, and mode shapes by means of MAC, COMAC and eCOMAC indices, is introduced. Three metaheuristic algorithms, namely Gravitational Search Algorithm (GSA), Particle Swarm Optimization algorithm (PSO) and hybrid PSOGSA algorithm, are applied to minimize the difference between simulation and experimental results. A laboratory pipe and Kien bridge are used to validate the proposed approach. Efficiency and reliability of the proposed algorithms are investigated by comparing their convergence rate, computational time, errors in frequencies and mode shapes with experimental data. From the results, PSO and PSOGSA show good performance and are suitable for complex and time-consuming analysis such as model updating of a real cable-stayed bridge. Meanwhile, GSA shows a slow convergence for the same number of population and iterations as PSO and PSOGSA.

Enhancing the Quality of Service by GBSO Splay Tree Routing Framework in Wireless Sensor Network

  • Majidha Fathima K. M.;M. Suganthi;N. Santhiyakumari
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2188-2208
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    • 2023
  • Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.