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Cubic-Spline Expansion for Electromagnetic Imaging of Buried Multiple Conductors

ELECTROMAGNETICS 2009年第4期29卷 321-336页

作者： Chiu, Chien-Ching Tu, Ting-Chieh Wysocki, Tadeusz A. Wysock, Beata J. Lu, Hung-Cheng Tamkang Univ Dept Elect Engn Tamsui 25137 Taiwan Univ Nebraska Sch Elect Comp & Elect Engn Lincoln NE USA

We present an inverse scattering problem for recovering the shapes of multiple conducting cylinders with the immersed targets in a half-space by the genetic algorithm. Two separate perfect-conducting cylinders of unknown shapes are buried in one half-space and illuminated by a transverse magnetic plane wave from the other half-space. In the shape expansions, the cubic-spline method is utilized to describe the shapes of objects. Based on the boundary condition and the measured scattered field, we have derived a set of nonlinear integral equations, and the inverse scattering problem is reformulated into an optimization problem. The improved steady-state genetic algorithm is used to solve the global extreme solution. Here, frequency dependence on the inverse problem of buried multiple conductors is investigated. Numerical results show that the reconstruction is good in the resonant frequency range, even when the initial guesses are far different from the original shapes. On the contrary, if the frequency is too high or too low, the reconstruction becomes bad. In addition, the reconstructed errors for different distances between two conductors are investigated. It is found the reconstructed results are poor when the distance between two conductors is less than about a wavelength.

关键词： inverse problem cubic-spline Fourier series half-space steady-state genetic algorithm

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Electromagnetic imaging for a conducting cylinder buried in a slab medium by the genetic algorithm

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INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2004年第1期14卷 1-7页

作者： Lin, CJ Chou, CY Chiu, CC Tamkang Univ Dept Elect Engn Tamsui Taiwan

This article presents a computational approach to the imaging of a perfectly conducting cylinder buried in a slab. A conducting cylinder of unknown shape buried in a slab scatters the incident wave from outside. The scattered field is recorded outside the slab. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived, and the imaging problem is reformulated into an optimization problem. The genetic algorithm is then employed to determine global extreme solution of the cost function. Numerical results demonstrated that, even when the initial guess is far removed from the exact one, good reconstruction can be obtained. In such a case, the gradient-based methods often are trapped in a local extreme. In addition, the effect of Gaussian noise on the reconstruction is investigated. (C) 2004 Wiley Periodicals, Inc.

关键词： electromagnetic imaging slab medium conductor steady-state genetic algorithm

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A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints

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Journal of Zhejiang University-Science C(Computers and Electronics) 2011年第12期12卷 965-975页

作者： Lei ZHANG Mattias LAMPE Zhi WANG State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou 310027 China Corporate Technology Siemens Ltd. Beijing 100102 China

With the advance of automation technology,the scale of industrial communication networks at field level is *** real-time performance of these networks is therefore becoming an increasingly difficult *** paper addresses the optimization of device allocation in industrial Ethernet networks with real-time constraints (DAIEN-RC).Considering the inherent diversity of real-time requirements of typical industrial applications,a novel optimization criterion based on relative delay is proposed.A hybrid genetic algorithm incorporating a reduced variable neighborhood search (GA-rVNS) is developed for *** results show that the proposed novel scheme achieves a superior performance compared to existing schemes,especially for large scale industrial networks.

关键词： Optimization Real-time Industrial Ethernet Device allocation steady-state genetic algorithm Variable neighbor-hood search

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Microwave imaging of a partially immersed non-uniform conducting cylinder

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INTERNATIONAL JOURNAL OF APPLIED ELECTROMAGNETICS AND MECHANICS 2012年第3期40卷 215-225页

作者： Chien, Wei Chiu, Chien-Ching Li, Ching-Lieh Sun, Chi-Hsien De Lin Inst Technol Dept Elect Engn Taipei Taiwan Tamkang Univ Dept Elect Engn Tamsui Taiwan

In this paper, we investigate the imaging problem to determine both the shape and the conductivity of a partially immersed non-uniform conducting cylinder from the knowledge of scattered far-field pattern of TM waves by solving the ill-posed nonlinear equation. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the inverse problem is reformulated into an optimization one. The steady-state genetic algorithm is then employed to find out the global extreme solution of the object function. As a result, the shape and the conductivity of the conductor can be obtained. Numerical results are given to demonstrate that even in the presence of noise, good reconstruction can be obtained.

关键词： Inverse problem partially immersed non-uniform conducting cylinder steady-state genetic algorithm

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Robot navigation by waypoints

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2008年第2期52卷 175-207页

作者： Wang, Yang Mulvaney, David Sillitoe, Ian Swere, Erick Univ Loughborough Dept Elect & Elect Engn Loughborough LE11 3TU Leics England Dunstaffnage Marine Res Lab Scottish Assoc Marine Sci Oban PA37 1QA Argyll Scotland

In this paper we propose a novel waypoint-based robot navigation method that combines reactive and deliberative actions. The approach uses reactive exploration to generate waypoints that can then be used by a deliberative system to plan future movements through the same environment. The waypoints are used largely to provide the interface between reactive and deliberative navigation and a range of methods could be used for either type of navigation. In the current work, an incremental decision tree method is used to navigate the robot reactively from the specified initial position to its destination avoiding obstacles in its path and a genetic algorithm method is used to perform the deliberative navigation. The new method is shown to have a number of practical advantages. Firstly, in contrast with many deliberative approaches, complete knowledge of the environment is not required, nor is it necessary to make assumptions regarding the geometry of obstacles. Secondly, the presence of a reactive navigator means it is always possible to continue directed movements in unknown or changing environments or when time constraints become particularly demanding. Thirdly, the use of waypoints allows escape from certain obstacle configurations that would normally trap robots navigated under the control of purely reactive methods. In addition, the results presented in this paper from a number of realistic simulated environments show that the adoption of waypoints significantly reduces the time to calculate a deliberative path.

关键词： waypoint identification complex environment deterministic crowding steady-state genetic algorithm decision tree learning robot navigation mobile robotics

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VECTOR QUANTIZATION BASED ON steady-state MEMETIC algorithm

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 2010年第4期18卷 553-557页

作者： Ou, Chien-Min Ching Yun Univ Dept Elect Engn Chungli Taiwan

A novel memetic algorithm (MA) for the design of vector quantizers (VQs) is presented in this paper. The algorithm uses steady-state genetic algorithm (GA) for the global search and K-means algorithm for the local improvement. As compared with the usual MA using the generational GA for global search, the proposed MA dramatically reduces the computational time for VQ training. In addition, it attains a near global optimal solution, and its performance is insensitive to the selection of initial codewords. Numerical results show that it can save more than 70% of computation time while maintaining a comparable performance as previous MA.

关键词： memetic algorithm vector quantizer steady-state genetic algorithm

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Image reconstruction of a buried perfectly conducting cylinder illuminated by transverse electric waves

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INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2005年第6期15卷 261-265页

作者： Chen, YC Chen, YF Chiu, CC Chang, CY Tamkang Univ Dept Elect Engn Tamsui Taiwan

This article presents a computational approach to the image reconstruction of a perfectly conducting cylinder illuminated by transverse electric waves. A perfectly conducting cylinder of unknown shape buried in one half-space and scatters the incident wave from another half-space where the scattered field is recorded. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived, and the imaging problem is reformulated into an optimization problem. The steady state genetic algorithm is then employed to find out the global extreme solution of the cost function. Numerical results demonstrated that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In such a case, the gradient-based methods often get trapped in a local extreme. In addition, the effect of different noise on the reconstruction is investigated. (C) 2006 Wiley Periodicals, Inc.

关键词： electromagnetic imaging transverse electric half-space structure perfect conductor steady-state genetic algorithm

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A Hybrid heuristic for the minimum weight vertex cover problem

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2006年第2期23卷 273-285页

作者： Singh, Alok Gupta, Ashok Kumar Univ Allahabad Fac Sci JK Inst Appl Phys & Technol Allahabad 211002 Uttar Pradesh India

Given an undirected graph with weights associated with its vertices, the minimum weight vertex cover problem seeks a subset of vertices with minimum sum of weights such that each edge of the graph has at least one endpoint belonging to the subset. In this paper, we propose a hybrid approach, combining a steady-state genetic algorithm and a greedy heuristic, for the minimum weight vertex cover problem. The genetic algorithm generates vertex cover, which is then reduced to minimal weight vertex cover by the heuristic. We have evaluated the performance of our algorithm on several test problems of varying sizes. Computational results show the effectiveness of our approach in solving the minimum weight vertex cover problem.

关键词： combinatorial optimization greedy heuristic minimum weight vertex cover steady-state genetic algorithm

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Hybrid evolutionary approaches for the single machine order acceptance and scheduling problem

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APPLIED SOFT COMPUTING 2017年 52卷 725-747页

作者： Chaurasia, Sachchida Nand Singh, Alok Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

This paper presents two hybrid metaheuristic approaches, viz. a hybrid steady-state genetic algorithm (SSGA) and a hybrid evolutionary algorithm with guided mutation (EA/G) for order acceptance and scheduling (OAS) problem in a single machine environment where orders are supposed to have release dates and sequence dependent setup times are incurred in switching from one order to next in the schedule. OAS problem is an NP-hard problem. We have compared our approaches with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approaches. (C) 2016 Elsevier B.V. All rights reserved.

关键词： steady-state genetic algorithm Estimation of distribution algorithm Evolutionary algorithm Guided mutation Order acceptance and scheduling Single machine scheduling Sequence dependent setup time

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A new hybrid genetic algorithm for the maximally diverse grouping problem

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2019年第10期10卷 2921-2940页

作者： Singh, Kavita Sundar, Shyam Natl Inst Technol Raipur Dept Comp Applicat Raipur 492010 Madhya Pradesh India

This paper presents a new hybrid approach (NSGGA) combining steady-state grouping genetic algorithm with a local search for the maximally diverse grouping problem (MDGP) related to equal group-size. The MDGP is a well-known NP-Hard combinatorial optimization problem and finds numerous applications in real world. NSGGA employs particularly (a) crossover operator (b) the effective way of utilization of local search and (c) the additional replacement strategy, making it different from the existing genetic algorithm for the MDGP. On a set of large benchmark instances, NSGGA is competitive in comparison to the existing best-known approaches in the literature and performs particularly well on large-size instances. Some important ingredients of NSGGA that shed some light on the adequacy of NSGGA are analyzed.

关键词： Maximally diverse grouping problem steady-state genetic algorithm Crossover Replacement strategy Local search

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