An experimental study on electromagnetic inverse scattering of a perfectly conducting cylinder by using the real-coded genetic algorithm

2001 ◽  
Vol 30 (5) ◽  
pp. 315-320 ◽  
Author(s):  
Anyong Qing
Keyword(s):  
Genetic Algorithm ◽  
Experimental Study ◽  
Inverse Scattering ◽  
The Real ◽  
Conducting Cylinder ◽  
Real Coded Genetic Algorithm ◽  
Electromagnetic Inverse Scattering

scholarly journals A Search History-Driven Offspring Generation Method for the Real-Coded Genetic Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Takumi Nakane ◽  
Xuequan Lu ◽  
Chao Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Operators ◽  
The Real ◽  
Model Driven ◽  
The Past ◽  
Limited Budget ◽  
Real Coded Genetic Algorithm ◽  
Quantitative Results ◽  
Offspring Generation ◽  
Search History

In evolutionary algorithms, genetic operators iteratively generate new offspring which constitute a potentially valuable set of search history. To boost the performance of offspring generation in the real-coded genetic algorithm (RCGA), in this paper, we propose to exploit the search history cached so far in an online style during the iteration. Specifically, survivor individuals over the past few generations are collected and stored in the archive to form the search history. We introduce a simple yet effective crossover model driven by the search history (abbreviated as SHX). In particular, the search history is clustered, and each cluster is assigned a score for SHX. In essence, the proposed SHX is a data-driven method which exploits the search history to perform offspring selection after the offspring generation. Since no additional fitness evaluations are needed, SHX is favorable for the tasks with limited budget or expensive fitness evaluations. We experimentally verify the effectiveness of SHX over 15 benchmark functions. Quantitative results show that our SHX can significantly enhance the performance of RCGA, in terms of both accuracy and convergence speed. Also, the induced additional runtime is negligible compared to the total processing time.

GENETINIO ALGORITMO TAIKYMAS ŽEMĖS SKLYPŲ RIBŲ TOPOLOGIJAI OPTIMIZUOTI NEKILNOJAMOJO TURTO KADASTRO ŽEMĖLAPYJE / АЛГОРИТМ ДЛЯ ОПТИМИЗАЦИИ ТОПОЛОГИИ ГРАНИЦ ЗЕМЕЛЬНЫХ УЧАСТКОВ НА КАДАСТРОВОЙ КАРТЕ НЕДВИЖИМОГО ИМУЩЕСТВА

2011 ◽  
Vol 37 (2) ◽  
pp. 84-90 ◽  
Author(s):  
Irina Jonauskienė ◽  
Algimantas Zakarevičius ◽  
Vladislovas Česlovas Aksamitauskas ◽  
Dmitrij Šešok
Keyword(s):  
Genetic Algorithm ◽  
Experimental Study ◽  
Genetic Algorithms ◽  
Real Estate ◽  
Turning Points ◽  
The Real ◽  
The Real Estate

Discrepancies between adjacent parcel boundaries happen when marking the boundaries of land parcels in the real estate cadastre map, for example, gaps, overlaps etc. In cases where the coordinates of land turning points meet statutory admissibility, the topology of land boundaries is adjusted. The paper addresses issues related to the application of genetic algorithms for optimizing the topology of land boundaries. When applying the genetic algorithm, for the purpose of optimizing the topology of the boundaries of land parcels, methodological justification and experimental study are employed. Santrauka Žymint žemės sklypų ribas nekilnojamojo turto kadastro žemėlapyje pasitaiko nesutapimų tarp gretimų sklypų ribų, t. y. atsiranda tarpai arba susidaro sanklotos. Tais atvejais, kai žemės sklypų posūkio taškų koordinatės atitinka teisės aktais nustatytus leistinumus, derinama žemės sklypų ribų topologija. Straipsnyje nagrinėjami klausimai, susiję su genetinių algoritmų taikymu žemės sklypų ribų topologijai optimizuoti. Atliktas genetinio algoritmo taikymo tam tikslui metodologinis pagrindimas ir eksperimentinis tyrimas. Резюме При обозначении границ земельных участков на кадастровой карте недвижимого имущества между границами смежных участков могут возникнуть расхождения, то есть появиться пробелы или пересечения. Когда координаты границ земельных участков не превышают предусмотренной правовыми и нормативными актами приемлемости, корректируется топология границ земельных участков. В статье рассмотрены вопросы, касающиеся применения генетических алгоритмов для оптимизации топологии границ земельных участков. Разработана методология применения генетического алгоритма для оптимизации топологии границ земельных участков и выполнено экспериментальное исследование.

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