scholarly journals Multimedia Detection and Processing of Remote-Sensing Image of Small Target Combined with Variable Neighborhood Search Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yaqin Wang ◽  
Maolong Qiu
Keyword(s):  
Remote Sensing ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Image Data ◽  
Unsupervised Classification ◽  
Neighborhood Search ◽  
Remote Sensing Images ◽  
The Earth ◽  
Small Targets ◽  
Neighborhood Search Algorithm

The development of scientific satellites has made it a reality for people to view the Earth from the sky. However, due to the resolution of the image obtained, the effective and accurate interpretation of remote-sensing images has always been one of the goals pursued by the industry. In this paper, we merge the variable neighborhood search algorithm, reduce the accuracy of remote-sensing images, clean the invalid information of the data, use unsupervised classification methods to quickly locate small targets, use it as verification information, compare and select the image data through sample information, distinguish the background and target results, and get stable detection results. Practice shows that this method can effectively detect small targets in remote-sensing images.

A variable neighborhood search algorithm for optimal protection coordination of power systems

2021 ◽  
Author(s):  
H. R. E. H. Bouchekara ◽  
M. S. Shahriar ◽  
M. S. Javaid ◽  
Y. A. Sha’aban ◽  
M. Zellagui ◽  
...  
Keyword(s):  
Power Systems ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Neighborhood Search Algorithm ◽  
Optimal Protection

scholarly journals Two meta-heuristics for solving the multi-vehicle multi-covering tour problem with a constraint on the number of vertices

2020 ◽  
pp. 14-14
Author(s):  
Manel Kammoun ◽  
Houda Derbel ◽  
Bassem Jarboui
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Descent Method ◽  
Computational Experiments ◽  
Neighborhood Search ◽  
Variable Neighborhood Descent ◽  
Covering Tour Problem ◽  
Neighborhood Search Algorithm

In this work we deal with a generalized variant of the multi-vehicle covering tour problem (m-CTP). The m-CTP consists of minimizing the total routing cost and satisfying the entire demand of all customers, without the restriction of visiting them all, so that each customer not included in any route is covered. In the m-CTP, only a subset of customers is visited to fulfill the total demand, but a restriction is put on the length of each route and the number of vertices that it contains. This paper tackles a generalized variant of the m-CTP, called the multi-vehicle multi-covering Tour Problem (mm-CTP), where a vertex must be covered several times instead of once. We study a particular case of the mm-CTP considering only the restriction on the number of vertices in each route and relaxing the constraint on the length (mm-CTP-p). A hybrid metaheuristic is developet by combining Genetic Algorithm (GA), Variable Neighborhood Descent method (VND), and a General Variable Neighborhood Search algorithm (GVNS) to solve the problem. Computational experiments show that our approaches are competitive with the Evolutionary Local Search (ELS) and Genetic Algorithm (GA), the methods proposed in the literature.

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