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Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation
H.H. Li 1, H.R. Fu 2, W.H. Li 3

Anyang University, Anyang, Henan 455000, China,
Anyang Normal University, Anyang, Henan 455000, China,
School of Transportation, Southeast University, Nanjing, Jiangsu 211189, China

 PDF, 1128 kB

DOI: 10.18287/2412-6179-CO-732

Pages: 154-160.

Full text of article: English language.

Abstract:
With the development of economy, the distribution problem of logistics becomes more and more complex. Based on the traffic network data, this study analyzed the vehicle routing problem (VRP), designed a dynamic vehicle routing problem with time window (DVRPTW) model, and solved it with genetic algorithm (GA). In order to improve the performance of the algorithm, the genetic operation was improved, and the output solution was further optimized by hill climbing algorithm. The analysis of example showed that the improved GA algorithm had better performance in path optimization planning, the total cost of planning results was 31.44 % less than that of GA algorithm, and the total cost of planning results increased by 11.48 % considering the traffic network data. The experimental results show that the improved GA algorithm has good performance and can significantly reduce the cost of distribution and that research on VRP based on the traffic network data is more in line with the actual situation of logistics distribution, which is conducive to the further application of the improved GA algorithm in VRP.

Keywords:
traffic network data, logistics distribution, path optimization, genetic algorithm, time window.

Citation:
Li HH, Fu HR, Li WH. Analysis of logistics distribution path optimization planning based on traffic network data. Computer Optics 2021; 45(1): 154-160. DOI: 10.18287/2412-6179-CO-732.

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