Research on UAV Route Planning Technology Based on Evolutionary Algorithm

2022 ◽  
pp. 1179-1184
Author(s):  
Hancheng Zhang
Keyword(s):  
Evolutionary Algorithm ◽  
Route Planning

Integration of a Geographic Information System and Evolutionary Computation for Automatic Routing in Coastal Navigation

2010 ◽  
Vol 63 (2) ◽  
pp. 323-341 ◽  
Author(s):  
Ming-Cheng Tsou
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Evolutionary Algorithm ◽  
Evolutionary Computation ◽  
Spatial Data ◽  
Planning Process ◽  
Route Planning ◽  
Geographic Information ◽  
Environmental Information ◽  
Two Phase

Suitable route planning is related to the safety and economy of navigation. However, route planning has become increasingly complex over the years and the planning process requires a large amount of oceanic environmental information. In order to use the oceanic environmental information effectively and improve the efficiency of route planning, this research employed a Geographic Information System (GIS) as the platform for enabling two-phase automatic route generation design. Firstly, through GIS's spatial data management, spatial analysis and geometric computation capability, the presence of the obstacle is detected and candidate routes are automatically generated. These are provided to the evolutionary algorithm as the basis for preliminary population calculation. Then, a specially designed evolutionary algorithm is used for route elimination to obtain the optimal route, resulting in the most-recommended routes that encompass safety and economy. This technique is more efficient than evolutionary computation techniques that use traditional random searches. At the same time, this targets safety and economy, providing a reference for developing a route planning strategy.

Comparisons of a Multi-Objective Compromise Weight Model and a Multi-Objective Evolutionary Algorithm in Hazmat Transportation Route Planning

2020 ◽  
pp. 036119812096523
Author(s):  
Ta-Yin Hu ◽  
Yu-Cheng Hsu ◽  
Tsai-Yun Liao
Keyword(s):  
Evolutionary Algorithm ◽  
Route Planning ◽  
Careful Consideration ◽  
City Government ◽  
Multi Objective ◽  
Solution Algorithms ◽  
Hazmat Transportation ◽  
Transportation Route ◽  
Kaohsiung City ◽  
Weight Model

On July 31, 2014, a series of gas pipeline explosions occurred in Kaohsiung City, causing 32 deaths and 321 injuries. Following this accident, the Kaohsiung City government decided to replace the use of pipelines with trucks for transporting hazmat, transfering the risk from beneath the road to the surface. This means that careful consideration needs to be given to safety and cost in hazardous material (hazmat) transportation route planning. The issue of how to design optimal routes for the transportation of hazmat is, therefore, important and involves consideration of various criteria. This research focuses on three objectives: cost, risk, and emergency response capability. It then constructs two solution algorithms, the compromise weight model and the evolutionary algorithm, to solve the multi-objective problem. The results from these two algorithms are observed and compared. In addition, this research also provides some recommendations for stakeholders, including the hazmat industry, government, and residents.

Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

Informatica ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Ernestas Filatovas ◽  
Olga Kurasova ◽  
Karthik Sindhya
Keyword(s):  
Evolutionary Algorithm ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective
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