Emergency airport site selection using global subdivision grids

Han, Bing; Qu, Ting; Huang, Zili; Wang, Qiangyu; Pan, Xinlong

doi:10.1080/20964471.2021.1996866

Cited by 12 publications

(4 citation statements)

References 24 publications

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“…According to the bird ecological conservation data, Zhao, B. et al [16] evaluated the impact of the different droneport site selection schemes on bird ecology and then selected a more suitable site for the sustainable development of humans and nature. An emergency droneport site selection was proposed in [17] based on the GeoSOT-3D global subdivision grid model, which verifies that the discrete global grid system has good suitability when performed as a spatial data structure for site selection. Liao, Y. and Bao, F. [18] introduced the fuzzy decision-making thesis to evaluate different droneport site selection methods, which defined the dominance degree among the methods for evaluation by using the difference between the two triangular fuzzy numbers.…”

Section: Introductionmentioning

confidence: 79%

A Route Planning Method for UAV Swarm Inspection of Roads Fusing Distributed Droneport Site Selection

Zhong,

Ye,

Liu

et al. 2023

Sensors

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Current methods that use Unmanned Aerial Vehicle (UAV) swarms to inspect roads still have many limitations in practical applications, such as the lack of or difficulty in the route planning, the unbalanced utilization rate of the UAV swarm and the difficulty of the site selection for the distributed droneports. To solve the limitations, firstly, we construct the inspection map and remove the redundant information irrelevant to the road inspection. Secondly, we formulate both the route planning problem and the droneport site selection problem in a unified multi-objective optimization model. Thirdly, we redesign the encoding strategy, the updating rules and the decoding strategy of the particle swarm optimization method to effectively solve both the route planning problem and the droneport site selection problem. Finally, we introduce the comprehensive evaluation indicators to verify the effectiveness of the route planning and the droneport site selection. The experimental results show that (1) with the proposed method, the overlapped part of the optimized inspection routes is less than 7% of the total mileage, and the balanced utilization rate of the UAVs is above 75%; (2) the reuse rate of the distributed droneports is significantly improved after optimization; and (3) the proposed method outperforms the ant colony optimization (ACO) method in all evaluation indicators. To this end, the proposed method can effectively plan the inspection routes, balance the utilization of the UAVs and select the sites for the distributed droneports, which has great significance for a fully autonomous UAV swarm inspection system for road inspection.

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Section: Introductionmentioning

confidence: 79%

A Route Planning Method for UAV Swarm Inspection of Roads Fusing Distributed Droneport Site Selection

Zhong,

Ye,

Liu

et al. 2023

Sensors

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“…emergency materials via vehicles to cope with the sudden outbreak of the epidemic. In addition, similar to the logistics distribution center of emergency facilities, the siting problem is also reflected in the subway fire emergency station siting, chemical park emergency supplies warehouse siting, and so on [30][31][32][33][34].…”

Section: Model Assumptionsmentioning

confidence: 99%

“…The authors of [ 29 ] take the emerging coronavirus pneumonia epidemic as the research background, establish a multi-objective mathematical model with the highest vehicle utilization rate and the lowest transportation costs for the study of the emergency material distribution problem, and propose a hybrid multi-inverse optimization algorithm for the experimental simulation, and the computational results provide a solution for the optimization of the distribution of emergency materials via vehicles to cope with the sudden outbreak of the epidemic. In addition, similar to the logistics distribution center of emergency facilities, the siting problem is also reflected in the subway fire emergency station siting, chemical park emergency supplies warehouse siting, and so on [ 30 , 31 , 32 , 33 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

The Application of the Improved Jellyfish Search Algorithm in a Site Selection Model of an Emergency Logistics Distribution Center Considering Time Satisfaction

Ping

Fan

2023

Biomimetics

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In an emergency situation, fast and efficient logistics and distribution are essential for minimizing the impact of a disaster and for safeguarding property. When selecting a distribution center location, time satisfaction needs to be considered, in addition to the general cost factor. The improved jellyfish search algorithm (CIJS), which simulates the bionics of jellyfish foraging, is applied to solve the problem of an emergency logistics and distribution center site selection model considering time satisfaction. The innovation of the CIJS is mainly reflected in two aspects. First, when initializing the population, the two-level logistic map method is used instead of the original logistic map method to improve the diversity and uniform distribution of the population. Second, in the jellyfish search process, a Cauchy strategy is introduced to determine the moving distance of internal motions, which improves the global search capability and prevents the search from falling into local optimal solutions. The superiority of the improved algorithm was verified by testing 20 benchmark functions and applying them to site selection problems of different dimensions. The performance of the CIJS was compared to that of heuristic algorithms through the iterative convergence graph of the algorithm. The experimental results show that the CIJS has higher solution accuracy and faster solution speed than PSO, the WOA, and JS.

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“…Usage of site location decision methods is becoming more diverse each year, as more research of different fields researchers tries to provide a solution for their different study. For example those methods are used in warehouse site selection [1], school site selection [2], logistics site selection [3], wind farm site selection [4], Emergency airport site selection [5], cross-docking center location selection [6], sustainable offshore wind energy stations location selection [7], hospital site selection [8], ideal business location selection [9], retail shop site selection [10], solar site selection [11], power plant site selection [12], landfill site selection [13], textile manufacturing facility site selection [14] etc. Combined with the deployment requirements of AG600 and the application characteristics of various evaluation methods, this paper selects TOPSIS method as the evaluation method for AG600 site selection decision.…”

Section: Introductionmentioning

confidence: 99%

AG600 Maritime Base Location Decision Based on the Interval Intuitionistic Fuzzy TOPSIS Method

Wei

Wang

et al. 2022

IEEE Access

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Aiming at the location research blank of the AG600 amphibious aircraft marine rescue base, the location decision index system of the AG600 is established, and the AG600 location decision model based on the interval intuitionistic fuzzy theory and improved TOPSIS method is constructed. Through investigation and statistical analysis, the evaluation system with 10 indices is determined based on applicability, safety, and accessibility, and in the process of quantization of index assignment, a fuzzy conversion method for different indices is proposed. The interval intuitionistic fuzzy number of each index is obtained by combining objective calculation and subjective assignment, and the interval intuitionistic fuzzy decision matrix is constructed. The fuzzy entropy method is used to calculate the index weight, and then the improved Technique for Order of Preference by Similarity (TOPSIS) is used to evaluate and rank the rescue bases. The scientific and reasonable location decision results are obtained. Finally, taking the South China Sea islands as an example, the correctness and reliability of the proposed model is verified by comparison with the calculation results of the score function method and the projection method.INDEX TERMS AG600 amphibious aircraft, interval intuitionistic fuzzy TOPSIS, location decision, marine rescue base.

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Emergency airport site selection using global subdivision grids

Cited by 12 publications

References 24 publications

A Route Planning Method for UAV Swarm Inspection of Roads Fusing Distributed Droneport Site Selection

A Route Planning Method for UAV Swarm Inspection of Roads Fusing Distributed Droneport Site Selection

The Application of the Improved Jellyfish Search Algorithm in a Site Selection Model of an Emergency Logistics Distribution Center Considering Time Satisfaction

AG600 Maritime Base Location Decision Based on the Interval Intuitionistic Fuzzy TOPSIS Method

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