Limits...
Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation.

Wen T, Zhang Z, Wong KK - PLoS ONE (2016)

Bottom Line: This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity.Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight.By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

View Article: PubMed Central - PubMed

Affiliation: Software School, Xiamen University, Xiamen, Fujian, China.

ABSTRACT
Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

No MeSH data available.


Related in: MedlinePlus

Using frequency of each proportion in Table 5 for instance E-n101-k14 according to different MaxY values.MaxY is set as 150 and 30 for (a) and (b) respectively.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4862655&req=5

pone.0155176.g011: Using frequency of each proportion in Table 5 for instance E-n101-k14 according to different MaxY values.MaxY is set as 150 and 30 for (a) and (b) respectively.

Mentions: It can be seen from Table 5 that the change of the proportion is not uniform; the proportion value increases along the time axis from small to large and decreases with the blood weight. While the MinX for blood weight has been given above, the MaxY for distance is not set yet. As shown in Fig 11, when the MaxY takes a large value, the proportion between hot water and blood is easy to be concentrated in the smaller area on the time axis; however, if the MaxY takes a small value, the proportion is easy to be concentrated in the larger area. Fig 11 shows the distribution of the proportion caused by different MaxY values. If the MaxY takes a larger value, it will result in a larger requirement of the hot water, then the total weight UAVs need to carry will increase and the more UAVs will be needed.


Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation.

Wen T, Zhang Z, Wong KK - PLoS ONE (2016)

Using frequency of each proportion in Table 5 for instance E-n101-k14 according to different MaxY values.MaxY is set as 150 and 30 for (a) and (b) respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862655&req=5

pone.0155176.g011: Using frequency of each proportion in Table 5 for instance E-n101-k14 according to different MaxY values.MaxY is set as 150 and 30 for (a) and (b) respectively.
Mentions: It can be seen from Table 5 that the change of the proportion is not uniform; the proportion value increases along the time axis from small to large and decreases with the blood weight. While the MinX for blood weight has been given above, the MaxY for distance is not set yet. As shown in Fig 11, when the MaxY takes a large value, the proportion between hot water and blood is easy to be concentrated in the smaller area on the time axis; however, if the MaxY takes a small value, the proportion is easy to be concentrated in the larger area. Fig 11 shows the distribution of the proportion caused by different MaxY values. If the MaxY takes a larger value, it will result in a larger requirement of the hot water, then the total weight UAVs need to carry will increase and the more UAVs will be needed.

Bottom Line: This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity.Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight.By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

View Article: PubMed Central - PubMed

Affiliation: Software School, Xiamen University, Xiamen, Fujian, China.

ABSTRACT
Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

No MeSH data available.


Related in: MedlinePlus