|
|
1.INTRODUCTIONDue to frequent earthquakes, there is an urgent need to effectively ensure the supply of emergency supplies, and to strengthen the timely dispatch of emergency rescue teams without wasting time. The post-earthquake rescue work must take into account factors such as the shortage of supplies, the vague nature of the demand at the disaster site, the damage to the transportation road, the prolonged transportation time, the loss of the affected people, and the fairness of material distribution. Therefore, how to distribute the relief materials in a fair, reasonable and timely manner? It is very important to optimize distribution. In recent years, many researchers have explored the design and implementation of earthquake emergency material dispatch research, and achieved good results1. For example, Modena C in the United States believes that a scientific, efficient, fair and reasonable distribution plan of emergency materials can help improve the effectiveness of emergency rescue, and an inappropriate distribution plan may cause secondary damage to disaster areas and increase the degree of casualties and property losses in disaster areas2. Mascarucci M of the United Kingdom believes that material rescue is the key to meeting the survival needs and recovery and development of the disaster victims3. At present, scholars at home and abroad have carried out a lot of research on the design and implementation of earthquake emergency material dispatch research. These previous theoretical and experimental results provide a theoretical basis for the research in this paper. In this paper, under the background of improving particle swarm optimization algorithm, the design and realization of earthquake emergency material scheduling research, and through a series of experiments to verify the feasibility of the design and implementation of earthquake emergency material scheduling research. The results show that in the design and implementation of the earthquake emergency material scheduling research based on the improved particle swarm optimization algorithm, the average material satisfaction rate is higher than the minimum material satisfaction rate. The required materials can meet the minimum demand for disaster relief, so that the material distribution meets the scheduling results. 2.RELATED THEORETICAL OVERVIEW AND RESEARCH2.1Research on dispatching of earthquake emergency materials
2.2Theoretical introduction to improved particle swarm optimization algorithmIn the algorithm, the main change process of the particle’s understanding, cognition and learning of itself is as follows: first, the particle swarm understands the particle’s grasp of the current state according to the inertia weight and the particle’s own speed, and second is the particle’s own thinking based on its own experience, grasp the distance and direction between the basis of its existing position and its own historical optimal position, and finally the information sharing and cooperation between particles. The particles that reach the optimal position communicate and share information11. The information sharing mechanism of PSO enables the behaviors of individual particles to learn and learn from each other, simulates the mutual cooperation and competition between individuals and groups in the group, and finally promotes the particle development of the entire group, and finally obtains the optimal solution. The PSO optimization algorithm is to regard each motion state variable in the process of earthquake emergency material dispatch as a particle without size and weight, simulate the mutual cooperation and competition between individuals and groups in the group, and use the information sharing mode to make both individuals and groups move towards good direction of development12. The direction and distance are determined at a certain speed. The dynamic adjustment of the movement speed is mainly based on the individual learning group movement experience, and the flight speed is based on the individual learning group flight experience. Therefore, the improved particle swarm optimization algorithm can be more accurate for the real variables of the dispatching state of earthquake emergency materials. control. 3.EXPERIMENT AND RESEARCH3.1Experimental methodIn addition to ensuring the rescue efficiency, emergency relief work should also consider the fairness issues caused by the disaster situation and population in different disaster-stricken areas during the deployment of materials. When determining the distribution of emergency materials at the disaster-stricken point, the ratio of the actual material quantity obtained by the disaster-stricken point j to the demand must be greater than or equal to the minimum satisfaction rate a, that is, h ≥ input. The formula for calculating the satisfaction rate of emergency supplies at disaster site j is as follows: In the above formula, h is the emergency material satisfaction rate of disaster-affected point j; f is the sum of the resources actually allocated to demand point j by all supply points, and q is the expected material demand of disaster-affected point j. Among them, the numerator xn is the total amount of materials actually allocated to the disaster site j, and the denominator d is the demand for materials at the disaster site. 3.2Experimental requirementsIn the process of emergency decision-making, the fair distribution of emergency supplies is extremely important, but whether the distribution is fair is often a relative concept. Proportional equity is reflected in the distribution of disaster relief materials in the same proportion of the demand for materials in the disaster area. Although it can make the distribution of disaster-stricken points relatively fair to a certain extent, it cannot be ignored that adopting this method will result in less or even no relief materials allocated to disaster-stricken points with lower demand, which will lead to another The distribution of such materials is unfair. The minimum satisfaction rate λ of emergency materials is set as a threshold for the satisfaction of each demand point to the actual resources obtained (the ratio of the actual acquisition of resources to the expected demand). If it is higher than the threshold, it is considered that the scheme can obtain the minimum fairness requirements for the masses, and the corresponding scheme is relatively fair. 4.ANALYSIS AND DISCUSSION4.1Analysis of influence of emergency priority on material scheduling resultsWhether the scheme is feasible is judged by comparing and analyzing the error relationship between the required quantity of material dispatch and the shortage ratio in the design and implementation of the earthquake emergency material dispatch research. The experimental data are as follows: From the data analysis in Table 1 and Figure 1, it can be seen from the results that in the five experimental groups, the required quantities of emergency material dispatch are 9.94 tons, 6.52 tons, 4.98 tons, 7.64 tons and 5.33 tons respectively. The corresponding emergency material dispatch shortage ratios are 6.74%, 4.33%, 3.41%, 5.17% and 4.05%, respectively. Through the data comparison, it can be seen that in the process of design and implementation of the research on earthquake emergency material dispatch based on the improved particle swarm optimization algorithm, the shortage ratio of emergency material dispatch changes with the change of the required quantity of emergency material dispatch, and the two are positively correlated. Therefore, in order to control the shortage ratio of emergency material dispatch, it is necessary to control the required quantity of emergency material dispatch to meet the minimum demand for emergency material dispatch. Table 1.Analysis of the impact of emergency priority on material scheduling results.
4.2Minimum material satisfaction rate analysisBased on the improved particle swarm optimization algorithm, the design and realization of the minimum material satisfaction rate of the earthquake emergency material scheduling research are analyzed to judge the feasibility of the scheme. The experimental data is shown in the following Table 2. Table 2.Analysis of minimum material satisfaction rate.
As shown in Figure 2, through the data analysis of the design and realization of the minimum material satisfaction rate of the earthquake emergency material dispatch research based on the improved particle swarm optimization algorithm, the results are as follows, the minimum material satisfaction rate in the four sets of data is 0.454, 0.481, 0.419 and 0.432, and the average material satisfaction rates were 0.558, 0.571, 0.519 and 0.587, respectively. The results show that in the design and implementation of the earthquake emergency material scheduling research based on the improved particle swarm optimization algorithm, the average material satisfaction rate is higher than the minimum material satisfaction rate. The required materials can meet the minimum demand for disaster relief, so that the material distribution meets the scheduling results. 5.CONCLUSIONSBased on the research background of the improved particle swarm optimization algorithm, this paper firstly analyzes and designs the design and implementation of the earthquake emergency material scheduling research on the basis of the algorithm. During the design and implementation of the research on earthquake emergency material dispatch based on improved particle swarm optimization algorithm, the proportion of emergency material dispatch shortage changes with the change of the required quantity of emergency material dispatch, and the two are positively correlated. Therefore, in order to control the shortage ratio of emergency material dispatch, it is necessary to control the required quantity of emergency material dispatch to meet the minimum demand for emergency material dispatch. In the experiment of the minimum material satisfaction rate analysis, the results show that in the design and implementation of the earthquake emergency material scheduling research based on the improved particle swarm optimization algorithm, the average material satisfaction rate is higher than the minimum material satisfaction rate. The results show that in the process of dispatching emergency materials for earthquakes, the required materials can meet the minimum demand for disaster relief, so that the distribution of materials can meet the dispatching results. ACKNOWLEDGEMENTSThis work was supported by the Joint open fund project of Anhui Mencheng National Geophysical Observatory Key Fund No. MENGO-202114. REFERENCESVaradharajan, V. and Tupakula, U.,
“On the design and implementation of an integrated security architecture for cloud with improved resilience,”
IEEE Transactions on Cloud Computing, 5
(3), 375
–389
(2019). https://doi.org/10.1109/TCC.2016.2535320 Google Scholar
Modena, C., Valluzzi, M. R., Porto, F. D., et al.,
“Structural aspects of the conservation of historic masonry constructions in seismic areas: Remedial measures and emergency actions,”
International Journal of Architectural Heritage, 5
(4-5), 539
–558
(2021). https://doi.org/10.1080/15583058.2011.569632 Google Scholar
Mascarucci, M. and Giannotti,R.,
“Sustainable, materials, components and technologies: green and smart proposals for the post earthquake reconstruction in the territory of L’Aquila,”
74
(6), 53
–65 Abruzzo, Italy),2021). Google Scholar
Schmehl, A., Mairoser, T., Herrnberger, A., et al.,
“Design and realization of a sputter deposition system for the in situ- and in operando-use in polarized neutron reflectometry experiments,”
North-Holland, 21
(1), 88
–94
(2020). Google Scholar
Nie, S. M., Ping, H. E. and Li, H.-T.,
“The design and realization of the information system for Guangdong Commanding Center of Earthquake Emergency Response,”
South China Journal of Seismology, 21
(1), 88
–94
(2020). Google Scholar
Bader, B., Berlin, W. and Demes, M.,
“Interdisciplinary research for the development and realization of a structural component in multi-material design suitable for mass scale production,”
9
(1), 1
–16
(2021). Google Scholar
Abtahi, P. and Samali, B.,
“Evaluation of in-plane and out-of-plane movement of facade panels to reduce structure response during earthquake excitation,”
in Proceedings of the 23rd Australasian Conference on the Mechanics of Structures and Materials (ACMSM23),
53
–65
(2020). Google Scholar
Wei, B., Song, P. and Ying, Z.,
“Design and realization of information sharing platforms for train operation dispatching and command system,”
Railway Signaling & Communication, 29
(3), 242
–249
(2020). Google Scholar
Razmjooy, S., et al.,
“Design and realization of distribution route planning system of power grid operation and maintenance materials,”
Logistics Technology, 36
(05), 1
–23
(2019). Google Scholar
Voermans, W.,
“Design and realization of earthquake emergency response system,”
Science of Surveying and Mapping, 115
(1), 120
–150
(2020). Google Scholar
Zhao, Q.,
“Design and realization of the software with automatic generating earthquake briefing in Xinjiang,”
Seismological and Geomagnetic Observation and Research, 31
(5), 1257
–1273
(2021). Google Scholar
Hassan, C.,
“Design and realization of earthquake emergency equipment information management system,”
Technology for Earthquake Disaster Prevention, 135
(3), 131
–161
(2021). Google Scholar
|
