scholarly journals Optimization Algorithm and Simulation of Public Resource Emergency Scheduling Based on Wireless Sensor Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi Zhou ◽  
Weili Xia
Keyword(s):  
Genetic Algorithm ◽  
Resource Scheduling ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Algorithm Optimization ◽  
Use Of Resources ◽  
Public Resource ◽  
Rational Allocation ◽  
Public Resources ◽  
Effective Use

Public resource scheduling refers to the rational allocation and effective use of resources, while public emergency scheduling refers to the rational allocation and effective use of resources in the context of emergencies. Its main purpose is to reduce casualties and property losses caused by emergencies. This paper mainly studies the emergency scheduling of public resources based on line sensing technology and solves the scheduling problem of public resources through algorithm optimization. Firstly, combined with the positioning algorithm of wireless sensor, this paper optimizes the positioning and detection technology of wireless sensor technology. Then, we design an improved multiagent genetic algorithm (MAGA-MTERS) using natural number coding and design a penalty function to solve the model. Then, the algorithm is compared with the traditional genetic algorithm. The results show that the accurate positioning of wireless sensor technology can improve the efficiency of public resource scheduling and save the scheduling cost. The multiagent genetic algorithm optimizes the positioning function of wireless sensor. Compared with the traditional genetic algorithm, MAGA-MTERS algorithm can obtain a better solution.

scholarly journals Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Linna Li ◽  
Renjun Liu
Keyword(s):  
Genetic Algorithm ◽  
Human Resources ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Time Consumption ◽  
Public Resource ◽  
Public Resources ◽  
Benefit Function ◽  
The Cost ◽  
Better Than

The management of public resources means that people’s governments at all levels and other public administrative subjects should use certain means and methods, follow certain principles, rationally allocate and utilize public resources, and maximize their functions and benefits. Under the background of limited human resources, this study adheres to the principle of maximizing the benefits of human resources and rationally allocates the use of human resources. In this study, this kind of resource allocation problem is regarded as a linear programming problem by specifying the benefit function, and then, genetic algorithm, ant colony algorithm, and hybrid genetic-ant colony algorithm are used to solve the problem; the cost and time consumption of different algorithms under different scales are evaluated. Finally, it is found that genetic algorithm is superior to ant colony algorithm when the task scale is small and the effect of genetic algorithm is lower than ant colony algorithm with the expansion of task scale, whereas the improved hybrid genetic-ant colony algorithm is better than ordinary algorithm in general.

scholarly journals Construction of Wireless Underground Footwork Mobile Training and Monitoring Sensor Network in Venues of Major Sports Events

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yang Wen ◽  
Fangliang Yu
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Network Management ◽  
Sensor Network ◽  
Working Life ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Sports Events ◽  
Movement Ability ◽  
Multiagent Cooperation

At the Summer Olympics in Tokyo, technology was used extensively in major sports events. The level of foot movement ability greatly affects the performance of sports technology. Modern sports are developing in the direction of high speed, high skills, flexibility, and rapidity, and more and more reflect the important position of reasonable and accurate foot movement ability in sports. This article uses wireless sensor technology and wireless communication technology to design the overall architecture of the wireless underground footwork mobile training and monitoring network in venues of major sports events. According to the determined monitoring parameters and data transmission plan, a wireless remote monitoring data acquisition system is designed, and the hardware design, software design, and networking of the wireless monitoring node are completed, so as to realize the real-time monitoring and remote transmission of the underlying data. This paper proposes a wireless sensor network management architecture and method based on multiagent cooperation and combines active and passive wireless underground footwork mobile training and monitoring for experimental verification. A multitask allocation strategy optimized for network working life is proposed. A genetic algorithm is used to model and optimize the task data report routing of cluster head nodes. The simulation experiment results show that the wireless sensor network management method based on multiagent cooperation can effectively coordinate different monitoring sensor nodes to complete the assigned monitoring tasks; the multitask assignment strategy based on a genetic algorithm can optimize the working life of the application network.

scholarly journals Emergency Scheduling Optimization Simulation of Cloud Computing Platform Network Public Resources

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dingrong Liu ◽  
Zhigang Yao ◽  
Liukui Chen
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Objective Function ◽  
Hamming Distance ◽  
Fitness Function ◽  
Initial Population ◽  
Computing Platform ◽  
Public Resource ◽  
Public Resources ◽  
Cloud Computing Platform

Emergency scheduling of public resources on the cloud computing platform network can effectively improve the network emergency rescue capability of the cloud computing platform. To schedule the network common resources, it is necessary to generate the initial population through the Hamming distance constraint and improve the objective function as the fitness function to complete the emergency scheduling of the network common resources. The traditional method, from the perspective of public resource fairness and priority mapping, uses incremental optimization algorithm to realize emergency scheduling of public resources, neglecting the improvement process of the objective function, which leads to unsatisfactory scheduling effect. An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. Experimental results show that the proposed method can effectively improve the efficiency of emergency resource scheduling, and the reliability of emergency scheduling is better.

GIS-based genetic algorithm optimization tool for supporting land use and land management restructuring

2007 ◽  
Vol 13 (1s) ◽  
pp. 33-37
Author(s):  
V. Makarenko ◽  
◽  
G. Ruecker ◽  
R. Sommer ◽  
N. Djanibekov ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Land Use ◽  
Land Management ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

Genetic Algorithm Based Approach to Personal Worklist Resource Scheduling

2012 ◽  
Vol 23 (7) ◽  
pp. 1702-1716 ◽  
Author(s):  
Tie-Qing DENG ◽  
Gen-Quan REN ◽  
Ying-Bo LIU
Keyword(s):  
Genetic Algorithm ◽  
Resource Scheduling
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