scholarly journals Research on Airport Scheduling of FGAP Multi-Objective Programming Model Based on Uncertainty Theory

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1915
Author(s):  
Xijian Hu ◽  
Jiaqi Teng ◽  
Wei Wu ◽  
Yan Li ◽  
Yuhong Sheng

Based on the current background of airport management and flight-gate scheduling in China, this paper takes Shanghai Pudong International Airport’s flight number of the rising and landing aircraft in a certain day as the research object, and it establishes an uncertain FGAP (Flight-Gate Assignment Problem) multi-objective programming model under the framework of uncertainty theory. Using genetic algorithm to solve the model, the specific flight-gate assignment scheduling plan is given. The research results show that the model in this paper can effectively alleviate the problems, such as unbalanced flight-gate allocation and excessive operating pressure of a single gate, in the conventional model, and make the allocation and scheduling more reasonable and efficient. Finally, we give the future application of uncertainty theory in finance and management, as well as the prospect of combining it with symmetry in physics.

2021 ◽  
pp. 1-10
Author(s):  
Zhaoping Tang ◽  
Wenda Li ◽  
Shijun Yu ◽  
Jianping Sun

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.


2014 ◽  
Vol 538 ◽  
pp. 127-133 ◽  
Author(s):  
Zhao Ning Zhang ◽  
Zhong Zhou Hao ◽  
Zheng Gao

To alleviate the conflicts between the current flight traffic demand and the resource constraints of airspace, we need to improve the restrictions of flow allocation caused by the static air traffic flow allocation mode. The author analyzes the optimal allocation problem of dynamic adjusting flight flow and draws the conclusion that the problem should satisfy multiple targets, such as low flight delays, low flight cost and balancing the load of the route. Then consider a variety of limiting factors, such as the capacity of the route, flight planning, emergency situations, etc. Then establish multi-objective programming model of dynamic adjusting flight traffic. The objective function is determined by the flight cost, the flight delays and the value of the load balance. And the value of the load balance was first proposed according to the idea of least squares method. Then solve the model based on linear weighted technique. Finally the numerical result shows that the model can satisfy the multiple objectives and dynamic adjust the flight traffic optimally, that proves the rationality and validity of the model and the algorithm.


2014 ◽  
Vol 707 ◽  
pp. 525-531
Author(s):  
Ze Ming Jiang ◽  
Cong Hou

By using Analytic Hierarchy Process (AHP), a solution is given in different aspects to analyze the weight of the impacts of electric vehicles. The economic and social impacts are found out to be the key factors. When EV’s penetration rate reaches a certain level, the lowest cost, lowest harm degree to our environment and society, and maximum possibility are considered to avoid using un-renewable energy. In addition, multi-objective programming model is built to solve the problem of the amount and type of electricity generation needed that will produce the largest number of benefits.


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