Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Air flight planning method based on particle swarm algorithm

A particle swarm algorithm and particle technology, which is applied in the field of optimizing aircraft flight planning using particle swarm algorithm to achieve the effect of flexible algorithm, simple and easy-to-understand and easy-to-execute algorithm.

Inactive Publication Date: 2009-07-08
SUN YAT SEN UNIV
View PDF0 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The invention applies the particle swarm algorithm to the solution of the aircraft flight planning problem

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Air flight planning method based on particle swarm algorithm
  • Air flight planning method based on particle swarm algorithm
  • Air flight planning method based on particle swarm algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The method of the invention will be further described below in conjunction with the accompanying drawings.

[0028] First define some variables in the aircraft flight schedule.

[0029] Variables associated with aircraft type i include, seating capacity S i , hourly flight cost C i , the daily utilization rate U i and the number of aircraft A i . Variables related to flight routes include, fare V ij and passenger load factor R ij , where j represents the route of the aircraft. In addition, with T ij Indicates the flight time (voyage) of aircraft i on route j. The variables for these questions are shown in the table below:

[0030]

[0031] The optimization goal of the aircraft flight planning problem is to optimize the flight frequency of each type of aircraft on each route under the premise of satisfying a series of constraints, so as to maximize profits. we use x ij Indicates that model i has x daily on route j ij times, then the solution to the problem...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

Flight scheduling problem is to determine the optimal flight frequency for each flight path of airplanes of each type, which has important meanings for service planning and profit maximization of airline companies. In the invention, particle swarm algorithm is applied in solving the flight scheduling problem for defining the variables, the target and the constraint conditions in the flight scheduling problem, and provides the detailed steps. The algorithm has the advantages of simple process and easy execution. The test result shows that the particle swarm algorithm can rapidly and effectively solve the flight scheduling problem.

Description

Technical field: [0001] The invention relates to two major fields of market planning and intelligent calculation, and mainly relates to a method for optimizing aircraft flight planning by using a particle swarm algorithm. technical background: [0002] The problem of aircraft flight planning is crucial to the planning and operation of airlines, and has once received great attention from the aviation industry. Flight planning refers to the allocation of limited resources (such as aircraft, routes, funds, personnel, etc.) of airlines, and stipulates the routes, models, flight frequencies and schedules of regular flights. Generally speaking, flight planning in a broad sense includes five aspects. According to the order of planning, they are market analysis and forecasting, determination of flight frequency and time, assignment of aircraft types, scheduling of aircraft and scheduling of crews. However, flight planning in a narrow sense only includes the first three aspects. Th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/00G06Q10/06
Inventor 张军詹志辉黄韬
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com