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一种高效的登机策略 被引量:8

Adaptive Approach to Aircraft Boarding Strategy
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摘要 随着航空领域业务量的增加,减少飞机的回航时间变得越来越重要.主要研究了减少飞机回航时间的最佳登机策略.针对小型机,建立了混合整数非线性规划模型,定义登机时间主要决定于座位的冲突时间和走廊的冲突时间,并采用GASimplex算法(一种遗传算法与单纯形法结合的算法)求解该模型.针对中型机,建立了基于蒙特卡罗模拟模型.然后,我们综合了前面两个模型来解决大型机的问题.应用matlab6.5实现了模型的求解,我们发现倒金字塔形和旋转形相结合的登机策略要比其他的策略更有效.最后,我们分析了模型的稳定性和准确性. As air travel business grows larger,it is more and more important to reduce the plane's turnaround minute.In this paper,we try to find an optimum boarding strategy,so as to reduce the turnaround time.For small-size planes,we set up a Mixed-integer Nonlinear Programming model,in which the boarding time depends mainly on the interference taking place in the seat sections and the aisles,and give a solution to this model using GASimplex Algorithm(a combination of Genetic Algorithms and Simplex method).For middle-size planes,we take Monte Carlo Simulation model which is based on probabilistic aspect.After this,we integrate these two models to make a solution for the problem of large-size planes.Based on the realization of our models with the aid of toolbox of Matlab6.5,we discover that the boarding strategy combining Reverse Pyramid with Rotation outperforms other strategies.Finally,we analyze the stability and sensibility of the model.
机构地区 北京交通大学
出处 《交通运输系统工程与信息》 EI CSCD 2008年第5期118-123,共6页 Journal of Transportation Systems Engineering and Information Technology
关键词 混合整数非线性规划 遗传算法 单纯形法 蒙特卡罗模拟 MINPL genetic algorithms simplex method monte carlo simulation
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  • 1Geoffrion, A.M. Generalized Benders Decomposition [J]. Journal of Optimization Theory and Applications 1972, 10(4): 237-260.
  • 2Duran M A, I E Grossmann. An Outer Approximation Algorithm for a Class of Mixed Integer Nonlinear Programs [J]. Mathematical Programming 36: 307-339. 1986.
  • 3Grossman, I. E. Mixed-Integer Nonlinear Programming Techniques for the Synthesis of Engineering Systems [J]. Research in Engineering Design. 1. pp: 205-228. 1990.
  • 4Sahinidis N, I E Grossmann. MINLP Model for Scheduling in Continuous Parallel Production Lines [C]. Presented at AIChE meeting, San Francisco, CA. 1989.
  • 5Mordecal Avriel. Nonlinear Programming Analysis and Methods [M]. Prentice-Hall, Inc. 1976.
  • 6Leonard W. Swanson. Linear programming - basic theory and applications [M]. McGraw-Hill Book Company. 1980.
  • 7Renders J M, Flasse S P. Hybrid methods using genetic algorithms for global optimization. System, Man, and Cybernetics, Part B [J]. IEEE Transactions on, 1996, 26 (2): 243 -258.
  • 8J A Joines, M G Kay, R E King. A hybrid-genetic algorithm for manufacturing cell design. Technical Report NCSU-IE [R]. Department of Industrial Engineering, North Carolina State University, Box 7906 Raleigh, NC 276957906, February 1997.
  • 9R Chelouah, P Siarry. A continuous genetic algorithm designed for the global optimization of multimodal functions [J]. Journal of Heuristics 6. pp: 191-213, 2000.
  • 10N Durand, J M Alliot. A combined Nelder-Mead simplex and genetic algorithm, in: W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon, V. Honavar, M. Jakiela, R.E. Smith (Eds.) [C]. Proceedings of the Genetic and Evolutionary Computation Conference GECCO'99, Morgan Kaufmann, Orlando, FL, USA, 1999, 1-7.

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