期刊文献+

动态时空衔接的一体化恢复 被引量:3

Integrated recovery considering dynamic space-time connection
原文传递
导出
摘要 针对恶劣天气、飞机故障等因素导致的不正常航班问题,在综合考虑飞机、航班、机组和机场的动态时空衔接等条件下,建立了飞机和机组的优化恢复模型.结合一体化恢复问题特点和模型结构,设计了一种GRASP算法,通过用C#编程进行求解.实例研究表明:该模型和算法在时间和成本上都有明显的优势,符合航空公司的实际需求. In order to deal with irregular flights resulted by sever weather and aircraft problems, this paper presented the integrated recovery for aircraft and crew considering the dynamic space-time connection of aircraft, flight, crew and airport. Aiming at the characteristics of integrated recovery problem and model structure, the GRASP method was designed by using C#. The case study shows that the model and method together are proved quite efficient to get the efficient result in lesser time, which can fulfill actual needs of airline.
出处 《辽宁工程技术大学学报(自然科学版)》 CAS 北大核心 2014年第5期696-699,共4页 Journal of Liaoning Technical University (Natural Science)
基金 国家自然科学基金资助项目(71171129) 上海市自然科学基金创新行动计划基金资助项目(10190502500) 上海市科委工程中心基金资助项目(09DZ2250400) 上海市教委重点学科基金资助项目(J50604)
关键词 航空复原 动态时空衔接 GRASP算法 列生成算法 飞机恢复 机组恢复 一体化恢复 aviation recovery dynamic space-time connection GRASP method Column Generation algorithm aircraft recovery crew recovery integrated recovery
  • 相关文献

参考文献11

  • 1Eggenberg N, Salani M,Bierlaire M.Constraint-specific recovery network for solving airline recovery problems[J].Computers & Operations Research,2010,37(6):1 014-1 026.
  • 2Thengvall B,Bard J,Yu G.Balancing user preferences for aircraft schedule recovery during irregular operations[J].Institute of Industrial Engineers Transactions,2000,32(3): 181-193.
  • 3Argullo M F.A GRASP for aircraft routing in response to groundings and delays[J].Journal of Combinatorial Optimization, 1997,1 (3):211-228.
  • 4Le Meilong.Solving the airline recovery problem based on vehicle routing problem with time window modeling and Genetic Algorithm[J]. International Conference on Natural Computation,2013,9(3): 817-823.
  • 5Guo Wei,Yu Gang.Optimization model and algorithm for crew management during airline irregular operations[J].Joumal of Combinatorial Optimization, 1997,1(3):305-321.
  • 6Tobias Andersson Granberg,Peter Varbrand.The flight perturbation problem[J] Transportation planning and tedmology,2004,27(2):91 -117.
  • 7Shaw C C.A duty based approach in solving the aircrew recovery problem [J].Journal of Air Transport Management,2012,19( 1 ): 16-20.
  • 8Anne Mercier.An integrated aircraft routing, crew scheduling and flight retiming model[J].Computers & Operations Research,2007,34(8):2 251- 2 265.
  • 9Pertersen J D.An optimization approach to airline integrated recovery[J]. Transportation Science,2012,46(4):482-500.
  • 10孟宪云,付钦慧,李芳,张建龙,刘海涛.基于停机时间的可修串联系统的维修更换策略[J].辽宁工程技术大学学报(自然科学版),2011,30(6):926-929. 被引量:5

二级参考文献21

  • 1郭权,卢桂艳,王希诚.基于扩展神经网络的网格资源调度优化算法[J].辽宁工程技术大学学报(自然科学版),2005,24(5):730-733. 被引量:2
  • 2Lei Zhang,Yuehui Chen,Bo Yang.Task Scheduling Based on PSO Algorithm in Computationl Grid[M].Intelligent System Design and Applications,2006:696-704.
  • 3Tingwei Chen,Bin Zhang,Xianwen Hao,Yu Dai.Task Scheduling in Grid Based on Particle Swarm Optimization[M].Parallel and Distributed Computing,2006:238-245.
  • 4H Aghdam,S Payvar.A Modified Simulated Annealing Algorithm for Static Task Scheduling in Grid Computig[C] //International Conference on Computer Science and Informatiion Technology 2008:623-627.
  • 5FATOS XHAFA,JAVIER CARRETERO.Genetic Algorithm Based Schedulers for Grid Computing Systems[J].International Journal of Innovative Computing,Information and Control,2007,3(5):1-19.
  • 6SAMI J,BUTHAINAH S.Comparative study between the internal behavior of GA and PSO through problem-specific distance functions[C] // Edinburgh UK:IEEE Congress on Evolutionary Computation,2005.
  • 7Kennedy J,Bratton D.Defining a Standard for Particle Swarm Optimization,Proc[M].IEEE Swarm Intelligence Symposium,(SIS) 2007:120-127.
  • 8MAHESWARAN M,ALI S,SIEGEL H J,et al.A comparison of Dynamic Strategies for Mapping a Class of Independent Tasks onto Heterogeneous Computing Systems[R].Technical Report,School of Electrical and Computer Engineering,Purdue University,1999.
  • 9E MUNIR,Jianzhong Li,Shengfei Shi.Performance Analysis of Task Scheduling Heuristics in Grid[C] // International Conference on Machine Learning and Cybernetics,2007:3093-3098.
  • 10Kennedy J,Eberhart R C,Particle swarm optimization,Proc[J].IEEE Conference Neural Network,1995:1942-1948.

共引文献10

同被引文献9

引证文献3

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部