飞行员模拟机复训计划优化模型研究  

The Research on Optimization Model for Recurrent Training Plan of Aviator Full Flight Simulators

作　　者：潘邦传[1] 宋志勇[2] 许保光[1] 高敏刚[1] 池宏[1] 

机构地区：[1]中国科学院科技政策与管理科学研究所 [2]中国国际航空股份有限公司,北京100621

出　　处：《中国管理科学》2008年第2期69-75,共7页Chinese Journal of Management Science

基　　金：国家自然科学基金资助项目(70371059)

摘　　要：根据民航有关规定,飞行员每6个日历月需要参加一次模拟机复训。公司制定模拟机复训计划,要考虑模拟机资源、教员资源、生产任务允许模拟机复训的人数和飞行员训练适宜期,本文以机长和副驾驶配组数最大化和训练/检查月内参加复训人数最大化为目标,在此基础上建立了多目标规划问题,仅考虑配组目标时,给出了不存在隔月配组的条件。根据不同的目标,本文研究对象可分解为两个经典网络规划子问题,文中给出了求解的方法,并给出了一个实际案例。According to the regulation of civil aviation, pilots need to attend Full Flight Simulator （FFS） recurrent training every six months, according to civil aviation rules. In this paper, we present a muIti-objective nonlinear programming model to fulfill aviator recurrent training arrangement. One objective is to make the pilots practice before the end of the duration since the last recurrent training. The other is to make the pilots and copilots match for a practice. The restrictions of the obtainable time of faculty, the number of FFS, the flights scheduled and the duration of the recurrent training are considered. If we take into account the match only, there is a precondition for no bimonthly match. A decomposition algorithm is designed to solve the model and an example is settled.

关 键 词：多目标决策 优化模型 复训 分解算法 

分 类 号：C931[经济管理—管理学]