摘要
为更有效地解决航空公司飞机恢复问题,在经典的资源指派优化模型中放宽飞机流平衡约束,加入合并航班的恢复策略;在贪婪随机自适应算法(GRASP)和模拟退火算法的基础上,提出一种新的启发式算法-贪婪随机模拟退火算法,降低了陷入局部最优解的概率,同时通过限定路径对的种类和候选解的数量,提高了算法的时间效率.实例计算结果表明,本文提出的模型和算法能有效处理流不平衡条件下大规模飞机恢复问题,在有效的时间内求得最优解或近似最优解.
In order to deal with aircraft recovery effectively for airlines,the classic resource assignment model is expanded by broadening aircraft balance constraint and adding flight merger strategy.Besides,integrating the characteristics of Greedy Random Adaptive Search Procedure and Simulated Annealing algorithm,a new greedy random simulated annealing algorithm is presented,which reduces the probability of getting a local optimal solution and improves the operating efficiency of the algorithm through restricting the types of aircraft route pairs and the number of candidate solutions.Empirical results demonstrate the ability of the new model and algorithm to quickly explore a wide range of unbalanced scenarios and to produce an optimal or near-optimal solution in time.
出处
《小型微型计算机系统》
CSCD
北大核心
2010年第4期793-796,共4页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(70771046)资助
中国民航总局应用技术基金项目(MHRD0622)资助
关键词
不正常航班
飞机恢复
GRASP
贪婪随机模拟退火算法
流平衡约束
irregular flight schedule
aircraft recovery
greedy random adaptive search procedure
greedy random simulated annealing algorithm
aircraft balance constraint
