摘要
为提高排班结果的准确性可靠性 ,提出了排班问题的多目标优化模型 ,并应用改进的基于信息熵的自适应遗传算法求解模型的最优解 .同时引入分割集和模拟退火算法的思想进行优解的选择 .通过对航空公司机组排班问题的仿真比较 。
To improve the solution of the rostering problem, a multi objective optimization model was proposed. The adaptive genetic algorithm based on entropy was improved and was used to solve the rostering problem to attain the best solution. In the improved method, inferior individuals were adopted with some probability as simulated annealing. Individuals of next generation were selected by using set partitioning method. The correctness and advancement of this model and algorithm were tested by solving aircrew rostering problem of Yunnan Airline.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2003年第9期821-824,共4页
Journal of Beijing University of Aeronautics and Astronautics
基金
高等学校优秀青年教师科研奖励计划
关键词
排班
多目标优化
信息熵
自适应遗传算法
crew rostering
multi objective combinatorial optimization
entropy
adaptive genetic algorithm
