Research on the modeling and algorithm of multi-objective crew rostering
-
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,模型的正确性和先进性得到了验证.Abstract: 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.
-
[1] Panta L.Simulated annealing for the multi-objective aircrew rostering problem . Transportation Research, 1999,33(A):19~45 [2] Chu P C, Beasley J E. Constraint handling in genetic algorithms:the set partitioning problem[J]. Journal of Heuristics, 1998,4:323~357 [3] Srinivas M, Patnaik L M. Adaptive probabilities of crossover and mutation in genetic algorithms[J]. IEEE Transaction on System, Man and Cybernetics, 1994, 24(4):656~666 [4] 郝 翔,李人厚.基于信息熵的自适应遗传算法[J].西安建筑科技大学学报,1997, 29(1):34~38 Hao Xiang, Li Renhou. On the adaptive genetic algorithm based on shannon entropy[J]. Journal of Xi'an University of Arch & Tech,1997, 29(1):34~38(in Chinese) [5] 云庆夏.进化算法[M].北京:冶金工业出版社,2000 Yun Qingxia. Evolution Algorithm[M]. Beijing:Publishing House of Metallurgy Industry, 2000(in Chinese) [6] 储理才.基于MATLAB的遗传算法程序设计及TSP问题求解[J].集美大学学报(自然科学版), 2001,6(1):9~11 Chu Licai. Genetic algorithm programming based on Matlab and TSP solving[J]. Journal of Jimei University (Natural Science),2001,6(1):9~11(in Chinese) -
点击查看大图
计量
- 文章访问数: 3678
- HTML全文浏览量: 146
- PDF下载量: 30
- 被引次数: 0
下载:
