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计算机系统应用:2018,27(8):180-186
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基于鲸鱼群优化算法的带Sigmoid满意度应急车辆调度问题
范祥, 叶春明, 曹磊
(上海理工大学 管理学院, 上海 200093)
Scheduling Problem with Sigmoid Satisfaction Emergency Vehicle Based on Whale Swarm Algorithm
FAN Xiang, YE Chun-Ming, CAO Lei
(Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)
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投稿时间:2017-12-06    修订日期:2017-12-27
中文摘要: 针对突发大规模灾害事件下受灾点严重程度不同的特点,引入Sigmoid时间满意函数评价救援效果,建立平均时间满意度最大与救援路径最短双目标调度模型.设计了基于混沌序列搜索算子的混沌鲸鱼群算法,通过构建三组不同规模的实验案例对模型进行求解,并将所得结果与模拟退火算法和基本鲸鱼群算法进行比较.实验表明,在处理较小规模车辆调度情况下,三种算法处理效果差距不明显,随着求解规模增大,混沌鲸鱼群算法对解决所提问题具有更好的效果,是一种优化应急车辆的有效方法.
Abstract:Considering the different levels of large-scale urgent disaster, Sigmoid time satisfaction function is proposed to evaluate the rescue effect. It builds the shortest rescue path and maximum satisfaction of average time vehicle scheduling model. Chaotic Whale Swarm Algorithm is designed based on Chaos sequence search operator. the improved algorithm is applied to optimize three groups of experimental cases of different sizes, and the results are compared with those of the simulated annealing algorithm and original Whale Swarm Algorithm. Results show that there is little difference in performance when the handling smaller scale of vehicle scheduling, while the improved algorithm gain more advantage over the simulated annealing algorithm and original algorithm as the handling scale getting larger. Chaotic Whale Swarm Algorithm is effective method to deal with emergency vehicle scheduling problem.
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基金项目:国家自然科学基金(71271138);上海市一流学科建设项目(S1201YLXK);上海市高原学科项目(GYXK1201);上海理工大学科技发展项目(16KJFZ028)
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范祥,叶春明,曹磊.基于鲸鱼群优化算法的带Sigmoid满意度应急车辆调度问题.计算机系统应用,2018,27(8):180-186
FAN Xiang,YE Chun-Ming,CAO Lei.Scheduling Problem with Sigmoid Satisfaction Emergency Vehicle Based on Whale Swarm Algorithm.COMPUTER SYSTEMS APPLICATIONS,2018,27(8):180-186

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