改进乌鸦搜索算法在邮件集散中心航空运力调度中的应用  

Application of Improved Crow Search Algorithm in Air Transport Capacity Scheduling of Mail Distribution Center

作　　者：卢卓桓 仰燕兰[1,2] 叶桦 LU Zhuo-Huan;YANG Yan-Lan;YE Hua(School of Automation,Southeast University,Nanjing 210096,China;Key Laboratory of Measurement and Control of Complex Systems of Engineering,Ministry of Education,Nanjing 210096,China)

机构地区：[1]东南大学自动化学院,南京210096 [2]复杂工程系统测量与控制教育部重点实验室,南京210096

出　　处：《计算机系统应用》2022年第9期324-332,共9页Computer Systems & Applications

摘　　要：邮件集散中心航空运力调度涉及固定运力和备选运力两种调度对象,本文在航空运力资源充足的前提下,建立了以最小化运输成本为目标的优化模型,研究了一种改进的乌鸦搜索算法求解方法.首先根据问题的数学模型,引入惩罚函数法将部分约束转化为惩罚项,与目标函数共同构成适应度函数;然后引入Logistic混沌映射提高初始种群的多样性;根据问题的特点,提出了基于个体最优追随机制和正余弦算法的位置更新策略,并引入交叉变异机制以丰富搜索过程中种群的多样性.通过大量算例实验分析,证明了该算法的有效性与优越性.The scheduling of air transport capacity by a mail distribution center involves fixed capacity and alternative capacity. This study establishes an optimization model to minimize transportation costs under the premise of sufficient air transport capacity and proposes an improved crow search algorithm. First, depending on the mathematical model of the problem, the penalty function method is employed to convert some constraints into penalty terms which then form a fitness function together with the objective function. Second, the Logistic chaotic map is utilized to improve the diversity of the initial population. In addition, considering the characteristics of the problem, the study proposes a location update strategy based on the individual optimal follow mechanism and the sine-cosine algorithm. Finally, a cross-mutation mechanism is introduced to enrich population diversity in the search process. The effectiveness and superiority of the algorithm are proved by a large number of cases.

关 键 词：运力调度 乌鸦搜索算法 惩罚函数法 LOGISTIC混沌映射 正余弦算法 交叉变异 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] V35[自动化与计算机技术—控制科学与工程]