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

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.

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

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.