解决有配放限制的多集装箱配载系统优化的多蚁群协同算法

在分析具有装载重量、体积等约束条件及配放限制的集装箱配载模型的基础上，分析了求解其的蚁群算法与求解TSP的蚁群算法在结点性质、原点（中心结点）的作用、蚂蚁路径构造规则、可移动结点集合、可行解的形成过程等方面的区别. 针对问题特点，充分考虑货物配放限制，装载工具的载重、容积两个方面同时优化的问题，基于待装货物比容动态逼近装载工具剩余空间比容的思想，综合运用ACA-INI、ACA-CONTAINER和ACA-VOTUME三个不同蚁群协同考虑问题的两个目标--需用集装箱数目优化和装载工具重量、容积利用率优化，对问题的求解策略进行了研究. 进一步地，结合8类40件不同品种货物的集装箱配载问题对模型算法的实用性和有效性进行了验证.

Multi-Ant Colony Algorithm for Optimal Stowage of Multi-Category Goods and Multi-Container

Considering the optimal loading and volume, and the stowage with limitation, this paper analyzes several differences of the multi-ant colony algorithm for the current problem and TSP, namely, joint property, original note function, route construction rule, and formulation of feasible solution. Multi-Ant colony algorithm include three parts: ACA-INI, ACA-CONTAINER and ACA-VOTUME. Improvement on route construction rule and pheromone updating rule was adopted on the basis of former algorithm. An example was analyzed to demonstrate the correctness of the application of this model and algorithm. It is proved that multi-ant colony algorithm is efficient and feasible in solving optimal loading of multi-category goods and multi-container.