捕食搜索算法是Linhares Alexandre于1998年提出的一种模拟动物捕食策略的仿生计算方法,算法原理如下:捕食搜索算法寻优时,先在整个搜索空间进行全局搜索,直至找到一个较优解;然后在较优解附近的区域进行集中搜索,如果搜索很多次也没有找到更优解,则放弃局域搜索;然后再在整个搜索空间进行全局搜索,如此循环,直至找到最优解(或近似最优解)为止。
区别于传统捕食搜索算法,新算法采用变化的局部搜索和全局搜索限制,从而避免陷入局部最优和解的退化。
The new PSA USES variable constraints of local search and global search to avo id falling into local optimal solutions and the degeneration of solutions.
为了求解上述模型,首先利用FLOYD算法求得不完全无向图中各节点间的最短路径和最短路径长度,然后设计了捕食搜索算法对模型进行求解。
To solve the model, the shortest path and its length of every two nodes in the incomplete undigraph are calculated with FLOYD algorithm, and a predatory search algorithm is designed for the solution.
为了求解上述模型,首先将模型进行清晰化处理,使之转化为一类确定性多设施车辆路径模型,然后设计了嵌入FLOYD算法的捕食搜索算法对之进行求解。
The model was firstly converted into a crisp multi-depot vehicle routing problem, and then it was solved by a predator search algorithm with FLOYD.
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