粒子群优化算法在配送中心连续性选址中的应用

Application of particle swarm optimization to continuous location of distribution center

在用常规算法对配送中心进行连续性选址时,很容易陷入局部最优解。针对这一问题,引入ALA方法的思想,提出了解决此类模型的粒子群优化算法。该算法首先利用ALA方法的局部寻优能力对初始粒子进行优化,然后利用粒子群优化算法进行全局寻优。通过实例分析表明,该算法能很好地处理物流配送中心的连续选址问题,为决策者提供一种有效的优化工具。

The local optimal solution is often got when general algorithm was applied to solve continuous location of distribution center. To solve the problem, Alert Location - Allocation （ALA） algorithm to construct hybrid particle swarm optimization was cited in this paper. The computing result of the algorithm is nearer to the global optimal solution by combining local search of ALA algorithm and global optimization of particle swarm optimization. An example demonstrates that hybrid particle swarm optimization can solve the problem of continuous location of logistics distribution center and provides an effective decision tool for decision-maker.