萤火虫邻域结构的多吸引子微粒群算法及应用——以中国台湾再制造资源回收处理中心选址规划为例

Multi-attractors PSO with glowworm neighborhood space and is application——location planning for the remanufacturing resource recycling centers in Taiwan China

借鉴萤火虫最优化算法的动态邻域空间结构,提出一种改进的多吸引子微粒群算法,从而能够对解空间进行多子群并行搜索,提高求解速度,避免陷入单点局部极值。并将该算法应用到中国台湾再制造资源回收处理中心的选址规划问题中,在运输总距离最短的目标下,成功地解决了再制造资源回收处理中心的选址规划问题并对资源回收站进行了有效的指派分配。

This paper puts forward a multi-attractors PSO that borrows the ideas of dynamic neighborhood space from the glowworm swarm optimization.Thus it can search the solution space parallelly with multi-subgroup to improve the speed of solving.It also avoids the problem of falling into the local extremum,which is attracted by a single attractor.The multi-attractors PSO with the glowworm neighborhood space is applied to the location planning for the remanufacturing resource recycling centers in Taiwan China.The results show that the algorithm can solve this problem and assign the recycle depots successfully,with the objective of minimizing the total transportation distance.