灰狼算法在PC构件厂选址中的应用研究

Research on application of gray wolf algorithm in site selection of PC factory

为满足日益增长的预制构件市场需求,提高对PC构件厂选址的决策效率,提出一种基于灰狼算法在PC构件厂选址中的决策方法。建立PC构件厂选址规划期内经济成本模型,将产业链间的运输网络划分为原材料运输网络和构件配送网络,为解决市场需求的时间节点问题,引入时间满意度函数作为约束条件,完善选址模型。针对PC构件厂选址最优解问题,避免经典算法易早熟收敛和仅得出局部最优解的缺陷,采用灰狼算法对备选厂址进行寻优,利用该智能优化算法解决选址优化问题有较好的适用性,提高了计算效率和精度,输出全局最优解。以某中部积极推进地区为例进行算例仿真,实验结果表明,灰狼算法在优化选址方面具有可行性与稳定性,为PC构件厂选址降低投资成本,提供了科学的决策依据。

In order to meet the growing market demand for prefabricated components and improve the efficiency of decision⁃making for locating the PC(precast concrete)factory,a PC factory site selection decision⁃making method based on gray wolf algorithm is proposed.A PC factory site selection model for the optimal economic cost during the planning period is established.The transportation network of the industrial chain is divided into raw material transportation network and component distribution network.The time satisfaction function is introduced as a constraint condition to solve the time node problem of market demand,so as to improve the site selection model.In order to solve the problem of the optimal solution for locating the PC factory and the facts that the classical algorithms are prone to premature convergence and that only the local optimal solution is obtained,the gray wolf algorithm is used to optimize the alternative plant sites.Better applicability of this intelligent evolution algorithm for the site selection optimization is taken as the advantage to improve the calculation efficiency and precision,and output the global optimal solution.A certain central area which actively promotes this algorithm is taken as an example for simulation.The experimental results show that the gray wolf algorithm is feasible and stable in optimizing the site selection,which provides a scientific decision⁃making basis for reducing the investment costs of the site selection of PC factory.