随着互联网的快速发展，面向大众的服务类型手机应用越来越多，为降低企业经营成本、增强企业的服务效率和提升服务质量，需要平台不断优化内部订单和服务人员的分配算法，本文章主要研究“58到家”上门服务平台的订单和家政服务人员的匹配优化问题。首先，本文针对订单服务平台的离线批量派单模式，对实际问题进行了一定简化，利用运筹学、数学规划的知识建立了优化模型，针对优化模型的求解，本文采用了模拟退火的启发式算法，利用Matlab编程首先生成一个初始解，作为当前的最优解，紧接着对当前解加一个随机扰动，得到一个新解，然后利用蒙特卡洛判断准则判断是否接受该解，接着规定迭代次数，当达到迭代次数后，如果达到指定的目标值，则输出结果，该模型的特点在于结合数学线性规划和模拟退火算法进一步增强了算法的可靠性和稳定性，该算法可用于求解更加复杂的非线性优化问题，但当面对原始数据过大的问题时，可能出现收敛速度过慢，执行时间较长的问题。

With the rapid development of the Internet, there are more and more service type mobile applications for the general public. In order to reduce the operating cost, enhance the efficiency and improve the quality of service, the platform needs to continuously optimize the internal order and service personnel allocation algorithm. This paper focuses on the optimization of the matching between orders and domestic helpers in the "58 Home Delivery" platform. Firstly, this paper simplifies the actual problem for the offline batch order distribution mode of the order service platform, and establishes an optimization model by using the knowledge of operation research and mathematical planning. Monte Carlo judgment criterion to determine whether to accept the solution, followed by specifying the number of iterations, and outputting the result when the number of iterations is reached, if the specified target value is reached. We solved the optimal matching result using Matlab programming. The model established in this paper is characterized by the combination of mathematical linear programming and simulated annealing algorithm to further enhance the reliability and stability of the algorithm, which can be used to solve more complex nonlinear optimization problems, and may suffer from slow convergence and long execution time when facing problems with too large original data alone.