Nonlinear Programming Model Based on Monte Carlo Simulation

Yudong Wang, Xiaochen Shi, Ruitao Dong, Mingzi Li
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Abstract

: This paper focuses on planning the choice of raw material ordering and transportation solutions for enterprises, and gives the most economical ordering and forwarding solutions for enterprises through quantitative analysis of supplier supply characteristics; and predicts the future production capacity of enterprises through time series analysis models, and finally gives the optimal ordering and transportation strategies. Among them, according to the existing optimal forwarder transshipment scheme to supplement, on the basis of the original consideration of the cost required for the production of enterprises, the model is improved, by increasing the target letter material type purchase limits, the establishment of multi-objective planning model based on Monte Carlo simulation to solve the optimal procurement scheme, the development of transshipment scheme. On this basis, the supplier supply data given in the article is divided in 240 weeks, 24 weeks as a cycle, and its long-term trend fluctuation over time is judged by drawing a time series diagram through SPSS, and the enterprise capacity prediction is made in cycles. In this paper, we find out the single-week capacity by selecting the capacity factor prediction, optimize the model, and substitute it into the improved multi-objective planning model to get the optimal strategy for purchasing and forwarding.
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基于蒙特卡罗仿真的非线性规划模型
:重点规划企业原材料订购和运输方案的选择,通过对供应商供应特征的定量分析,给出企业最经济的订购和运输方案;并通过时间序列分析模型预测企业未来的生产能力,最后给出最优的订货和运输策略。其中,根据现有最优货代转运方案进行补充,在原有考虑企业生产所需成本的基础上,对模型进行改进,通过增加目标信材类的采购限额,建立基于蒙特卡罗仿真的多目标规划模型求解最优采购方案,制定转运方案。在此基础上,将文中给出的供应商供应数据划分为240周,24周为一个周期,通过SPSS绘制时间序列图判断其随时间的长期趋势波动,并按周期进行企业能力预测。本文通过选择运力因子预测来确定单周运力,对模型进行优化,并将其代入改进的多目标规划模型中,得到最优的采购和转发策略。
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