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Academic Journal of Mathematical Sciences, 2022, 3(2); doi: 10.25236/AJMS.2022.030202.

## Nonlinear Programming Model Based on Monte Carlo Simulation

Author(s)

Yudong Wang1, Xiaochen Shi2, Ruitao Dong2, Mingzi Li2

Corresponding Author:
Yudong Wang
Affiliation(s)

1Department of Science, Northeast Forestry University, Harbin, 150040, China

2Department of Statistics, Chengdu University of Information Technology, Chengdu, 610103, China

### 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.

### Keywords

MATLAB; Multi-objective optimization; Optimal transit scheme; Monte Carlo simulation

### Cite This Paper

Yudong Wang, Xiaochen Shi, Ruitao Dong, Mingzi Li. Nonlinear Programming Model Based on Monte Carlo Simulation. Academic Journal of Mathematical Sciences (2022) Vol. 3, Issue 2: 6-12. https://doi.org/10.25236/AJMS.2022.030202.

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