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Main Authors: Liu, Ziyang, Hu, Yurui, Deng, Yihan
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2503.05807
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author Liu, Ziyang
Hu, Yurui
Deng, Yihan
author_facet Liu, Ziyang
Hu, Yurui
Deng, Yihan
contents This paper introduces a novel multi-stage decision-making model that integrates hypothesis testing and dynamic programming algorithms to address complex decision-making scenarios.Initially,we develop a sampling inspection scheme that controls for both Type I and Type II errors using a simple random sampling method without replacement,ensuring the randomness and representativeness of the sample while minimizing selection bias.Through the application of hypothesis testing theory,a hypothesis testing model concerning the defect rate is established,and formulas for the approximate distribution of the sample defect rate and the minimum sample size required under two different scenarios are derived. Subsequently,a multi-stage dynamic programming decision model is constructed.This involves defining the state transition functions and stage-specific objective functions,followed by obtaining six optimal decision strategies under various conditions through backward recursion.The results demonstrate the model's potent capability for multi-stage decision-making and its high interpretability,offering significant advantages in practical applications.
format Preprint
id arxiv_https___arxiv_org_abs_2503_05807
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Establishment and Solution of a Multi-Stage Decision Model Based on Hypothesis Testing and Dynamic Programming Algorithm
Liu, Ziyang
Hu, Yurui
Deng, Yihan
Systems and Control
Applications
This paper introduces a novel multi-stage decision-making model that integrates hypothesis testing and dynamic programming algorithms to address complex decision-making scenarios.Initially,we develop a sampling inspection scheme that controls for both Type I and Type II errors using a simple random sampling method without replacement,ensuring the randomness and representativeness of the sample while minimizing selection bias.Through the application of hypothesis testing theory,a hypothesis testing model concerning the defect rate is established,and formulas for the approximate distribution of the sample defect rate and the minimum sample size required under two different scenarios are derived. Subsequently,a multi-stage dynamic programming decision model is constructed.This involves defining the state transition functions and stage-specific objective functions,followed by obtaining six optimal decision strategies under various conditions through backward recursion.The results demonstrate the model's potent capability for multi-stage decision-making and its high interpretability,offering significant advantages in practical applications.
title Establishment and Solution of a Multi-Stage Decision Model Based on Hypothesis Testing and Dynamic Programming Algorithm
topic Systems and Control
Applications
url https://arxiv.org/abs/2503.05807