Research on production decision of electronic products based on genetic algorithm
DOI:
https://doi.org/10.62051/1kbedp72Keywords:
Production decision; Hypothesis testing; 0-1 Variable optimization model; Genetic algorithm.Abstract
This paper focuses on the production decision optimization problem of electronic products, using a variety of models and algorithms to carry out research. Assuming that the defect rate of electronic products follows Bernoulli distribution, a hypothesis testing model is constructed with binomial distribution and normal approximation, and the minimum sample size formula is derived to determine the minimum detection scheme. The 0-1 variable is introduced to construct the unconstrained decision optimization model, and the geometric series summation model is used to describe the correlation of the decision process. Genetic algorithm is used to solve the optimal decision strategy in various scenarios. The algorithm simulates Darwinian natural selection theory and iteratively optimizes a series of possible solutions through selection, crossover and mutation operations. The minimum sample size under different conditions and the production strategy and maximum profit of different cases were calculated, which revealed the key mechanism of production decision optimization and provided theoretical basis and method support for production process quality control optimization decision.
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