CAJ | 학술논문

为解决供应链中需求预测精度不高的问题,在传统 GM(1,1)预测模型的基础上,采用了一种基于遗传算法调整发展系数和内生灰作用量的灰色预测模型,运用此模型对供应链中各级需求量进行预测,使用博弈理论构建了供应链中各级需求预测出现误差时的协商策略用以对预测结果的优化.实验结果表明,协商策略获取了符合双方利益的需求量,预测结果有了较高的精度.
위해결공응련중수구예측정도불고적문제,재전통 GM(1,1)예측모형적기출상,채용료일충기우유전산법조정발전계수화내생회작용량적회색예측모형,운용차모형대공응련중각급수구량진행예측,사용박혁이론구건료공응련중각급수구예측출현오차시적협상책략용이대예측결과적우화.실험결과표명,협상책략획취료부합쌍방이익적수구량,예측결과유료교고적정도.
Aiming to overcome the low accuracy of demand forecasting in supply chain, this paper uses the genetic algorithm to estimate the developing coefficient and the control variable of the GM(1, 1)model and predicts the demand of every level in supply chain with this forecasting model, then uses a negotiation algorithm based on game theory to optimize the demand fore-cast when demand forecast disruption occurs among every level of supply chain. Results are very encouraging as this optimiza-tion clearly improves the accuracy of demand forecasting in supply chain.