基于目标规划的生产计划优化和基于神经网络需求预测的库存控制

Ratna Mira Yojana, Muhammad Hendra, I. A. Marie
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引用次数: 0

摘要

CV Bahyu Perkasa是一家从事混凝土建筑行业的公司。生产的产品之一是铺路砖。需求波动的数量使公司决定定期储备产品和采购原材料,以满足消费者的需求。这是在生产过剩和库存过剩中产生的。因此,需要一种能够使生产成本最小化,利润最大化的消费者需求预测方法。此外,需要库存控制方法来降低原材料的存储成本和订购成本。用于需求预测的方法是人工神经网络,其误差正确率为0.017769。预测结果利用目标规划优化生产计划,利用MRP优化库存控制计划。考虑优先级确定的目标规划优化模型的结果为满足消费者需求和使生产成本最小的最优解Rp为99,205,774.00。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Production Planning Using Goal Programming and Inventory Control Based on Demand Forecasting Using Neural Networks on CV Bahyu Perkasa
CV Bahyu Perkasa is a company engaged in the concrete construction industry. One of the products produced is paving block. The number of fluctuating demands makes the company decide to stockpile products and procure raw materials regularly to meet consumer demand. This was Born in over-production and overstock. Therefore, a consumer demand forecasting method is needed so that it can minimize production costs and maximize profits. In addition, inventory control methods are needed to reduce storage costs and ordering costs for raw materials. The method used for demand forecasting is an artificial neural network with an MSE error accuracy rate of 0.017769. Forecasting results are used to optimize production planning using goal programming and inventory control planning using MRP. The results of the goal programming optimization model with priority determination produce an optimal solution in fulfilling consumer demand and minimizing production costs of Rp. 99,205,774.00.
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