Demand Forecasting: A Case Study in the Food Industry

被引：3

作者：

Silva, Juliana C. ^{[1
]}

Figueiredo, Manuel C. ^{[2
]}

Braga, Ana C. ^{[2
]}

机构：

[1] Univ Minho, Sch Engn, DPS, Braga, Portugal

[2] Univ Minho, ALGORITMI Ctr, P-4710057 Braga, Portugal

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2019, PT III: 19TH INTERNATIONAL CONFERENCE, SAINT PETERSBURG, RUSSIA, JULY 1-4, 2019, PROCEEDINGS, PART III | 2019年 / 11621卷

关键词：

Forecasting demand; Exponential smoothing; ARIMA; Combining forecasts; COMBINATION; SALES;

D O I：

10.1007/978-3-030-24302-9_5

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The use of forecasting methods is nowadays regarded as a business ally since it supports both the operational and the strategic decision-making processes. This paper is based on a research project aiming the development of demand forecasting models for a company (designated here by PR) that operates in the food business, more specifically in the delicatessen segment. In particular, we focused on demand forecasting models that can serve as a tool to support production planning and inventory management at the company. The analysis of the company's operations led to the development of a new demand forecasting tool based on a combination of forecasts, which is now being used and tested by the company.

引用

页码：50 / 63

页数：14

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