Welcome to the InfoSci Platform
A Computational Intelligence Approach to Supply Chain Demand Forecasting

A Computational Intelligence Approach to Supply Chain Demand Forecasting

Nicholas Ampazis
Copyright: © 2011 |Pages: 15
ISBN13: 9781615206339|ISBN10: 1615206337|EISBN13: 9781615206346
DOI: 10.4018/978-1-61520-633-9.ch005
Cite Chapter Cite Chapter

MLA

Ampazis, Nicholas. "A Computational Intelligence Approach to Supply Chain Demand Forecasting." Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., IGI Global, 2011, pp. 110-124. https://doi.org/10.4018/978-1-61520-633-9.ch005

APA

Ampazis, N. (2011). A Computational Intelligence Approach to Supply Chain Demand Forecasting. In I. Minis, V. Zeimpekis, G. Dounias, & N. Ampazis (Eds.), Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods (pp. 110-124). IGI Global. https://doi.org/10.4018/978-1-61520-633-9.ch005

Chicago

Ampazis, Nicholas. "A Computational Intelligence Approach to Supply Chain Demand Forecasting." In Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, edited by Ioannis Minis, et al., 110-124. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61520-633-9.ch005

Export Reference

Mendeley
Favorite

Abstract

Estimating customer demand in a multi-level supply chain structure is crucial for companies seeking to maintain their competitive advantage within an uncertain business environment. This work explores the potential of computational intelligence approaches as forecasting mechanisms for predicting customer demand at the first level of organization of a supply chain where products are presented and sold to customers. The computational intelligence approaches that we utilize are Artificial Neural Networks (ANNs), trained with the OLMAM algorithm (Optimized Levenberg-Marquardt with Adaptive Momentum), and Support Vector Machines (SVMs) for regression. The effectiveness of the proposed approach was evaluated using public data from the Netflix movie rental online DVD store in order to predict the demand for movie rentals during the critical, for sales, Christmas holiday season.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.