A Proposed Order Prediction Methodology for Vendor-Managed Inventory System in FMCG Sector Based on Interval-Valued Intuitionistic Fuzzy Sets


DEMİRCAN M. L. , Merdan E.

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol.14, no.1, pp.1489-1500, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.2991/ijcis.d.210423.004
  • Title of Journal : INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
  • Page Numbers: pp.1489-1500

Abstract

Vendor-managed inventory (VMI) is a supply chain coordination improvement system. Due to the vendor's responsibility for the replenishment decision, demand forecasting and quick response for retailers' demand fluctuations are crucial in a VMI system. Our study focuses on order prediction of the VMI for FMCG companies, which is multicriteria decision-making entailing to consider various quantitative and qualitative criteria in the fuzzy decision-making process. The interval-valued intuitionistic fuzzy set (IVIFS) is applied to solve ambiguity, vagueness, and subjectivity in human judgments. With real sales data, sales conditions, and objective expert opinions, the proposed method showed logical and reliable results. The study also presented that the proposed methodology improves the company's supply chain performance while preventing excessive stocks and customer backorders with equalization of the alternatives.