A multi-objective decision-making system to increase supplier driven innovation using Python

Ahmed El Maalmi, Kaoutar Jenoui and Laila El Abbadi

International Journal of Management and Decision Making, 2024, vol. 23, issue 4, 395-414

Abstract: The fourth industrial revolution is contributing in an impressive way to companies' improving performances. Purchasing is the main function involved in the dynamic transformation because of its key role in the company's business process and sustainability. For this purpose, it must be the focus of the management to master its processes and their performance, especially supplier selection based on both qualitative and quantitative criteria. The paper proposes the standard implementation of a decision-making system for multi-criteria suppliers' selection. The system's solution is based on linear programming optimisation to enhance innovation between companies and suppliers. It explains the implementation method for a model based on total cost, delivery times, and a supplier's innovation criteria. A case study demonstrates this model's interest in improving purchasing function.

Keywords: decision support systems; multiple objective programming; innovation; suppliers' selection; supply chain management; python programming; cost optimisation; delivery optimisation. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=139385 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmdma:v:23:y:2024:i:4:p:395-414

Access Statistics for this article

More articles in International Journal of Management and Decision Making from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().