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

Authors: Ahmed El Maalmi; Kaoutar Jenoui; Laila El Abbadi

Addresses: Engineering Sciences Laboratory, National School of Applied Sciences, Ibn Tofail University, Kenitra 14 000, Morocco ' Laboratory Smartilab, Moroccan School of Engineering Sciences, EMSI, Rabat 10 000, Morocco ' Engineering Sciences Laboratory, National School of Applied Sciences, Ibn Tofail University, Kenitra 14 000, Morocco

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.

DOI: 10.1504/IJMDM.2024.139385

International Journal of Management and Decision Making, 2024 Vol.23 No.4, pp.395 - 414

Received: 27 Apr 2022
Accepted: 07 Dec 2022
Published online: 02 Jul 2024 *

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