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Jacques Lamothe

Researcher at University of Toulouse

Publications -  92
Citations -  864

Jacques Lamothe is an academic researcher from University of Toulouse. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 11, co-authored 87 publications receiving 718 citations. Previous affiliations of Jacques Lamothe include Mines ParisTech & École Normale Supérieure.

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An optimization model for selecting a product family and designing its supply chain

TL;DR: A mixed integer linear programming model is investigated that optimizes the operating cost of the resulting supply chain while choosing the product variants.
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A review of Vendor Managed Inventory (VMI): from concept to processes

TL;DR: In this article, a literature review of vendor managed inventory (VMI) is presented, and based on the conceptual elements extracted from this analysis, a VMI macro-process that summarises both operational and collaborative elements of VMI is proposed.
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Mass customization and configuration: Requirement analysis and constraint based modeling propositions

TL;DR: The purpose of this paper is to identify to define and classify customization requirements and evaluate how generic modeling and configuration assistance within the CSP framework can fulfil the requirements.
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Demand Driven MRP: assessment of a new approach to materials management

TL;DR: The results strongly indicate that DDMRP does represent a superior approach – one that warrants further academic study and its effectiveness relative to two widely accepted approaches – MRP II and Kanban/Lean production – through a series of structured computer simulation experiments.
Proceedings ArticleDOI

HospiT'Win: A Predictive Simulation-Based Digital Twin for Patients Pathways in Hospital

TL;DR: A novel framework for supporting the hospital of the future named HospiT'Win is proposed, that is a virtual replica of the hospital, allowing the health care providers to trace the patient's pathways data, monitor their behaviors, and predict their near future outcomes.