Mathematical Models and Methods for Supply Chain and Operations Research
A special issue of Mathematics (ISSN 2227-7390).
Deadline for manuscript submissions: 26 March 2025 | Viewed by 833
Special Issue Editors
Interests: supply chain planning; operational research; reverse logistic; inventory control; optimisation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The research on mathematical models and methods for supply chain and operations boasts a rich history in the scholarly literature, characterized by well-known basic models that have undergone continuous refinement over the years to enhance their performance across various domains such as strategic location and layout, tactical planning, operational routing and scheduling, and inventory control, among others.
Over the last few decades, there has been a notable shift in focus towards addressing new challenges related to sustainability, reverse logistics, CO2 emissions, energy consumption, the integration of financial factors, resilience amidst uncertainties, and increasingly complex systems.
New mathematical methods must integrate uncertainties and aspects of Industry 4.0 to enhance their efficiency and improve responses in supply chain and operations management. These emerging issues necessitate the identification of new variables, constraints, and performance indicators, thereby driving the need for the development of novel mathematical models and methods to tackle these evolving complexities.
This Special Issue aims to showcase recent works (theoretical breakthroughs, industrial cases, or reviews) on mathematical models and methods.
Dr. Matthieu Godichaud
Dr. Aghelinejad Mohammadmohsen
Guest Editors
Manuscript Submission Information
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Keywords
- mathematical programming (linear, non-linear, multi-objective)
- supply chain optimization
- simulation, statistical, and sensitivity analysis
- strategic, tactical, and operational planning
- operational routing and scheduling problem
- inventory control
- sustainability, CO2 emissions, and energy consumption
- reverse logistics
- financial aspects
- resilience
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