Mathematical Programming Modeling for Supply Chain Management
Course duration: 5 h
This course would be included in the Operational Research (OR) stream, whose general aiming is to introduce some methods of mathematical analysis that allow better solutions dealing with the complex challenges from the real life.
One of these real-life challenges concern to Supply Chain Management (SCM) which may be defined as the "design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand and measuring performance globally".
Basically, two problems may be addressed in SCM, those which are related with the Supply Chain configuration or design (strategic planning) and those which are related with the Supply Chain coordination (tactical and operational planning).
Although several perspectives (theoretical, case-based etc) are used to manage SCM, Operations Research-based methods, and particularly mathematical programming, has been one of the most studied in the literature.
In these course mixed-integer and linear models for SCM will be presented, some of them applied to real life examples.
The three first hours will be theoretical. A general overview of Supply Chain Management problems and Mathematical Programming Models applied to them will be addressed. Finally a real-cased based example applied to the Ceramic Sector will be shown and modeled.
The last two hours will be practical. The professional Modeling Programming Language (MPL) and one of its Solvers will be used to model some examples and solve them.
Dr. David P?rez Perales
M. Sc. In Industrial Engineering
Ph. D. In Industrial Engineering
Place of employment: Department of Business Management, Polytechnic University of Valencia; Research Centre on Production Management and Engineering, Valencia, Spain
Spheres of researches: Mixed and Integer Linear Programming Models, Supply Chains Collaborative Planning.
Telephone: +34 96 3877007 Ext: 76867