This course is about formulating, analyzing and solving models for optimal decision making in business, using data and computer-based decision support. The formulation of the models is based on mathematical programming and optimization methods. To process data and solve the models, we use up-to-date computational tools specially designed to find the best decisions to a mathematical programming model.
The course focuses on problems that capture strategic, tactical, operational and economic aspects involved in the decision making of organizations. These include, for example, applications of decision modelling in business related to energy, natural resources and the environment, such as petroleum, electricity markets, and standard logistic/distribution applications. Among these, we overview high-impact applications of decision models which have been recently developed for real-world problems, such as how to optimize the Norwegian natural gas production and transport, and how to find the equilibrium in the day-ahead market for trading power in the Nordic and Baltic regions.
The methods studied in the course come mainly from fields labeled as Operations Research, Management Science, and Prescriptive Analytics. Specific topics include linear programming, integer programming, nonlinear programming, economic interpretation, equilibrium models, computational optimization.
A set of problems split in three projects will be done individually or in groups of two students. Each project may consist of several parts: model formulation, implementation in software, interpretation and analysis of solution, article discussion and report writing.