Class Operational Research

The Operations Research course introduces the fundamental concepts, methods, and techniques for decision support based on mathematical optimization models and quantitative analysis. It covers the formulation and solution of linear programming problems, transportation models, network models, and queueing systems, using classical algorithms and sensitivity analysis techniques. The course focuses on resource optimization, planning, and process improvement in industrial, logistics, commercial, and service organizations. It develops students' skills in modelling complex problems, evaluating alternative solutions, and supporting decision-making, constituting a key component of education in engineering, management, and applied sciences by promoting an analytical and efficiency-oriented approach to solving real-world problems.

Not applicable

Operations research methodology: origins, nature and applications; mathematical techniques - areas of application; problem of decision; optimization problems. Linear optimization: linear programming; formulation of models; graphic representation. Simplex algorithm. Sensitivity analysis. Economic Interpretation. Transport problem: Northwest corner, Minimum cost, and Vogel methods; stepping stone. Network models: terminology; shortest path problem - Dijkstra algorithm; Minimum spanning Tree Problem - Kruskal and Prim Algorithms; maximum flow problem - Ford-Fulkerson algorithm. Introduction to queueing theory.

Series of exercises will be proposed to consolidate knowledge and stimulate problem-solving skills. In each session , students are encouraged to focus on questions related to the topics covered in class and to show the results of their individual work in the following session where questions are resolved on the board, whenever necessary, and details that have caused doubts are clarified. The fundamental idea is repeatedly highlighted that solving exercises has the main objective of allowing a deeper understanding of the conceptual body of the curricular unit, mastering which will allow the application of these tools to solve more advanced problems. When ever possible, a progression is adopted that starts from more calculative issues and develops towards the more conceptual parts of linear programming, aiming to radually consolidate mastery of the various tools provided by this curricular unit.

Hillier, F. S., & Lieberman, G. J. (2024). Introduction to Operations Research (2024 Evergreen Release). McGraw-Hill. Hill, M. M., & Santos, M. M. (2021). Programação Linear (Vols. 1-3). Edições Sílabo. Hill, M. M., & Santos, M. M. (2009). Exercícios de Programação Linear . Edições Sílabo.