Class Operational Research

Provides knowledge, skills and mathematical tools essential for management and engineering.

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.

Series of exercises will be proposed with the aim of consolidating knowledge and stimulating problem-solving skills. The evaluation of the discipline, expressed on a scale from 0 to 20 points, will be made at different times, including 2 midterms (40% + 50%) and individual work to be developed outside the classroom (10%). If the weighted average of these evaluations is equal to or greater than 9.5, the student will be successful in the subject, otherwise the student will be able to attend a global frequency. In the final exam, the student can improve the grade. The minimum passing grade for these assessments is also 9.5. Assessment criteria are explained at the beginning of the semester.

HILLIER, F. S.; LIEBERMAN, G. J. (2021), Introduction to Operations Research, McGraw-Hill.
WINSTON, W. L. (2002), Introduction to Mathematical Programming, Duxbury Press.