Rehabilitation sciences and techniques
Module Operations Research

Academic Year 2023/2024 - Teacher: GABRIELLA COLAJANNI

Expected Learning Outcomes

The course aims at presenting linear programming problems in healthcare. The course provides students with the analytic tools to model and to foresee situations in which a single decision-maker must find the best choice. At the end of the course, the students will be able to formulate mathematically linear programming problems in healthcare, solve numerically the problems, and realize what the optimal choice is.

The goals of the course are:

Knowledge and understanding: to acquire base knowledge that allows students to study optimization problems and apply opportune techniques to solve the decision-making problems. The students will be able to use algorithms for linear programming problems.
  • Applying knowledge and understanding: to identify and model real-life decision-making problems. In addition, through real examples, the student will be able to find correct solutions for complex problems.
  • Making judgments: to choose and solve autonomously complex decision-making problems and to interpret the solutions.
  • Communication skills: to acquire base communication and reading skills using technical language.
  • Learning skills: to provides students with theoretical and practical methodologies and skills to deal with optimization problems in healthcare; to acquire further knowledge on mathematics applied to healthcare.

Course Structure

There will be classroom lessons and exercises.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Learning assessment may also be carried out on line, should the conditions require it.

Required Prerequisites

Mathematics (important/mandatory).

Attendance of Lessons

Mandatory

Detailed Course Content

  • LINEAR PROGRAMMING
  • Linear programming models. Graphical method. Primal simplex method.
  • INTEGER PROGRAMMING
  • Interger programming models. Branch and Bound method in integer programming, Knapsack problem.
  • EXCEL FOR LINEAR PROGRAMMING PROBLEMS
  • APPLICATIONS TO HEALTHCARE

Textbook Information

  1. R. Tadei, F. Della Croce, “Elementi di Ricerca Operativa”, Società Editrice Esculapio, 2005;
  2. R. Tadei, F. Della Croce, A. Grosso, “Fondamenti di Ottimizzazione”, Società Editrice Esculapio, 2005;
  3. F. Hillier, G.J. Liebermann, “Ricerca Operativa”, McGraw-Hill, 2006
  4. F. Fumero, Metodi di ottimizzazione. Esercizi ed applicazioni, Società Editrice Esculapio, 2013​
  5. F.S. Hillier, G.J. Lieberman, Introduction to Operations Research, Mc Graw Hill.

(consultation books)

Course Planning

 SubjectsText References
1Linear Programming1,3,4,5
2graphic method1,3,4,5
3Simplex Algorithm1,3,4,5
4Integer Linear Programming2,3,4,5
5Branch and Bound method2,3,4,5
6Knapsack Problem2,3,4,5

Learning Assessment

Learning Assessment Procedures

The final exam consists of a written test (mandatory) with open-ended, closed-ended questions and/or exercises, and an oral/practical test (optional).

Elements to be evaluated: relevance of the answers, quality of their contents, ability to connect with other topics within the program, ability to report examples, quality of technical language, and overall expressive ability.

To guarantee equal opportunities and in compliance with current laws, students can request a meeting in order to plan any compensatory and/or dispensatory measure, according to the educational goals and specific needs. In this case, it is advisable to contact the CInAP (Centre for Active and Participated Integration - Services for Disabilities and/or SLD) professor of the Department where the Degree Course is included.

Examples of frequently asked questions and / or exercises

Linear programming problems. Graphic solutions. Simplex. Integer Linear Programming models. Knapsack problem.
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