N90401 Operations Research

Scuola di Ingegneria Industriale
Syllabus
Academic Year 2019/20 First Semester

foto
Docente TitolareGiacomo Buonanno
E-mailbuonanno@liuc.it
Office"Torre" (main tower), 2nd floor
Phone0331 572323

Learning Objectives

The course aims to provide the theoretical foundations and the main technical solutions for Operational Research. In particular, Linear Programming, Full Linear Programming and Theory of Games are dealt with.

At the end of the course, the student will be able to apply optimization methods to economic-organizational decision-making problems such as production planning, resource allocation, and the distribution of resources (using appropriate IT tools).

Learning targets

The course aims to provide the theoretical foundations and the main technical solutions for Operational Research. In particular, Linear Programming, Full Linear Programming and Theory of Games are dealt with.

At the end of the course, it is assumed that the student will be able to apply optimization methods to economic-organizational decision-making problems such as production planning, resource allocation, and the distribution of resources (using appropriate IT tools).

Course Content

The course is structured in the following parts:

  1. The general model. Elements of Decision Theory.
  2. Linear programming: geometric solution, simplex algorithm, duality, sensitivity analysis.
  3. Integer programming: transport and assignment problems, branch-and-bound.
  4. Game theory: non cooperative games.

Course Delivery

The course includes:

  1. lectures, where problems and general techniques for their solution are introduced from a theoretical point of view,
  2. practical lessons in computer laboratory where these techniques are applied to real world problems with increasing complexity levels.

Course Etiquette

Students are expected to participate in an active and critical way.

Course Evaluation

The exam can be carried out either face-to-face (in presence) or remotely (distance). In both cases, as part of the teaching activities related to the course, a simulation of the exam will be organized to allow all candidates to better understand the operating procedures of the test and to reduce any operational/organizational problem as much as possible.

Full exam - face-to-face mode

The exam is held in the computerized classrooms (PC laboratories) and consists of a written part based on some open and/or closed questions to be answered in the traditional way (on paper), followed by some practical exercises to be solved using the tools installed on the PCs made available to students.

The organization of the written part (on paper) is traditional, while the practical part (on PC) is partially "open book", i.e. the candidates can use the material distributed to support the lessons during the course.

Full exam - distance mode

The exam consists of two written parts, each followed by an oral part.

  • Each of the two written parts uses a PC for the test and an additional device (smartphone) for control and connection (via zoom). Each written part consists of

    • some questions to be answered directly on the exam platform or by completing files on your PC,

    • some practical exercises to be solved using the tools installed on the PCs available to the candidate (and for which the candidate is responsible for their correct functioning).

The number of questions/exercises is usually between two and four for each written test. The questions or exercises will be proposed one at a time through the platform ecorsi.liuc.it. The candidate must answer the questions or upload the solution of each exercise (composed of one or more files) within the time foreseen for the single exercise. Files uploaded after the established time limit will not be accepted.

  • The oral part following each written test includes one or more questions related to the course program and/or the solution of the written part. Only students who have passed the corresponding written part are admitted to the oral part.

Partial tests

During the course, two partial tests can be scheduled. Each test is organized like the full exam, with one only written part followed by the corresponding oral part. Passing both the partial tests replaces the final exam. The overall evaluation is equal to a combination (usually a weighted average) of the results of the ongoing tests.

The calendar of the partial tests is defined during the year.

Syllabus

Session 101
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Linear programming

Readings:

Session 102
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Graphical (geometric) LP solution

Readings:

Session 103
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

The Simplex Method and Sensitivity Analysis.

Readings:

Session 104
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Duality

Readings:

Session 105
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Game Theory - Non-cooperative games

Readings:

Session 106
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Game Theory - Equilibrium

Readings:

Session 107
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Game Theory - MIxed Strategy

Readings:

Session 108
Hours of lesson: 3
Instructor: C. Rossignoli

Topics:

Game Theory - Extensive Form

Readings:

Session 201
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Spreadsheets (Microsoft Excel) for Modeling and Solving Linear Programming Problems

Readings:

Session 202
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to model and solve transport and assignment problems.

Readings:

Session 203
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to model and solve network flow problems

Readings:

Session 204
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to model and solve Linear Programming problems and to perform an effective sensitivity analysis.

Readings:

Session 205
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to model and solve Integer Programming problems.

Readings:

Session 206
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to model and solve Non-Linear Programming problems.

Readings:

Session 207
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Use of spreadsheets to solve (medium complexity) practical cases.

Readings:

Session 401
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Possible tutoring session with solution of exercises and practical problems.

Readings:

Session 402
Hours of lesson: 4
Instructor: G. Buonanno

Topics:

Possible tutoring session with solution of exercises and practical problems.

Readings:


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