Scuola di Ingegneria Industriale
Syllabus
Academic Year 2019/20 First Semester
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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:
Course Delivery
The course includes:
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: |