MATHEMATICS OF DECISION MAKING
(objectives)
Main goal: develop skills and background to - understand and formulate real-world problems; - construct mathematical models that abstract the essence of real-world problems; - solve the mathematical models of real-world problems. Specific goals are detailed next according to Dublin descriptors. - Knowledge and understanding: at the end of the course, students are expected to know the fundamental aspects of quantitative methods involving operations research, mathematical programming and analytics as support to decision making. - Applying knowledge and understanding: at the end of the course, students are expected to know how to rely on mathematical programming techniques and computer software (e.g., Microsoft Excel) to practically address real-world problems in economics. - Making judgements: the whole course is organized so as to make the students ask (themselves) the “right” questions. To achieve this objective, computer lab activities, exercise sessions, homework assignments, case study analyses are resorted to in a flipped classroom context. - Communication: students are continuously invited to lead lectures and participate directly and actively in the learning process in flipped classroom schemes. - Lifelong learning skills: lectures are devised to encourage self-motivated pursuit of knowledge. In fact, as detailed above, but also in the light of an ongoing evaluation approach, students are urged to develop a leading role during the lectures in a cooperative, as well as competitive environment.
|
Code
|
21210122 |
Language
|
ENG |
Type of certificate
|
Profit certificate
|
Credits
|
9
|
Scientific Disciplinary Sector Code
|
SECS-S/06
|
Contact Hours
|
60
|
Type of Activity
|
Core compulsory activities
|
Teacher
|
LAMPARIELLO LORENZO
(syllabus)
The course focuses on the fundamental aspects of operations research, mathematical programming and analytics. Main topics are organized according to the following learning units.
Unit 1 - Applied Aspects (40 hours) 1.a (20 hours) Modeling techniques through mathematical programming, and case study analyses (e.g., planning, logistics, capital budgeting, transportation, assignment problems, portfolio selection, …)
1.b (20 hours) How to solve problems’ models: algorithms and computer software Microsoft Excel solver
Unit 2 - Theory (20 hours) Mathematical programming problems properties. More specifically, - linear programming: logic and geometry of linear programming, duality, sensitivity analysis; - basic aspects of integer programming; - a glimpse of nonlinear programming.
(reference books)
Taha H.A. (2017) Operations Research: An Introduction (Pearson)
Hillier F.S., Lieberman G.J. (2015) Introduction to Operations Research (McGraw-Hill Education)
|
Dates of beginning and end of teaching activities
|
From 24/02/2020 to 29/05/2020 |
Delivery mode
|
Traditional
|
Attendance
|
not mandatory
|
Evaluation methods
|
Written test
Oral exam
|
|
|