## 21210122 - MATHEMATICS OF DECISION MAKING

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.

Curriculum

teacher profile | teaching materials

Programme

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.

Core Documentation

Taha H.A. (2017) Operations Research: An Introduction (Pearson)

Hillier F.S., Lieberman G.J. (2015) Introduction to Operations Research (McGraw-Hill Education)

Type of delivery of the course

By virtue of its very applied nature, the course is organized in: - computer lab activities - exercise sessions - case study analyses. Within a flipped classroom framework, students are encouraged to participate directly and actively in the learning process in a cooperative, as well as competitive environment. The active attitude throughout the lessons is in turn instrumental for the students to better internalize and independently elaborate the underlying elementary meaning that is behind the main mathematical concepts.

Type of evaluation

Ongoing evaluation approach To stimulate an active attitude throughout the course, the students’ behaviour during the classes and willingness to participate in learning activities are taken into account in the evaluation process: more specifically, students who make themselves noteworthy in a positive way (by, e.g., a proactive participation or an excellent effort evident in office hours) are rewarded with positive marks that will contribute to the final grade. Exams Computer-based mid-term exam: to ascertain the comprehension of basic modeling techniques, and the understanding of Microsoft Excel fundamental tools. Final written exam followed by a brief discussion of students’ scripts. It consists of - written questions (on theoretical aspects) - exercises to be solved also with the help of Microsoft Excel solver to verify how the students are able to elaborate independently the main topics of the course, and to rely on mathematical programming techniques and computer software to practically deal with real-world problems in economics.

teacher profile | teaching materials

Mutuazione: 21210122 MATHEMATICS OF DECISION MAKING in Finanza e impresa LM-16 LAMPARIELLO LORENZO

Programme

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.

Core Documentation

Taha H.A. (2017) Operations Research: An Introduction (Pearson)

Hillier F.S., Lieberman G.J. (2015) Introduction to Operations Research (McGraw-Hill Education)

Type of delivery of the course

By virtue of its very applied nature, the course is organized in: - computer lab activities - exercise sessions - case study analyses. Within a flipped classroom framework, students are encouraged to participate directly and actively in the learning process in a cooperative, as well as competitive environment. The active attitude throughout the lessons is in turn instrumental for the students to better internalize and independently elaborate the underlying elementary meaning that is behind the main mathematical concepts.

Type of evaluation

Ongoing evaluation approach To stimulate an active attitude throughout the course, the students’ behaviour during the classes and willingness to participate in learning activities are taken into account in the evaluation process: more specifically, students who make themselves noteworthy in a positive way (by, e.g., a proactive participation or an excellent effort evident in office hours) are rewarded with positive marks that will contribute to the final grade. Exams Computer-based mid-term exam: to ascertain the comprehension of basic modeling techniques, and the understanding of Microsoft Excel fundamental tools. Final written exam followed by a brief discussion of students’ scripts. It consists of - written questions (on theoretical aspects) - exercises to be solved also with the help of Microsoft Excel solver to verify how the students are able to elaborate independently the main topics of the course, and to rely on mathematical programming techniques and computer software to practically deal with real-world problems in economics.

teacher profile | teaching materials

Programme

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.

Core Documentation

Taha H.A. (2017) Operations Research: An Introduction (Pearson)

Hillier F.S., Lieberman G.J. (2015) Introduction to Operations Research (McGraw-Hill Education)

Type of delivery of the course

By virtue of its very applied nature, the course is organized in: - computer lab activities - exercise sessions - case study analyses. Within a flipped classroom framework, students are encouraged to participate directly and actively in the learning process in a cooperative, as well as competitive environment. The active attitude throughout the lessons is in turn instrumental for the students to better internalize and independently elaborate the underlying elementary meaning that is behind the main mathematical concepts.

Type of evaluation

Ongoing evaluation approach To stimulate an active attitude throughout the course, the students’ behaviour during the classes and willingness to participate in learning activities are taken into account in the evaluation process: more specifically, students who make themselves noteworthy in a positive way (by, e.g., a proactive participation or an excellent effort evident in office hours) are rewarded with positive marks that will contribute to the final grade. Exams Computer-based mid-term exam: to ascertain the comprehension of basic modeling techniques, and the understanding of Microsoft Excel fundamental tools. Final written exam followed by a brief discussion of students’ scripts. It consists of - written questions (on theoretical aspects) - exercises to be solved also with the help of Microsoft Excel solver to verify how the students are able to elaborate independently the main topics of the course, and to rely on mathematical programming techniques and computer software to practically deal with real-world problems in economics.

teacher profile | teaching materials

Mutuazione: 21210122 MATHEMATICS OF DECISION MAKING in Finanza e impresa LM-16 LAMPARIELLO LORENZO

Programme

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.

Core Documentation

Taha H.A. (2017) Operations Research: An Introduction (Pearson)

Hillier F.S., Lieberman G.J. (2015) Introduction to Operations Research (McGraw-Hill Education)

Type of delivery of the course

By virtue of its very applied nature, the course is organized in: - computer lab activities - exercise sessions - case study analyses. Within a flipped classroom framework, students are encouraged to participate directly and actively in the learning process in a cooperative, as well as competitive environment. The active attitude throughout the lessons is in turn instrumental for the students to better internalize and independently elaborate the underlying elementary meaning that is behind the main mathematical concepts.

Type of evaluation

Ongoing evaluation approach To stimulate an active attitude throughout the course, the students’ behaviour during the classes and willingness to participate in learning activities are taken into account in the evaluation process: more specifically, students who make themselves noteworthy in a positive way (by, e.g., a proactive participation or an excellent effort evident in office hours) are rewarded with positive marks that will contribute to the final grade. Exams Computer-based mid-term exam: to ascertain the comprehension of basic modeling techniques, and the understanding of Microsoft Excel fundamental tools. Final written exam followed by a brief discussion of students’ scripts. It consists of - written questions (on theoretical aspects) - exercises to be solved also with the help of Microsoft Excel solver to verify how the students are able to elaborate independently the main topics of the course, and to rely on mathematical programming techniques and computer software to practically deal with real-world problems in economics.