MATHEMATICAL PROGRAMMING

Course objectives

General outcomes: The course aims to provide advanced knowledge of mathematics more directly connected to the learning of basic optimization techniques. In particular, optimization topics concern the mathematical modeling of decision problems and solution algorithms for specific classes of optimization problems. A) knowledge and understanding: Acquire basic knowledge in the filed of mathematical analysis especially in connection with the study of properties of functions of many variables, with the definition of simple decision models, with the solution of simple minimum problems of for functions of many variables. B) applying knowledge and understanding: Ability to study the continuity and differentiability of a function of many variables and to solve some exercises connected with the determination of minimum points of linear or non linear problems. D) E) communication and learning skills: Ability of understanding the nature of some decisional problems by studying the properties of a function of many variables; ability to find the most suitable solution method to solve linear or nonlinear problems

Channel 1

Program - Frequency - Exams

Course program
1. Real valued functions of more than one variable (10 ore) 2. Limits and continuity for functions of than one variable (10 ore) 3. Differentiability for functions of more than one variable (10 ore) 4. Convexity of sets and functions in R^n (5 ore) 5. Maximum and minimum points for functions of more than one variable(10 ore) 6. Mathematical programming models(15 ore) 7. Linear programming (15 ore) 8. Methods for nonlinear programming problems (15 ore)
Prerequisites
having successfully attended the courses: Fondamenti di Matematica; Geometria
Books
G.Liuzzi, M.Sciandrone, "Complementi di Matematica" (Hoepli editore) Teaching notes by Prof. M. Roma
Teaching mode
The course is taught completely in presence
Frequency
Participation to the lectures is optional
Exam mode
In order to pass the exam the student needs a note greater or equal than 18/30. The student has to show a sufficient knowledge on all the topics of the course and has to be able to fomulate a linear programming model. To get the maximum note, 30/30 cum laude, the student has to show an excellent knowledge on all the topics of the course being able to logically link them.
Lesson mode
The course is taught completely in presence
Channel 2
GIAMPAOLO LIUZZI Lecturers' profile

Program - Frequency - Exams

Course program
1. Real valued functions of more than one variable (10 ore) 2. Limits and continuity for functions of than one variable (10 ore) 3. Differentiability for functions of more than one variable (10 ore) 4. Convexity of sets and functions in R^n (5 ore) 5. Maximum and minimum points for functions of more than one variable(10 ore) 6. Mathematical programming models(15 ore) 7. Linear programming (15 ore) 8. Methods for nonlinear programming problems (15 ore)
Prerequisites
having successfully attended the courses: Fondamenti di Matematica; Geometria
Books
G.Liuzzi, M.Sciandrone, "Complementi di Matematica" (Hoepli editore) Teaching notes by Prof. M. Roma
Teaching mode
The course is taught completely in presence
Frequency
Participation to the lectures is optional
Exam mode
In order to pass the exam the student needs a note greater or equal than 18/30. The student has to show a sufficient knowledge on all the topics of the course and has to be able to fomulate a linear programming model. To get the maximum note, 30/30 cum laude, the student has to show an excellent knowledge on all the topics of the course being able to logically link them.
Lesson mode
The course is taught completely in presence
GIAMPAOLO LIUZZI Lecturers' profile

Program - Frequency - Exams

Course program
1. Real valued functions of more than one variable (10 ore) 2. Limits and continuity for functions of than one variable (10 ore) 3. Differentiability for functions of more than one variable (10 ore) 4. Convexity of sets and functions in R^n (5 ore) 5. Maximum and minimum points for functions of more than one variable(10 ore) 6. Mathematical programming models(15 ore) 7. Linear programming (15 ore) 8. Methods for nonlinear programming problems (15 ore)
Prerequisites
having successfully attended the courses: Fondamenti di Matematica; Geometria
Books
G.Liuzzi, M.Sciandrone, "Complementi di Matematica" (Hoepli editore) Teaching notes by Prof. M. Roma
Teaching mode
The course is taught completely in presence
Frequency
Participation to the lectures is optional
Exam mode
In order to pass the exam the student needs a note greater or equal than 18/30. The student has to show a sufficient knowledge on all the topics of the course and has to be able to fomulate a linear programming model. To get the maximum note, 30/30 cum laude, the student has to show an excellent knowledge on all the topics of the course being able to logically link them.
Lesson mode
The course is taught completely in presence
  • Lesson code1022722
  • Academic year2025/2026
  • CourseComputer and Control Engineering
  • CurriculumInformatica
  • Year2nd year
  • Semester1st semester
  • SSDMAT/09
  • CFU9
  • Subject areaAttività formative affini o integrative