CIRIACO D'AMBROSIO | IMIZATION PROBLEMS FOR CYBERSECURITY
CIRIACO D'AMBROSIO IMIZATION PROBLEMS FOR CYBERSECURITY
cod. 0222700027
IMIZATION PROBLEMS FOR CYBERSECURITY
| 0222700027 | |
| DEPARTMENT OF MANAGEMENT & INNOVATION SYSTEMS | |
| EQF7 | |
| DATA SCIENCE AND INNOVATION MANAGEMENT | |
| 2021/2022 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2020 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| MAT/09 | 3 | 21 | LESSONS | |
| MAT/09 | 3 | 21 | LAB |
| Objectives | |
|---|---|
| THE COURSE AIMS TO DEEPEN THE KNOWLEDGE REGARDING THE SOLUTION OF CONTINUOUS LINEAR PROGRAMMING PROBLEMS (PL), TO PRESENT THE FORMULATION TECHNIQUES, THROUGH CONTINUOUS AND INTEGER LINEAR PROGRAMMING MODELS, AND RESOLUTIVE ALGORITHMS FOR INTERGER OPTIMIZATION PROBLEMS. DURING THE COURSE, DIFFERENT CLASSES OF OPTIMIZATION PROBLEMS OF RELEVANT APPLICATION INTEREST WILL BE PRESENTED. KNOWLEDGE AND UNDERSTANDING AT THE END OF THE COURSE THE STUDENT WILL KNOW: - SIMPLEX ALGORITHM FOR SOLVING PROBLEMS OF PL. - THE MAIN FOUNDATIONS OF MATHEMATICAL MODELING OF INTEGER VARIABLE OPTIMIZATION PROBLEMS AND THE TECHNIQUES TO KNOW THE EFFECTIVENESS OF THE PROPOSED MATHEMATICAL MODELS; - SOME RESOLUTION ALGORITHMS BOTH OF THE EXACT TYPE AND OF THE HEURISTIC / METAEURISTIC TYPE FOR SOLVING PLI PROBLEMS. - DESIGN ALGORITHMS FOR SOLVING PLI PROBLEMS. ATTITUDES TO FLEXIBLE UPDATING OF KNOWLEDGE AND SKILLS IN THE FIELD OF OPTIMIZATION AND OPTIMIZATION PROBLEMS IN ORDER TO ADDRESS CYBERSECURITY PROBLEMS. |
| Prerequisites | |
|---|---|
| THERE ARE NOT SPECIFIC PRE-REQUIREMENTS FOR THIS COURSE. |
| Contents | |
|---|---|
| 1. LINEAR PROGRAMMING (PL) (5 HOURS OF LESSON AND 5 HOURS OF LABORATORY) ; SIMPLEX TABLEAU; 2 ALGORITHMS ALTERNATIVE TO THE SIMPLEX METHOD (4 HOURS OF THEORETICAL LESSON AND 4 OF LABORATORY) - ALGORITHM OF THE DELAYED COLUMN GENERATION. 3. INTEGER LINEAR PROGRAMMING (PLI) (6 HOURS OF LESSON AND 6 HOURS OF LABORATORY) - VARIABLES AND LOGICAL CONSTRAINTS; PROBLEMS WITH MULTIPLE OBJECTIVE FUNCTIONS; - PRESENTATION OF THE MAIN COMBINATORIAL PROBLEMS; - VALID INEQUALITIES. 4 SOLUTION APPROACHES FOR INTEGER LINEAR PROGNOSIS PROBLEMS: (6 HOURS OF LESSON AND 6 HOURS OF LABORATORY) EXACT TYPE RESOLUTION METHODS AND EURISTIC APPROACHES: BRANCH AND BOUND; - LOCAL SEARCH ALGORITHMS; - GREEDY ALGORITHM; - TABU SEARCH; |
| Teaching Methods | |
|---|---|
| FRONTAL LESSONS FOR A TOTAL DURATION OF 42 HOURS (TWO MODULES OF 21 HOURS), WHICH TAKE PLACE IN THE CLASSROOM WITH THE AID OF PROJECTIONS. AT THE END OF THE PRESENTATION OF A TOPIC, VARIOUS APPLICATION EXAMPLES AND EXERCISES WILL BE PROVIDED. |
| Verification of learning | |
|---|---|
| THE FINAL EXAM IS DESIGNED TO EVALUATE AS A WHOLE: THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED IN THE COURSE, AS WELL AS THE ABILITY TO APPLY SUCH KNOWLEDGE FOR THE RESOLUTION OF OPTIMIZATION PROBLEMS. THE ORAL EXAMINATION WILL COVER ALL THE TOPICS OF THE COURSE AND ASSESSMENT WILL TAKE INTO ACCOUNT THE KNOWLEDGE DEMONSTRATED BY THE STUDENT CONCERNING BOTH THE THEORETICAL AND APPLICATIVE ASPECTS FOR THE RESOLUTION OF THE OPTIMIZATION PROBLEMS. THE EVALUATION OF THE ORAL EXAMINATION IS EXPRESSED IN THIRTIES. |
| Texts | |
|---|---|
| - GEORGE L. NEMHAUSER, LAURENCE A. WOLSEY, INTEGER AND COMBINATORIAL OPTIMIZATION, 1999 - LECTURE NOTES |
| More Information | |
|---|---|
| -THE COURSE LANGUAGE IS ITALIAN. -PARTICIPATION TO THE LECTURES IS STRONGLY RECOMMENDED. -THE EMAIL ADDRESS OF TEACHER IS: RAFFAELE@UNISA.IT |
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