The objective of the course is to endow the students with advanced knowledge for operations planning and scheduling in manufacturing and logistics systems. Topics include deterministic operations research methodology for the design of decision support systems, modeling, algorithms and applications.
Curriculum
scheda docente
materiale didattico
Gradient, Hessian
Local minimum, Necessary conditions (first and second order)
Local minimum, Sufficient conditions (secondo order and convex case)
Gradient method, Line search
Newton method,
2. Constrained non-linear programming
KKT conditions
Barrier method and Penalty functions
3. Lot Sizing
EOQ model
Wagner-Whitin Algorithm
Zangwill Algorithm
4. Job Shop Scheduling
Exact methods, Carlier-Pinson Algorithm
Euristhic methods, Nowicki-Smutnicki Algorithm
5. Vehicle Routing Problem
6. Crew Scheduling
7. Plant Location
Mutuazione: 20801784 OTTIMIZZAZIONE DELLA LOGISTICA in Ingegneria gestionale e dell'automazione LM-32 PACCIARELLI DARIO
Programma
1. Non-linear programmingGradient, Hessian
Local minimum, Necessary conditions (first and second order)
Local minimum, Sufficient conditions (secondo order and convex case)
Gradient method, Line search
Newton method,
2. Constrained non-linear programming
KKT conditions
Barrier method and Penalty functions
3. Lot Sizing
EOQ model
Wagner-Whitin Algorithm
Zangwill Algorithm
4. Job Shop Scheduling
Exact methods, Carlier-Pinson Algorithm
Euristhic methods, Nowicki-Smutnicki Algorithm
5. Vehicle Routing Problem
6. Crew Scheduling
7. Plant Location
Testi Adottati
Lecture notesModalità Erogazione
Classroom lectures and exercises.Modalità Frequenza
Not mandatory but suggested.Modalità Valutazione
The exam consists of two steps. In the written part the student is asked to solve two exercises and one or more theoretical questions. The oral part consists of one or more questions on the written part and/or theoretical questions. The texts of the exams of the last years are available on the web page of the course (http://pacciarelli.dia.uniroma3.it/CORSI/MSP/Welcome.html ).
scheda docente
materiale didattico
Gradient, Hessian
Local minimum, Necessary conditions (first and second order)
Local minimum, Sufficient conditions (secondo order and convex case)
Gradient method, Line search
Newton method,
2. Constrained non-linear programming
KKT conditions
Barrier method and Penalty functions
3. Lot Sizing
EOQ model
Wagner-Whitin Algorithm
Zangwill Algorithm
4. Job Shop Scheduling
Exact methods, Carlier-Pinson Algorithm
Euristhic methods, Nowicki-Smutnicki Algorithm
5. Vehicle Routing Problem
6. Crew Scheduling
7. Plant Location
Programma
1. Non-linear programmingGradient, Hessian
Local minimum, Necessary conditions (first and second order)
Local minimum, Sufficient conditions (secondo order and convex case)
Gradient method, Line search
Newton method,
2. Constrained non-linear programming
KKT conditions
Barrier method and Penalty functions
3. Lot Sizing
EOQ model
Wagner-Whitin Algorithm
Zangwill Algorithm
4. Job Shop Scheduling
Exact methods, Carlier-Pinson Algorithm
Euristhic methods, Nowicki-Smutnicki Algorithm
5. Vehicle Routing Problem
6. Crew Scheduling
7. Plant Location
Testi Adottati
Lecture notesBibliografia Di Riferimento
Caramia, Giordani, Guerriero, Musmanno, Pacciarelli, "Ricerca Operativa", Isedi, Italia, 2014. Sassano A., "Modelli e Algoritmi della Ricerca Operativa", Franco Angeli. Carlier J., Pinson E., “An algorithm for solving the job shop problem”, Management Science, 35 (2), 164-175 (1989). Carlier J., Pinson E., “Adjustment of heads and tails for the job-shop problem”, European Journal of Operational Research, 78 (2), 146-161 (1994). Brucker P., Jurisch B., Sievers B., “A branch and bound algorithm for the job scheduling shop problem”, Discrete Applied Mathematics, 49, 107-127 (1994). Nowicki E., Smutnicki C., “A fast taboo search algorithm for the job shop problem”, Management Science, 42 (6), 797-813 (1996). Nowicki E., Smutnicki C., “An advanced tabu search algorithm for the job shop problem”, Journal of Scheduling, 8, 145-159 (2005). Il PDF è scaricabile qui da un PC di Roma Tre. Heinz Gröflin, Andreas Klinkert, "A new neighborhood and tabu search for the Blocking Job Shop", Discrete Applied Mathematics, 157 (2009), 3643-3655.Il PDF è scaricabile qui da un PC di Roma Tre. Yazid Mati and Xiaolan Xie, "Multiresource Shop Scheduling With Resource Flexibility and Blocking", IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, in press Christoph J. Schuster, Jose M. Framinan, "Approximative procedures for no-wait job shop scheduling", Operations Research Letters, 31 (2003) 308 – 318.Il PDF è scaricabile qui da un PC di Roma Tre.Modalità Erogazione
Classroom lectures and exercises.Modalità Frequenza
Not mandatory but suggested.Modalità Valutazione
The exam consists of two steps. In the written part the student is asked to solve two exercises and one or more theoretical questions. The oral part consists of one or more questions on the written part and/or theoretical questions. The texts of the exams of the last years are available on the web page of the course (http://pacciarelli.dia.uniroma3.it/CORSI/MSP/Welcome.html ).