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
teacher profile teaching materials
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
Programme
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
Prerequisiti
Basic algebraic operations between vectors (linear combination, scalar product) and matrices (linear combination, product, determinant, inverse, rank). Functions of n variables: partial derivatives, gradient Linear Programming: formulations and solution methods. Integer Programming: formulations and solution methods. Graph Theory: formulations and solution methods.Core Documentation
Lecture notes available on the Moodle web page of the courseType of delivery of the course
Classroom lectures and exercises.Attendance
Not mandatory but suggested.Type of evaluation
Learning is assessed through a selective written examination lasting 90–120 minutes and an oral examination. These are intended to assess students’ actual understanding of the concepts and their ability to apply them in real-world contexts. The course also includes one or more optional written midterm assessments. Each consists of one or two exercises and/or one or more theoretical questions divided into open-ended sub-questions, and is intended to assess students’ learning of the material covered in the first part of the course. Each assessment lasts 90–120 minutes. The final examination includes a written examination consisting of two compulsory exercises and an optional theoretical question divided into open-ended sub-questions. It lasts 90–120 minutes. The oral examination consists of one or more questions on the written examination and may include additional theoretical questions. Examination papers from recent years are available on the course Moodle page. The final grade takes several factors into account, including the level and quality of students’ knowledge of the subject matter; their ability to critically analyze the topics covered; the coherence and soundness of the arguments supporting a thesis; their ability to apply theories and concepts to specific cases and contexts; and their use of terminology appropriate to the subject. teacher profile teaching materials
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
Programme
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
Prerequisiti
Basic algebraic operations between vectors (linear combination, scalar product) and matrices (linear combination, product, determinant, inverse, rank). Functions of n variables: partial derivatives, gradient Linear Programming: formulations and solution methods. Integer Programming: formulations and solution methods. Graph Theory: formulations and solution methods.Core Documentation
Lecture notes available on the Moodle web page of the courseReference Bibliography
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.Type of delivery of the course
Classroom lectures and exercises.Attendance
Not mandatory but suggested.Type of evaluation
Learning is assessed through a selective written examination lasting 90–120 minutes and an oral examination. These are intended to assess students’ actual understanding of the concepts and their ability to apply them in real-world contexts. The course also includes one or more optional written midterm assessments. Each consists of one or two exercises and/or one or more theoretical questions divided into open-ended sub-questions, and is intended to assess students’ learning of the material covered in the first part of the course. Each assessment lasts 90–120 minutes. The final examination includes a written examination consisting of two compulsory exercises and an optional theoretical question divided into open-ended sub-questions. It lasts 90–120 minutes. The oral examination consists of one or more questions on the written examination and may include additional theoretical questions. Examination papers from recent years are available on the course Moodle page. The final grade takes several factors into account, including the level and quality of students’ knowledge of the subject matter; their ability to critically analyze the topics covered; the coherence and soundness of the arguments supporting a thesis; their ability to apply theories and concepts to specific cases and contexts; and their use of terminology appropriate to the subject.