Overview on decision making and Decision Support Systems (DSS). Model Driven DSS.
Mathematical modeling (examples of LP, ILP, and NLP formulations). Basics on computational complexity.
Introduction to Business Analytics. Predictive analytics, optimal classification trees, examples.
Prescriptive analytics. Heuristic algorithms: constructive heuristics, local search, variable depth local search, Tabu Search, Simulated Annealing, genetic algorithms, hints to other metaheuristics.
Robust Optimization.
Study of real world cases (optimization of the flows in the distribution of frozen food, optimization of staff shifts in hospital departments, optimial routing for the collection of material for laboratory analysis, optimal management of the warehouse of a company that deals with online sales, ....).

1. Modelli e metodi decisionali in condizioni di incertezza e rischio, di G. Ghiani, R. Musmanno (a cura di), McGraw-Hill Education, 2009.
2. Slides e notes given by the lecturer

Linear Systems
1. INTRODUCTION TO LINEAR SYSTEMS
1.1. Modelling
1.2. State-Space Representation
2. DIFFERENTIAL EQUATIONS
2.1. Linear Differential Equations with Constant Coefficients
2.2. Exponential Matrix
2.3. Free Evolution
2.4. Forced Evolution
3. RELATIONSHIP BETWEEN REPRESENTATIONS
3.1. From State-Spate to Transfer Function
3.2. From Transfer Function to State-Spate
4. MODAL DECOMPOSITION
4.1. Eigenvalues and Eigenvectors
4.2. Coordinate Transformation
4.3. Diagonalization and Jordanization
5. STRUCTURAL PROPERTIES
5.1. Controllability and Observability
5.2. Controllability and Observability Kalman Forms
5.3. Kalman Canonical Decomposition
7. EIGENVALUE ASSIGNMENT PROBLEM
7.1. Eigenvalue assignment using state feedback
7.1.1. Assignment Theorem (SISO/MIMO)
7.1.2. Assignment Unicity Theorem (SISO)
7.2. Stabilization Problem
7.3. State Asymptotic Observer
7.4. Separation Principle
7.5. Eigenvalue placement using output feedback
8. LINEAR OUTPUT REGULATION PROBLEM
8.1. Full-Information Problem
8.2. Error-Feedback Problem
Nonlinear Systems
9. INTRODUCTION TO NONLINEAR SYSTEMS
9.1. Fundamental Properties
9.2. Lipschitz Condition
9.3. Existence and Unicity of Solution
9.4. Comparison Lemma
10. LYAPUNOV STABILITY
10.1. Autonomous Systems
10.2. Stability Definition
10.3. Stability Theorem (Direct Criterion)
10.4. Chetaev Instability Theorem
10.5. Lyapunov Control Functions (Krasovskii)
10.6. Invariance Principle (LaSalla Theorem)
10.7. Stability Theorem for Linear Systems (Indirect Criterion)

Linear Systems
1. An Introduction to Linear Control Systems, Thomas E. Fortmann, Konrad L. Hitz
2. Lecture Notes (http://gasparri.dia.uniroma3.it/Stuff/complementi_teoria_dei_sistemi.pdf)
3. Sistemi di controllo (Vol. 2), Alberto Isidori

Nonlinear Systems
1. Nonlinear Systems (3rd Edition), Hassan K. Khalil

PART ONE: The company balance sheet

The flow-rate model for representing business dynamics.
- The residual rights of the owners of the enterprise to the wealth produced: the dual aspect principle and the analysis of the sources and uses of resources
The objectives and cognitive limits of accounting:
- the accounting principles;
- accounting systems and accounting methods
The Balance Sheet and the Profit and Loss Account:
- Fixed assets and depreciation, net working capital.
- Inventories and cost of sales
- The Cash Flow Statement and cash flow analysis: the derivation of cash flows.
- Income Statement reclassifications

Balance sheet analysis: profitability, profitability, efficiency and financial indicators

Reference text
R.Anthony, D. F. Hawkins, D. Macrì, K.A. Merchant. The Balance Sheet. Economic analysis for decision making and performance reporting. McGraw-Hill - XV edition. Chapters 1 to 11

SECOND PART: Sustainability in strategic business management

The enterprise as a complex and sustainable system
- Founding principles and corporate sustainability
- The role of stakeholders in addressing sustainability: Agenda 2030-Global Compact-European Union Green Paper, sustainable finance;
- Sustainable strategic management: articulation of strategy - values - objectives - choices resulting from internal and contextual conditions - SWOT analysis;
- Activities and relations for defining a strategy - the value chain and the chain of relations

The context relevant to the enterprise - market and sector analysis
- Description of the competitive context: Porter's five competitive forces model
- Strategic groupings

Sustainable business model
- Concept of value and shared value
- The circular business model paradigm in the principles of the green economy



Sustainable business model
- concept of value and shared value;
- The circular business model paradigm in the principles of the green economy

Sustainable strategic management

- Competitive advantage: concept, determinants and durability
- Cost advantage, differentiation and focus
- Competitive strategies: cost leadership, differentiation, focus
- Collaboration strategies: strategic alliances
- Growth strategies: integration, diversification, internationalisation
- Environmental and social value creation strategies: impact of environmental and social strategies on competitive advantage; areas of intervention
- Strategic and sustainability plan: elaboration and contents

Reference text
Matteo Caroli, Economia e gestione sostenibile delle imprese, McGraw-Hill - 2021

R.Anthony, D. F. Hawkins, D. Macrì, K.A. Merchant. Il Bilancio. Analisi economiche per le decisioni e la comunicazione della performance. McGraw-Hill – XV edizione. Capitoli da 1 a 11

Matteo Caroli, Economia e gestione sostenibile delle imprese, McGraw-Hill – 2021 Capitoli 1, 2, 4, 5, 6

Course programme
1. Introduction to Multi-Criteria Decision Making for Public Service Management Problems
2. Optimization in Project Planning and Scheduling
3. Disjunctive Programming: Scheduling and Routing Models, (Meta)Exact /Heuristic Algorithms
4. Reservations Systems and Interval Scheduling
5. Timetabling with Operator or Tooling Constraints
6. Scheduling and Timetabling in Sport Tournaments
7. Scheduling Network Television Programs
8. Transportation Problems: Tanker/Aircraft/Train Coordination, Scheduling and Routing
9. Decision Support Systems for Real-Time Dispatching of Operations
10. Workforce Scheduling: Days-Off Scheduling, Shift Scheduling, Cyclic Staffing
11. Airline Crew Scheduling
12. Discrete Location Problems
13. Water and Air Quality Management
14. Health Care Delivery

Michael L. Pinedo (Author) “Planning and Scheduling in Manufacturing and Services”, Springer Series in Operations Research, Edition 2005
S.M. Pollock, M.H. Rothkopf, A. Barnett (Editors), “Operations Research and the Public Sector”, Handbooks in Operations Research and Management Science, Volume 6, Edition 1994

1. Non-linear programming
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

Linear Systems
1. INTRODUCTION TO LINEAR SYSTEMS
1.1. Modelling
1.2. State-Space Representation
2. DIFFERENTIAL EQUATIONS
2.1. Linear Differential Equations with Constant Coefficients
2.2. Exponential Matrix
2.3. Free Evolution
2.4. Forced Evolution
3. RELATIONSHIP BETWEEN REPRESENTATIONS
3.1. From State-Spate to Transfer Function
3.2. From Transfer Function to State-Spate
4. MODAL DECOMPOSITION
4.1. Eigenvalues and Eigenvectors
4.2. Coordinate Transformation
4.3. Diagonalization and Jordanization
5. STRUCTURAL PROPERTIES
5.1. Controllability and Observability
5.2. Controllability and Observability Kalman Forms
5.3. Kalman Canonical Decomposition
7. EIGENVALUE ASSIGNMENT PROBLEM
7.1. Eigenvalue assignment using state feedback
7.1.1. Assignment Theorem (SISO/MIMO)
7.1.2. Assignment Unicity Theorem (SISO)
7.2. Stabilization Problem
7.3. State Asymptotic Observer
7.4. Separation Principle
7.5. Eigenvalue placement using output feedback
8. LINEAR OUTPUT REGULATION PROBLEM
8.1. Full-Information Problem
8.2. Error-Feedback Problem
Nonlinear Systems
9. INTRODUCTION TO NONLINEAR SYSTEMS
9.1. Fundamental Properties
9.2. Lipschitz Condition
9.3. Existence and Unicity of Solution
9.4. Comparison Lemma
10. LYAPUNOV STABILITY
10.1. Autonomous Systems
10.2. Stability Definition
10.3. Stability Theorem (Direct Criterion)
10.4. Chetaev Instability Theorem
10.5. Lyapunov Control Functions (Krasovskii)
10.6. Invariance Principle (LaSalla Theorem)
10.7. Stability Theorem for Linear Systems (Indirect Criterion)

Linear Systems
1. An Introduction to Linear Control Systems, Thomas E. Fortmann, Konrad L. Hitz
2. Lecture Notes (http://gasparri.dia.uniroma3.it/Stuff/complementi_teoria_dei_sistemi.pdf)
3. Sistemi di controllo (Vol. 2), Alberto Isidori

Nonlinear Systems
1. Nonlinear Systems (3rd Edition), Hassan K. Khalil

Discrete event simulation, a fundamental methodology for evaluating the performance of complex systems (computational, telecommunications, traffic, etc.)

The topics covered can be grouped into the following three phases:
- Construction of a model of a real system:
- "Execution" of a simulation model
- Analysis of simulation results:

Teacher's material uploaded to the teams

PART ONE: The company balance sheet

The flow-rate model for representing business dynamics.
- The residual rights of the owners of the enterprise to the wealth produced: the dual aspect principle and the analysis of the sources and uses of resources
The objectives and cognitive limits of accounting:
- the accounting principles;
- accounting systems and accounting methods
The Balance Sheet and the Profit and Loss Account:
- Fixed assets and depreciation, net working capital.
- Inventories and cost of sales
- The Cash Flow Statement and cash flow analysis: the derivation of cash flows.
- Income Statement reclassifications

Balance sheet analysis: profitability, profitability, efficiency and financial indicators

Reference text
R.Anthony, D. F. Hawkins, D. Macrì, K.A. Merchant. The Balance Sheet. Economic analysis for decision making and performance reporting. McGraw-Hill - XV edition. Chapters 1 to 11

SECOND PART: Sustainability in strategic business management

The enterprise as a complex and sustainable system
- Founding principles and corporate sustainability
- The role of stakeholders in addressing sustainability: Agenda 2030-Global Compact-European Union Green Paper, sustainable finance;
- Sustainable strategic management: articulation of strategy - values - objectives - choices resulting from internal and contextual conditions - SWOT analysis;
- Activities and relations for defining a strategy - the value chain and the chain of relations

The context relevant to the enterprise - market and sector analysis
- Description of the competitive context: Porter's five competitive forces model
- Strategic groupings

Sustainable business model
- Concept of value and shared value
- The circular business model paradigm in the principles of the green economy



Sustainable business model
- concept of value and shared value;
- The circular business model paradigm in the principles of the green economy

Sustainable strategic management

- Competitive advantage: concept, determinants and durability
- Cost advantage, differentiation and focus
- Competitive strategies: cost leadership, differentiation, focus
- Collaboration strategies: strategic alliances
- Growth strategies: integration, diversification, internationalisation
- Environmental and social value creation strategies: impact of environmental and social strategies on competitive advantage; areas of intervention
- Strategic and sustainability plan: elaboration and contents

Reference text
Matteo Caroli, Economia e gestione sostenibile delle imprese, McGraw-Hill - 2021

R.Anthony, D. F. Hawkins, D. Macrì, K.A. Merchant. Il Bilancio. Analisi economiche per le decisioni e la comunicazione della performance. McGraw-Hill – XV edizione. Capitoli da 1 a 11

Matteo Caroli, Economia e gestione sostenibile delle imprese, McGraw-Hill – 2021 Capitoli 1, 2, 4, 5, 6

Dynamical models of stationary processes and prediction
- Physical laws in engineering and science
- Stochastic processes
- Models for filtering, prediction and control: Input-output models for time series and dynamical systems (AR, ARMA, ARX, ARMAX)

Identification
- Black-box identification (Least Squares and Maximum likelihood methods)
- Model complexity selection
- Cross-validation, FPE (Final Prediction Error), AIC (Akaike Information Criterion) or MDL (Minimum Description Length) techniques
- Recursive identification methods (RLS,ELS,RML). Adaptation via forgetting factor techniques

Bayesian filtering
- The state estimation problem. Filtering, prediction and smoothing.
- Kalman filter, steady-state filter Extended Kalman filter
- Unscented transformation, Unscented Kalman filter
- Grid-based filtering
- Particle filtering

Distributed filtering
- Information filter
- Extended Information filter

Sergio Bittanti, "Model Identification and Data Analysis", John Wiley and Sons Ltd

Manipulators (Chapters of Siciliano et al. Robotics):
- Direct kinematics
- Differential kinematics
- Inverse kinematics
- Trajectory planning
- Statics and manipulability ellipsoids
- Overview of the dynamic model
- Motion control schemes
- Overview of force control schemes

Mobile robotics:
- Basic Topological Concepts (Chapter 4.1, LaValle Planning Algorithms)
- 2D Rigid Bodies: SE(2) (Chapter 4.2.1, LaValle Planning Algorithms)
- Vector Fields and Integral Curves (Chapter 8.3, LaValle Planning Algorithms)
- Differential Models (Chapter 13.1, LaValle Planning Algorithms)
- Control Affine Systems (Chapter 15.4, LaValle Planning Algorithms)
- Motion Control (Chapter 11.6, Siciliano et al. Robotics)
- Multi-Robot Swarming (Chapter 3, Gazi & Passino, Swarm Stability and Optimization)

- Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, and Giuseppe Oriolo. 2009. Robotics: Modelling, Planning and Control. Springer Publishing Company, Incorporated.
- Steven M. LaValle. 2006. Planning Algorithms. Cambridge University Press, USA.
- Veysel Gazi and Kevin Passino. 2011. Swarm Stability and Optimization. Springer Publishing Company, Incorporated.

Manipulators (Chapters of Siciliano et al. Robotics):
- Direct kinematics
- Differential kinematics
- Inverse kinematics
- Trajectory planning
- Statics and manipulability ellipsoids
- Overview of the dynamic model
- Motion control schemes
- Overview of force control schemes

Mobile robotics:
- Basic Topological Concepts (Chapter 4.1, LaValle Planning Algorithms)
- 2D Rigid Bodies: SE(2) (Chapter 4.2.1, LaValle Planning Algorithms)
- Vector Fields and Integral Curves (Chapter 8.3, LaValle Planning Algorithms)
- Differential Models (Chapter 13.1, LaValle Planning Algorithms)
- Control Affine Systems (Chapter 15.4, LaValle Planning Algorithms)
- Motion Control (Chapter 11.6, Siciliano et al. Robotics)
- Multi-Robot Swarming (Chapter 3, Gazi & Passino, Swarm Stability and Optimization)

- Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, and Giuseppe Oriolo. 2009. Robotics: Modelling, Planning and Control. Springer Publishing Company, Incorporated.
- Steven M. LaValle. 2006. Planning Algorithms. Cambridge University Press, USA.
- Veysel Gazi and Kevin Passino. 2011. Swarm Stability and Optimization. Springer Publishing Company, Incorporated.

- Introduction to CPS: applications and evolution
- Modeling CPS
- Communication standards and technologies for CPS
- Real time system
- Fault diagnosis: model based detection-isolation-identification of anomalies
- Model based anomaly detection for cyber attacks

Notes of the course
Scientific papers