LEARNING OUTCOMES

The aim of the course is to give students the basic methodological and sw tools for being able to analyze complex logistics and transportation systems in the maritime field. The main performance indices will be described and evaluated, assessing their performance both in terms of efficiency and economic sustainability.

The course is aimed at providing the skills to solve strategic planning problems and developing discrete event simulation models, including their input and output analysis.

AIMS AND LEARNING OUTCOMES

The aim of the course is to give students the basic methodological and sw tools for being able to analyze complex logistics and transportation systems in the maritime field. The main performance indices will be described and evaluated, assessing their performance both in terms of efficiency and economic sustainability.

The course is aimed at providing the skills to solve strategic planning problems and developing discrete event simulation models, including their input and output analysis.

Having in mind applications to maritime and port systems, the main topics are: route evaluation, activity and fleet planning, location and sizing problems, queuing systems, discreve event system, performance evaluation, Petri Nets.

TEACHING METHODS

Frontal lectures in computer classroom, where all students have the possibility to define, develop and analyze the models using sw tools at the same time with the teacher. Group work and seminars are foreseen.

SYLLABUS/CONTENT

According to the aims of the course described above, the contents of the course are as follows:

 1. Basic strategic issues in maritime transport of persons and in port-maritime logistics.     - Route evaluation issues: definition and reliability of routes.
    - Covering and fleet planning problems.
    - Terminal location problems.
 2. Introduction to Discrete Event Simulation. System and model definition. Time Advance Criteria. Input Analysis. Direct use of data. Empirical distributions. Deduction of theoretical distributions. Generating random numbers and random variables. Validation of a simulation model. Analysis of sea-port terminals using discrete event simulation methods.
3. Using the sw environment Witness for Complex Systems Analysis. Inserting and defining elements. Dynamics and flow rules. Computation of the system performance indices. Trade-off cost / performance evaluation of the system.
4. Maritime terminals and ports. Operating Cycles of a Marine Terminal. Performance indices. Productivity indicators. Determination of performance indicators of a sea - port terminal through simulation.
5. Analysis of queueing systems. Performance Analysis in Code Systems. Classification of queueing systems. Performance indices. Single queueing system. Queueing network systems. Simulation of queueing systems. The theory of queues in the analysis of the operation of a maritime terminal. Optimum dimensioning of port service centers.
6. Interdisciplinary laboratory.
   - Evaluation of the performance of logistic systems. Cost analysis. Business plan feasibility and development.
   - Evaluation of the routes. Definition of alternative routes. Cost analysis. Trade-off cost / reliability evaluation.
   - Analysis of flows in intermodal transport networks. Choice of interchange nodes. External cost estimation. Impact of externalities on modal split.
7. Presentation and discussion of case studies.
8. Part only for students of SMID course and Mathematics. Modeling and analysis of complex systems through Petri Nets. Introdction to the Petri Nets. Main components. Dynamics of a system. Queueing models with Petri nets. Structural properties. Calculation of invariants. Stochastic Petri Nets and Equivalence with Markov Chains.

RECOMMENDED READING/BIBLIOGRAPHY

Materials provided by the teacher, including notes, chapters of books and scientific articles.

Some suggested books:

• A.M.Law, Simulation modeling and analysis, IV edizione, McGraw-Hill, 2007
• J. Banks, J.S. Carson,B.L. Nelson, D.M.Nicol, Discrete Event System Simulation, Prentice-Hall,2001.
• W. Reisig. Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies, Springer 2013