SIMULATION

Computer science SIMULATION

0512100025
DIPARTIMENTO DI INFORMATICA
COMPUTER SCIENCE
2013/2014



YEAR OF DIDACTIC SYSTEM 2008
SECONDO SEMESTRE
CFUHOURSACTIVITY
648LESSONS
Objectives
- KNOWLEDGE AND UNDERSTANDING:
THE OBJECTIVE OF THE COURSE OF SIMULATION IS THE FORMULATION AND THE ANALYSIS OF SIMPLE THEORETICAL AND SIMULATION MODELS, WITH EMPHASIS ON SERVICE SYSTEMS WITH QUEUES. THE COURSE IS DIVIDED INTO TWO PARTS. THE FIRST PART WILL PROVIDE THE BASIC KNOWLEDGE NECESSARY FOR THE PROBABILISTIC DESCRIPTION OF THE SIMPLEST SERVICE SYSTEMS WITH ONE OR MORE SERVERS, ANALYZING THEIR MAIN INDICES OF PERFORMANCE AND RELIABILITY. THE SECOND PART OF THE COURSE AIMS TO INTRODUCE THE SIMULATION MODELS, ADDRESSING THE PROBLEM OF THE CHOICE OF THE SIMULATOR AND THE PLANNING OF A SIMULATION EXPERIMENT. DURING THE COURSE ARE IDENTIFIED SUITABLE METHODS FOR THE CONSTRUCTION OF SEQUENCES OF PSEUDO-RANDOM NUMBERS UNIFORM AND NON-UNIFORM, BY APPLYING THE APPROPRIATE STATISTICAL TESTS. THE ULTIMATE GOAL IS TO ENABLE STUDENTS TO APPLY THEIR KNOWLEDGE AND THEIR UNDERSTANDING TO THE SIMULATION OF SIMPLE SERVICE SYSTEMS, OBTAINING ADEQUATE ESTIMATES OF THE MAIN INDICES OF PERFORMANCE OF THE SYSTEM.

- APPLYING KNOWLEDGE AND UNDERSTANDING:
THE COURSE OF SIMULATION AIMS TO ENABLE STUDENTS TO PERFORM THE ANALYSIS OF THE PERFORMANCE OF A SERVICE SYSTEM AND TO UNDERSTAND THE POSSIBLE STRATEGIES TO MAKE THE SYSTEM RELIABLE IN ORDER TO AVOID CONGESTION. THE COURSE ALSO AIMS TO ENABLE STUDENTS TO APPLY THEIR KNOWLEDGE AND UNDERSTANDING IN APPLIED CONTEXTS, INCLUDING COMMUNICATION SYSTEMS AND DATA TRANSMISSION, PROCESSING, TRANSPORT, PRODUCTION AND SERVICES.

- MAKING JUDGEMENTS:
THE STUDENTS ARE GUIDED TO LEARN IN A CRITICAL AND RESPONSIBLE FOR EVERYTHING THAT THE TEACHER PRESENTS DURING THE LECTURES. TO HELP STUDENTS IN THE INDIVIDUAL STUDY, THE TEACHER WILL PROVIDE COMPREHENSIVE NOTES DURING THE COURSE OF THE LESSONS, INCLUDING THE VARIOUS TOPICS, THE PROBLEMS ADDRESSED WITH THE RELEVANT EXAMPLES.

- COMMUNICATION AND LEARNING SKILLS:
DURING THE LECTURES STUDENTS ARE CONSTANTLY ENCOURAGED TO INTERVENE ACTIVELY TO SOLVE THE EXERCISES AND PROBLEMS PROPOSED. THEY MAINLY CONCERN THE CALCULATION OF PERFORMANCE INDICES OF SIMPLE SERVICE SYSTEMS, THE DESIGN OF SUITABLE SIMULATION ALGORITHMS AND THE USE OF DATA IN ORDER TO PROVIDE ESTIMATES OF THE INPUT PARAMETERS AND OUTPUT. STUDENTS ARE ENCOURAGED TO COMMUNICATE AT WHOLE CLASS INFORMATION, IDEAS OF DEVELOPMENT AND SOLUTION OF SIMPLE PROBLEMS.
Prerequisites
BASIC KNOWLEDGE OF PROBABILITY
Contents
- INTRODUCTION TO SERVICE SYSTEMS. SOURCE, WAITING CENTER, SERVICE CENTER, DESTINATION. SERVICE DISCIPLINE. MECHANISM OF ARRIVALS AND SERVICE MECHANISM. INTERARRIVAL AND SERVICE TIMES: DETERMINISTIC, UNIFORM, EXPONENTIAL, ERLANG, HYPEREXPONENTIAL. KENDALL'S NOTATION IN THE THEORY OF QUEUES.

- SOME PERFORMANCE MEASURES. STATE OF THE SYSTEM. WAITING TIME IN THE SYSTEM AND IN THE QUEUE. TRAFFIC INTENSITY AND UTILIZATION FACTOR OF THE SYSTEM. LITTLE’S LAW. IDLE AND BUSY PERIODS.

- POISSON PROCESS. BIRTH-DEATH STOCHASTIC PROCESSES. STATISTICAL EQUILIBRIUM. PRINCIPLE OF BALANCE.
MODELS WITH A SINGLE SERVER. SERVICE SYSTEMS M/M/1 , M/M/1/K , M/G/1.

- SERVICE SYSTEM M/M/2. COMPARISON BETWEEN SYSTEMS M/M/1 AND M/M/2. SERVICE SYSTEMS M/M/S AND M/M/S/S. SYSTEMS WITH SERVICE ACCELERATION AND WITH DISCOURAGEMENT.

- INTRODUCTION TO SIMULATION. CLASSIFICATION OF SIMULATORS. MONTE CARLO METHOD AND ITS APPLICATIONS. SIMULATION OF A SERVICE SYSTEM.

- INTRODUCTION TO THE GENERATION OF PSEUDORANDOM SEQUENCES. METHOD OF THE CENTER OF THE SQUARE. METHOD MULTIPLICATIVE CONGRUENTIAL. OTHER TYPES OF CONGRUENT GENERATORS. UNIFORM GENERATORS IN (0.1).

- METHODS FOR THE GENERATION OF CONTINUOUS RANDOM VARIABLES: INVERSION METHOD OF THE DISTRIBUTION FUNCTION AND METHOD OF REJECTION. GENERATION OF SOME CONTINUOUS RANDOM VARIABLES: EXPONENTIAL, NORMAL AND OF ERLANG. METHOD COMPOUND. GENERATION OF AN HYPEREXPONENTIAL RANDOM VARIABLE. METHODS FOR THE GENERATION OF DISCRETE RANDOM VARIABLES. GENERATION OF SOME DISCRETE RANDOM VARIABLES: GEOMETRIC, BINOMIAL AND OF POISSON. SIMULATION OF A POISSON PROCESS.

- STATISTICAL INFERENCE. ESTIMATORS. SAMPLE MEAN AND SAMPLE VARIANCE. HYPOTHESIS TESTING. CHI-SQUARE DENSITY. STATISTICAL TESTS ON THE GENERATED SEQUENZE (OF UNIFORMITY, SERIAL, POKER, GAP).
Teaching Methods
THE TEACHING METHOD INCLUDES THEORETICAL LESSONS SUPPLEMENTED BY EXERCISES, EXAMPLES, AND PROBLEMS ON ALL TOPICS.
Verification of learning
STUDENTS ARE STIMULATED DURING THE LESSONS TO LEARN AND CONNECT IN A SYSTEMATIC MANNER AND CRITICIZES THE VARIOUS TOPICS.
Texts
- JERRY BANKS, JOHN S. CARSON II, BARRY L. NELSON, DAVID M. NICOL (2005) DISCRETE-EVENT SYSTEM SIMULATION. PEARSON EDUCATION INTERNATIONAL;

- SHELDON M. ROSS (2002) SIMULATION ACADEMIC PRESS;

- LECTURE NOTES OF THE TEACHER
More Information
CLASS ATTENDANCE IS STRONGLY RECOMMENDED. THE FINAL DISCUSSION CONSISTS OF AN ORAL EXAMINATION. THE FINAL RESULT DEPEND ON THE KNOWLEDGE AND UNDERSTANDING OF THE BASIC CONCEPTS AND ON THE ABILITY TO MAKE THE NECESSARY CONNECTIONS BETWEEN THE VARIOUS TOPICS COVERED IN THE COURSE.
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