* Program Structure
* Degree Requirements
* Graduate Curriculum (MS)
* Courses Offered in 2006-2007 Spring
* News and Events
* Facts, Numbers
* Publications
* MS Projects
* Links
* Thesis Preparation Guidelines
* Open Academic Positions
Objectives
Master of Science in Modeling and Simulation (MS in MODSIM) is an interdisciplinary program focusing on operations research modeling, virtual environments, and computer simulation. MODSIM program aims at educating students having sufficient background in various disciplines, and is intended mainly for those who will work as professionals as they pursue academic work. MODSIM curriculum is designed to develop and integrate modeling and simulation skills with special emphasis on application of these skills in virtual environments. The objectives of the program are:
* to educate graduates from different disciplines in the theoretical and practical aspects of modeling, virtual environments, and computer simulation,
* to foster and support interdisciplinary research in the field of modeling and simulation,
* to meet modeling and simulation needs of defense industry, and public and private sectors in general.
General information about the the department is summarized in this presentation (Turkish).
Career Opportunities
Graduates of the program can work in any field related with modeling and simulation.
Program Structure
MODSIM is a non-thesis program and mainly intended for working professionals. It has no deficiency program and has two tracks: Decision Models and Virtual Environments. Each track has background requirements, core courses, and elective courses as defined in the curricula. Students are expected to complete the program in 5 semesters. Students enrolled in MODSIM program pay tuition fee based on the number of credit hours they register every semester. The amount of tuition fee per credit hour is determined at the beginning of every academic year.
Degree Requirements
MS 501 Deterministic Decision Models
Description: Introduction to the methodology of deterministic decision models. Kuhn-Tucker conditions of optimality. Linear programming using the simplex method. Duality theory. The dual simplex method and post optimality analysis. Parametric linear programming. The transportation algorithm. Transshipment and assignment problems. Integer programming models and an introduction to enumerative algorithms. Dynamic programming.
MS 515 System Simulation
Description: Simulation methodology and model building. Modelling with a simulation language. Random variate generation. Basic issues in the design, verification and validation of simulation models. Advanced simulation modelling concepts in process interaction orientation. Examples will be based on modelling of defense systems. Station submodels. Continuous and mixed simulation. Introductory output analysis for a single system and comparison of alternatives.
MS 521 Object-Oriented Programming
Description: Review of data structures Using C++. Introduction to Object-Oriented Programming Languages. Abstraction, approaches to modular program design, principles of abstract data types, basic concepts of objects: local variables and methods. Classes and instances, single and multiple inheritance and object hierarchies. Principles of object-oriented software development. Overview of and experience with the object-oriented programming environments such as C++, Java, through programming assignments and possibly a term project.
MS 531 Distributed Simulation
Description: Introduction to DIS. The DIS protocol. DMSO s. High Level Architecture (HLA) and Run-Time Infrastructure (RTI). Representing synthetic environments. Federation development process .
MS 590 Graduate Seminar
Description: This course is designed to expose MODSIM students to various research areas in modeling and simulation. Speakers from industry and acemedia are invited to give talks in their field of interest. Second yearMODSIM students with significant modeling and simulation experience may also be asked to represent their projects.
MS 591 Research Methods in MODSIM
MS 592 MS Project
Decision Models Track Core Courses
MS 502 Stochastic Decision Models
Description: Review of probability theory and random variables. Sequence of random variables, convergence concepts. Stochastic processes. Queuing problems based on birth and death models. Introduction to renewal theory. Applications in reliability and replacement models. Semi-Markov processes. Poisson processes, shot noise; Markov processes; orthogonal expansions, least mean square error estimation.
MS 503 Mathematical Modeling and Applications
Description: The aim of this course is to develop better skills in building and understanding mathematical modeling. Deterministic models in the areas of transportation, distribution, location, production and economic planning are analyzed.
MS 522 Computer Graphics
Description: Introduction to computer graphics. The rendering pipeline. Rasterization algorithms. Two-dimensional and three-dimensional transformations. Quaternions. Hierarchical modelling. Animation. Viewing transformations. Rendering basics. Illumination and color models. Geometrical Modelling. Hidden surface elimination problem. Shading, deformation, ray tracing, radiosity, texture mapping, fractal representation and various other advanced techniques are discussed. Concepts of motion are introduced for the generation of digital animation.
Virtual Environments
MS 529 Software Engineering
Description: Software development process is explained within its engineering perspective, through a variety of traditional methods. With an emphasis on modeling techniques for the problem definition and design, traditional approaches are compared to contemporary conceots. New methods and current research in defining future technology are introduced.
Elective Courses
MS 504 Mathematical Models in Defense Analysis
Description: Basic LP models. Lanchester models. Deterministic combat models. Probabilistic combat models. Strategic defense. Tactical engagements. Homogenous combat models. Heterogeneous combat models. Threat assessment. Strategic stability. Mathematical models of combat. War games.
MS 506 Combinatorial Analysis
Description: What is Combinatorics? Basic counting rules. Recurrence Relations. Divide and conquer algorithms. Deterministic Decision Models Methods: Linear programming, integer programming, nonlinear programming, enumeration, dynamic programming. Analysis of algorithms: worst-case, average. Applications: Knapsack, Traveling Salesman, Chinese Postman, Spanning Tree, Steiner Tree, Set Partitioning, Cell Formation, Assembly Line Balancing. Heuristics: greedy, divide and conquer, local search: interchange, look-ahead, simulated annealing, genetic algorithms, neural networks
MS 510 Scheduling Models
Description: Scheduling and sequencing problems. Basic formulation. Single processor, multi processor scheduling procedures and heuristics. Scheduling approaches. Priority rules and job shop scheduling.
MS 513 Decision Analysis
Description: Maximizing expected monetary value. Maximizing expected utility. Judgmental probabilities. Value of information. Normal form of analysis. Risk sharing.
Name: MS 514 Decision Support System Design and Implementation
Description: Individual and organizational decision making. Normative and behavioral models of decision making. Utility functions. Basic concepts of DSS. Data collection, database management, modeling support user interface design issues. EIS, ES, intelligent DSS. Integration of MSS. Basics of modeling, model building blocks. Implementation issues.
MS 516 Simulation Output Analysis
Description: Simulation methodology and its comparison with other techniques, discrete change simulation concepts. Selecting input distributions, random variate generation, statistical analysis of output. Selected applications of simulation
MS 517 Statistical Data Analysis
Description: Computer aided exploration, analysis and classification of data and empirical model building in engineering through the use of descriptive statistics, random sampling, probability distribution fitting, analysis of variance, regression analysis, discrimination and classification and clustering.
MS 523 Virtual Reality
Description: The selected topic for this semester will be virtual reality. The emphasis will be on input and display technologies and on computational models: Stereoscopic display, head-mounted displays, holographic displays, force display, tracking technologies. Building and displaying virtual worlds. Applications of virtual reality.
MS 525 Computer Communication and Networking
Description: Basics of data communication, and computer networks, ISO/OSI basic reference model. Physical, data-link, network, and transport layers. Routing, flow control, congestion control. Internetworking. TCP/IP suite of protocols. Higher layer protocols. Contemporary network architectures.
MS 527 Artificial Intelligence
Description: Problem-solving techniques: state-space approach, problem-reduction approach, problem model, problem representation, exhaustive search algorithms (breadth-first, depth-first, iterative deepening, and other strategies), heuristic search algorithms (A*). Game-playing. Knowledge representation and reasoning: syntax, semantics, and proof theory (deductive inference) of propositional logic, first-order predicate logic, production systems, semantic nets, and frames. Knowledge base, expert systems, inference engine.
MS 541 Human Computer Interfacing
Description: Information processing and information-processing models. Information measurement and channels. Human performance in information-transmission tasks. Continuous information. Fundamental considerations in modelling the human operator in a control system. Sensory modalities and displays. Neuromuscular characteristics and control-handle/console design. Human-operator adaptation. Decision making and utility. Signal detection. Dynamic decision making. The study of man-computer interaction. The physical interface. The cognitive interface. Designing interactive systems.
MS 551 Fundamentals of GIS
Description: Understanding of Information Systems, basic concepts, introduction to Geographic Information Systems (GIS), Data Conversion, available technology, hardware, software, peripherals, use of GIS in decision making. Basic project design steps for data conversion, raster to vector conversion and GIS, database design, automation of data, Query and analysis of spatial data. Sample projects, computer applications.
MS 561 Physics-Based Modeling
Description: Review of continuous and discerete time signals and systems. Space-time domain representations of signals. Modeling and simulation of active and passive sensor systems. Sampling and noise in physical systems. Applications in infrared and color imaging and radar or acoustic signal processing.
MS 701 Logistics Engineering and Management
Description: Introduction to logistics engineering and management. Commonalities and differences of military logistics and industrial logistics. Acquisition issues: research, design, test, production, construction. Operations management: technical data, personel, facilities, utilities and energy.
Product distribution planning and control: transportation, traffic and material handling. Software market: operating and maintenance software. Maintenence system design: customer service, field, suplier factory maintenance. Equipment test methods and cost analyses. Training systems: operator and maintenance training. Supply support systems: spares, inventory management and material support. Retirement and disposal.