2000

The course covers mathematical modeling, the algorithmic ideas behind it and the mathematical properties of optimization models. It familiarizes the student with mathematical programming packages. The main subjects are: Linear optimizations problems and its geometrical characterization, improving search, Simplex Method, initialization algorithms e.g. two-phase method, Big M method; duality theory, sensitivity analysis and Linear problems with special structures like transport and transfer applications. Finally, a brief introduction to the Branch-and Bound Method, is presented.

This course is intended to provide students with a sound preparation in stochastic processes basic concepts, and queuing and simulation theory, which enable them to better understand and use non-deterministic models in real problem formulation and solution. The course is divided in two parts: Discrete Time Stochastic Processes and Continuous Time Stochastic Processes.

Simulation enables the study of the behavior in a real system or a system proposed under present functioning conditions or under different operating scenarios. It finds increasing applicability s due to its high versatility, the inherent complexity reached by numerous modern systems, and the growing computing capacity, among other reasons. This course is oriented to manufacture and service system simulation, although it is also applicable in many other areas. Discrete simulation is highlighted but continual simulation elements are also included. Aspects such as modeling, experimentation, input and output information analysis, random variables generation, and variance reduction techniques, among others, are addressed.

This course is aimed to provide students with a comprehensive preparation in Probability and Statistic basic concepts and their applications, in such a way that they will better understand and use probabilistic models in the solution of real life problems that involve risk and uncertainty, as well as in statistic data management and analysis.

The course is focused on methods and statistics techniques. Parameter Estimation.Variability and standard error of estimators.Confidence interval, hypothesis testing, p- value.Analysis of Variance and experimental design.Linear Model and Regression analysis with emphasis in categorical variables and multicollinearity.

The course covers the basics of production planning and control operations. The main topics are: forecasting, aggregated planning, inventory systems and scheduling. The student should be able to identify, formulate and solve problems using the tools presented in the course. It is expected that after students have been exposed to current approaches they will be able to adapt them to real situations in manufacturing and service companies.

This course focuses on introducing students to fundamental concepts and tools to analyze and improve operations in manufacturing and services industries. The main subjects include work study, plant design and process flow study in manufacturing operations. The student, at the end of the course, must be capable of analyzing processes and infrastructure elements of production systems in order to identify improving alternatives from its operations standpoint. Complementary to class sessions, students develop a team-work project in a production company to analyze a real environment and put in practice concepts and tools.

The course aims to introduce System Dynamics as a way for developing  systemic thinking and understanding the behavior of complex systems,  particularly of social systems, in order to develop better skills in  policy design. Course subjects include: introduction to systems thinking  and dynamic complexity, basic concepts of System Dynamics such as causal loop diagrams, stock and flow models, model building, computer simulation tools, generic structures, evaluation of models, critical thinking and design of systemic policies.

The student should become familiar with the evolution of the concept of organizations so as to appreciate different dimensions to observe and to conceptualize such social systems. He should also be able to observe organizations from a systemic point of view; finally, he should be able to prepare a technical bibliography review report on an organizational topic.

The course covers evaluation of investment projects and capital budgeting alternatives. The different concepts introduced will allow the student to determine the financial viability and feasibility of an investment project. At the end of the course, the student must be able to understand the concept of time value of money, evaluate an investment project and calculate its net present value and its internal rate of return, evaluate a project under uncertainty and risk, as well as its sensitivity to the variables involved. Some of the course subjects include basic financial mathematics, selectin among mutually exclusive alternatives, and construction of cash flows, among others.