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 at providing students with a sound preparation in Probability and Statistic basic concepts and their applications, in such a way that they will better understand and use non-deterministic models in the solution of real life problems that imply 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.

The core course elements include: work study, plant design and process flow study in a manufacturing plant. The student, at the end of the course, must be capable of outlining the design of a production system, outlining the design of a work station in a manufacturing plant, identifying the main work study elements and evaluating, in detail, a company from its operations standpoint.

The logistics course covers different conceptual elements related to Supply Chain management. The basic components of the Supply Chain (customer service, transport management and inventory management) are analyzed from a systemic, comprehensive standpoint. Students gain Logistics Management skills, as they study the basic components and processes from an optimum vendor, resource and client management perspective. Emphasis is made on the fact that the use of new information and communication technologies allows strengthening the efficiency of Logistics processes in the organization. Process integration models are studied, such as the SCOR model, and logistics processes are modeled through the use of mathematical models in the transportation, supply chain strategic design and inventory areas. The analysis methodology includes workshops where the logistics reality is analyzed by studying cases of Colombian companies. In such regard, students are encouraged to use prior knowledge acquired in inventory models, forecast techniques, cost analyses, transport models, optimization techniques and simulation, among other topics.

The course aims to introduce System Dynamics as a useful tool for analysis and understanding behavior of 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, computer simulation tools, generic structures, evaluation of system dynamics projects and critical thinking.

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 main objective of this course is to set the grounds for students to learn how to apply the organizational strategy tools from a systemic perspective, through the appropriate use of their autonomy and the development of their skills to think strategically.

The main objective is to provide the student with basic management information system guidelines, from the financial standpoint, used in organizations for planning and decision-making purposes. The intention, of these guidelines, is to ensure understanding of the accurate decision-making process complexity on a real company. The main subjects of the course include financial statements development and analysis (balance sheet, profit and loss statement and cash flow), depreciation, adjustments by inflation, financial diagnosis, financial grounds and indicators, financial planning, budgets and Cost-Volume-Profit analysis.

The course covers evaluation of investment projects and capital budgeting alternatives. Private engineering and investment projects are observed, as well as social projects. 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 money value through time, evaluate an investment proj- ect 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 financial mathematics, selection among mutually exclusive alternatives, and construction of cash flow, among others.