Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Introduction to industrial engineering concepts. Fundamentals of systems analysis and modeling. Basics of production and service systems. Computer and programming applications of several industrial engineering topics. Hands-on experience for industrial engineering subjects in team projects

Fundamentals of logic, mathematical induction, basic set theory, relations and functions, fundamental principles of counting, inclusion-exclusion principles, basic graph theory, trees, algorithms for basic industrial engineering and operations research problems on graphs and networks.

Fundamentals of logic, mathematical induction, basic set theory, relations and functions, fundamental principles of counting, inclusion-exclusion principles, basic graph theory, trees, algorithms for basic industrial engineering and operations research problems on graphs and networks.

Introduction to inventory management, deterministic economic quantity models and extensions. Stochastic continuous-review and periodic-review models. Markov chains and Markov processes. Introduction to queueing systems and the Poisson process. Markovian queues, networks and management of queueing systems. Markov decision models and applications. Probabilistic dynamic programming and algorithmic solution methods.

Introduction to modeling with integer variables and integer programming; network models, dynamic programming; convexity and nonlinear optimization; applications of various optimization methods in manufacturing, product design, communications networks, transportation, supply chain, and financial systems.

Facilities design process; strategic facilities planning, product, process, and schedule design, flow, space, and activity relationships, personnel requirements; material handling principles, equipment, unit load concept; facility layout, types, procedures, computer-aided tools; warehousing, order picking, automated storage/retrieval systems; quantitative models for facilities planning; evaluating, selecting, preparing, presenting, implementing, and maintaining the facilities plan.

Network flow models and optimization problems. Algorithms and applications. Minimum spanning tree problem. Shortest path problems. Maximum flow problems, minimum cuts in undirected graphs and cut-trees. The minimum cost network flow problem. Matching problems. Generalized flows. Multicommodity flows and solution by Lagrangean relaxation, column generation and Dantzig-Wolfe decomposition. Network design problems including the Steiner tree problem and the multicommodity capacitated network design problem; their formulations, branch-and-cut approaches and approximation algorithms.

Tools, techniques, and skills needed to analyze decision-making problems characterized by uncertainty, risk, and conflicting objectives. Methods for structuring and modeling decision problems and applications to problems in a variety of managerial decision-making contexts. Structuring decision problems: Decision trees, model building, solution methods and sensitivity analysis; Bayes' rule, the value of information and using decision analysis software. Uncertainty and its measurement: Probability assessment. Utility Theory: Risk attitudes, single- and multiattribute utility theory, and risk management. Decision making with multiple objectives.

Strategy with projects; integration of organization with projects; defining the project; estimating times and costs; developing a network plan; LP approach for CPM; PERT; scheduling resources; mathematical models for resource allocation; reducing project duration; mathematical model for crashing; progress and evaluation; control process; project closure audit process; international projects.

Investments and cash flows, present value and internal rate of return; fixed income securities, yield, duration and immunization; portfolio optimization, mean-variance models, Capital Asset Pricing Model and Arbitrage Pricing Theory; forwards, futures, swaps and risk hedging; pricing derivative securities and options, binomial market models, continuous market models and Black-Scholes equation.

Application and development of mathematical modeling tools for the analysis of strategic, tactical, and operational supply-chain problems. Mathematical programming formulations for integrated planning of capacity and demand in a supply chain. Planning and managing inventories in multi-level systems, centralized versus decentralized control of supply chain inventories. Models and algorithms for transportation and logistics systems design and analysis. Supply chain coordination issues and achieving coordination through contracts. The role of information technology and enterprise resource planning (ERP) and Advanced Planning and Optimization software.

A capstone design course where students apply engineering and science knowledge in an industrial engineering design project proposed by companies from different sectors. Development, design, implementation and management of a project in teams under realistic constraints and conditions. Emphasis on communication, teamwork and presentation skills.

Convex analysis, optimality conditions, linear programming model formulation, simplex method, duality, dual simplex method, sensitivity analysis; assignment, transportation, and transshipment problems.

The basic theory of the Poisson process, renewal processes, Markov chains in discrete and continuous time, as well as Brownian motion and random walks are developed. Applications of these stochastic processes are emphasized by examples, which are drawn from inventory and queueing theory, reliability and replacement theory, finance, population dynamics and other biological models.

Network flow models and optimization problems. Algorithms and applications. Minimum spanning tree problem. Shortest path problems. Maximum flow problems, minimum cuts in undirected graphs and cut-trees. The minimum cost network flow problem. Matching problems. Generalized flows. Multicommodity flows and solution by Lagrangean relaxation, column generation and Dantzig-Wolfe decomposition. Network design problems including the Steiner tree problem and the multicommodity capacitated network design problem; their formulations, branch-and-cut approaches and approximation algorithms.

Tools, techniques, and skills needed to analyze decision-making problems characterized by uncertainty, risk, and conflicting objectives. Methods for structuring and modeling decision problems and applications to problems in a variety of managerial decision-making contexts. Structuring decision problems: Decision trees, model building, solution methods and sensitivity analysis; Bayes' rule, the value of information and using decision analysis software. Uncertainty and its measurement: Probability assessment. Utility Theory: Risk attitudes, single- and multiattribute utility theory, and risk management. Decision making with multiple objectives.

Topics will be announced when offered.

Topics will be announced when offered.