Industrial and Systems Engineering (ISE)

ISE 100 Industrial Employment 0 Credits

Usually following the junior year, students in the industrial engineering curriculum are required to do a minimum of eight weeks of practical work, preferably in the field they plan to follow after graduation. A report is required. Must have sophomore standing.

ISE 111 Engineering Probability 3 Credits

Random variables, probability models and distributions. Poisson processes. Expected values and variance. Joint distributions, covariance and correlation.
Prerequisites: MATH 022 or MATH 096 or MATH 032 or MATH 052

ISE 112 Computer Graphics 1 Credit

Introduction to interactive graphics and construction of multiview representations in two and three dimensional space. Applications in industrial engineering. Must have sophomore standing in industrial engineering.

ISE 121 Applied Engineering Statistics 3 Credits

The application of statistical techniques to solve industrial problems. Regression and correlation, analysis of variance, quality control, and reliability.
Prerequisites: ISE 111 or MATH 231 or IE 111

ISE 131 Work Systems and Operations Management 3 Credits

Workermachine systems, work flow, assembly lines, logistics and service operations, and project management. Operations analysis, methods engineering, work measurement, lean production, and six sigma. Workplace ergonomics, plant layout design, and work management.
Prerequisites: ISE 111 or MATH 231 or IE 111
Can be taken Concurrently: ISE 111, MATH 231, IE 111

ISE 132 Work Systems Laboratory 1 Credit

Laboratory exercises, case studies, and projects in operations analysis, methods engineering, work measurement, and plant layout design.
Prerequisites: ISE 131 or IE 131
Can be taken Concurrently: ISE 131, IE 131

ISE 172 Algorithms in Systems Engineering 0,4 Credits

Use of computers to solve problems arising in systems engineering. Design and implementation of algorithms for systems modeling, systems design, systems analysis, and systems optimization. Computer systems, basic data structures, the design and implementation of efficient algorithms, and application of algorithms to the design and optimization of complex systems such as those arising in transportation, telecommunications, and manufacturing. Weekly laboratory with exercises and projects.
Prerequisites: CSE 004 or CSE 007 or CSE 017

ISE 215 Fundamentals of Modern Manufacturing 3 Credits

Manufacturing processes and systems. Metal machining and forming, polymer shape processes, powder metallurgy, assembly and electronics manufacturing. Introduction to automation, numerical control, and industrial robots.
Prerequisites: MAT 033

ISE 216 Manufacturing Laboratory 1 Credit

Laboratory exercises and experiments in manufacturing processes and systems.
Prerequisites: ISE 215 or IE 215
Can be taken Concurrently: ISE 215, IE 215

ISE 224 Information Systems Analysis and Design 3 Credits

An introduction to the technological as well as methodological aspects of computer information systems. Content of the course stresses basic knowledge in database systems. Database design and evaluation, query languages and software implementation. Students that take CSE 241 cannot receive credit for this course.

ISE 226 Engineering Economy and Decision Analysis 3 Credits

Economic analysis of engineering projects; interest rate factors, methods of evaluation, depreciation, replacement, breakeven analysis, aftertax analysis. decision-making under certainty and risk.
Prerequisites: ISE 111 or MATH 231 or IE 111
Can be taken Concurrently: ISE 111, MATH 231, IE 111

ISE 230 Introduction to Stochastic Models in Operations Research 3 Credits

Formulating, analyzing, and solving mathematical models of real-world problems in systems exhibiting stochastic (random) behavior. Discrete and continuous Markov chains, queueing theory, inventory control, Markov decision process. Applications typically include traffic flow, call centers, communication networks, service systems, and supply chains.
Prerequisites: ISE 111 or IE 111 or MATH 231

ISE 240 Introduction to Deterministic Optimization Models in Operations Research 3 Credits

Formulating, analyzing, and solving mathematical models of real-world problems in systems design and operations. A focus on deterministic optimization models having parameters that are known and fixed. Algorithmic approaches for linear, integer, and nonlinear problems. Solving optimization problems utilizing specialized software.
Prerequisites: MATH 205

ISE 251 Production and Inventory Control 3 Credits

Techniques used in the planning and control of production and inventory systems. Forecasting, inventory models, operations planning, and scheduling.
Prerequisites: ISE 121 and ISE 230 and ISE 240
Can be taken Concurrently: ISE 230, ISE 240

ISE 254 Senior Project 0,3 Credits

The use of industrial and systems engineering techniques to solve a major problem in either a manufacturing or service environment. Problems are sufficiently broad to require the design of a system. Human factors are considered in system design. Laboratory component provides significant industry exposure.
Prerequisites: ISE 226 or ISE 251
Can be taken Concurrently: ISE 226, ISE 251

ISE 255 Senior Thesis I 3 Credits

In-depth study of a research topic in industrial and systems engineering supervised by an Industrial and Systems Engineering department faculty member. Requires completion of a formal research proposal and a public presentation of the proposal at the end of the semester.

ISE 256 Senior Thesis II 3 Credits

Continued in-depth study of a research topic in industrial and systems engineering supervised by an Industrial and Systems Engineering department faculty member. Requires a formal thesis and public presentation of the results.
Prerequisites: ISE 255

ISE 260 (WGSS 260) Algorithms and Social Justice 4 Credits

This course explores how algorithms reflect and magnify social inequality. Topics include race, gender, sexuality, and class in the context of policing and punishment, search engines and social media, and ranking and optimization. Readings, discussions, and assignments are designed to cultivate transdisciplinary competence in the history of science and technology, feminist theory, machine learning, and artificial intelligence, and to encourage peer-to-peer learning across the humanities, social science, and engineering.

ISE 275 Fundamentals of Web Applications 3 Credits

Introduction to web technologies required to support the development of client side and server side components of Internet based applications. Students will be exposed to the problems of design, implementation, and management by way of assigned readings, class discussion, and project implementation. Term project.
Prerequisites: ISE 224 or IE 224 or CSE 241
Can be taken Concurrently: ISE 224, IE 224, CSE 241

ISE 281 Leadership Project 1-3 Credits

Application of leadership principles through team projects with industry. Written report required.
Repeat Status: Course may be repeated.
Prerequisites: ISE 382 or IE 382

ISE 300 Apprentice Teaching 1-4 Credits

ISE 304 Introduction to Mathematics and Statistics for Industrial Engineering 3 Credits

Random variables, probability functions, expected values, statistical inference, hypothesis testing, regression and correlation, analysis of variance, and introduction to design of experiments. Review of linear algebra and an introduction to quantitative analysis, matrices, concepts associated with systems of linear equations and linear optimization, algebraic and geometric models. Credits for this course cannot be applied to any undergraduate degree offered by the Industrial and Systems Engineering (ISE) Department. Consent of department required.
Prerequisites: MATH 023

ISE 308 Simulation 3 Credits

Applications of discrete and continuous simulation techniques in modeling industrial systems. Simulation using a high-level simulation language. Design of simulation experiments. This course is an undergraduate version of ISE 408. A student can receive credit for only one of the following courses: ISE 305, ISE 404, ISE 308, and ISE 408.
Prerequisites: ISE 121

ISE 309 Time Series Analysis 3 Credits

Theory and applications of an approach to process modeling, analysis, prediction, and control based on an ordered sequence of observed data. Single or multiple time series are used to obtain scalar or vector difference/ differential equations describing a variety of physical and economic systems. This course is an undergraduate version of ISE 409. A student cannot receive credit for both ISE 309 and ISE 409.

ISE 310 Design of Experiments 3 Credits

Experimental procedures for sorting out important causal variables, finding optimum conditions, continuously improving processes, and trouble shooting. Applications to laboratory, pilot plant and factory. Must have some statistical background and experimentation in prospect. This course is an undergraduate version of ISE 410. A student cannot receive credit for both ISE 310 and ISE 410.
Prerequisites: ISE 121

ISE 321 Independent Study in Industrial and Systems Engineering 1-3 Credits

Experimental projects in selected fields of industrial engineering, approved by the instructor. A written report is required. Department permission required.
Repeat Status: Course may be repeated.

ISE 324 Industrial Automation and Robotics 3 Credits

Introduction to robotics technology and applications. Robot anatomy, controls, programming, work cell design, sensors, vision systems, using Programmable Logic Controllers. Laboratory exercises. This course is an undergraduate version of ISE 424. A student cannot receive credit for both ISE 324 and ISE 424.
Prerequisites: MATH 205

ISE 327 Facilities Planning and Material Handling 3 Credits

Facilities planning including plant layout design and facility location. Material handling analysis including transport systems, storage systems, and automatic identification and data capture. This course is an undergraduate version of ISE 427. A student can receive credit for only one of the following courses: ISE 319, ISE 327, and ISE 427.
Prerequisites: ISE 131

ISE 332 Product Quality 3 Credits

Introduction to engineering methods for monitoring, control, and improvement of quality. Statistical models of quality measurements, statistical process control, acceptance sampling, and quality management principles. Some laboratory exercises. This course is an undergraduate version of ISE 432. A student cannot receive credit for both ISE 332 and ISE 432.
Prerequisites: ISE 121

ISE 333 Introduction to Systems Engineering and Decision Analysis 3 Credits

Systems Engineering modeling techniques. Architectures for large scale systems design. Includes physical, functional, and operational architectures. Requirements engineering, interface and integration issues, graphical modeling techniques. Additional topics may include: decision analysis techniques for systems, uncertainty analysis, utility functions, multiattribute utility functions and analysis, influence diagrams, risk preference, Analytical Hierarchy and Node Processes in decision making. A student cannot receive credit for both ISE 333 and ISE 356.
Prerequisites: ISE 230 and ISE 240

ISE 334 Operational Excellence 3 Credits

Provides a comprehensive understanding of Operational Excellence within an organization. From defining business strategy and creating measurable initiatives and metrics, students learn various tools, such as Lean and Six Sigma Methodologies, Sales, Operations and Inventory Planning, and Change, and Project Management to optimize the end-to-end value chain. These tools enhance operational and organizational efficiency in complex business environments. This course is an undergraduate version of ISE 434. A student cannot receive credit for both ISE 334 and ISE 434.

ISE 335 Planning and Scheduling in Manufacturing and Services 3 Credits

Models for the planning and scheduling of systems that produce goods or services. Resource allocation techniques utilizing static and dynamic scheduling methods and algorithms. Application areas include manufacturing and assembly systems, transportation system timetabling, project management, supply chains, and workforce scheduling. This course is an undergraduate version of ISE 435. A student can receive credit for only one of the following courses: ISE 335, ISE 435, and ISE 419.

ISE 336 Engineering Project Management 3 Credits

Presents the principles and techniques used in all phases of managing engineering projects that includes the initial phase, planning, execution, control, and closeout. Students develop the analytical skills and awareness necessary for managing engineering projects.

ISE 339 Stochastic Models and Applications 3 Credits

Introduction to stochastic process modeling and analysis techniques and applications. Generalizations of the Poisson process; renewal theory and applications to inventory theory, queuing, and reliability; Brownian motion and stationary processes. This course is an undergraduate version of ISE 439. A student cannot receive credit for both ISE 339 and ISE 439.
Prerequisites: ISE 230

ISE 347 Financial Optimization 3 Credits

Making optimal financial decisions under uncertainty. Financial topics include asset/liability management, option pricing and hedging, risk management and portfolio optimization. Optimization covered includes linear/nonlinear optimization, discrete optimization, dynamic programming and stochastic optimization. Emphasis on use of modeling languages and solvers in financial applications. Requires basic knowledge of linear optimization and probability. This course is an undergraduate version of ISE 447. A student cannot receive credit for both ISE 347 and ISE 447.
Prerequisites: ISE 240

ISE 355 Optimization Algorithms and Software 3 Credits

Basic concepts of large families of optimization algorithms for both continuous and discrete optimization problems. Pros and cons of the various algorithms when applied to specific types of problems; information needed; whether local or global optimality can be expected. Participants practice with corresponding software tools to gain hands-on experience. This course is an undergraduate version of ISE 455. A student cannot receive credit for both ISE 355 and ISE 455.
Prerequisites: ISE 240

ISE 358 Game Theory 3 Credits

A mathematical analysis of how people interact in strategic situations. Applications include strategic pricing, negotiations, voting, contracts and economic incentives, and environmental issues. This course is an undergraduate version of ISE 458. A student cannot receive credit for both ISE 358 and ISE 458.
Prerequisites: MATH 021 or MATH 031 or MATH 051 or MATH 076

ISE 362 (MSE 362) Logistics and Supply Chain Management 3 Credits

Modeling and analysis of supply chain design, operations, and management. Analytical framework for logistics and supply chains, demand and supply planning, inventory control and warehouse management, transportation, logistics network design, supply chain coordination, and financial factors. Students complete case studies and a comprehensive final project. This course is an undergraduate version of ISE 462. A student cannot receive credit for both ISE 362 and ISE 462.
Prerequisites: ISE 230 and ISE 240

ISE 364 Introduction to Machine Learning 3 Credits

Techniques of applied machine learning rather than deep theory behind the algorithms and methods. Programming solutions for machine learning problems using a high-level programming language and associated machine learning libraries. Regression, clustering, principal component analysis, Bayesian methods, decision trees, random forests, support vector machines, and neural networks. This course is an undergraduate version of ISE 464. A student cannot receive credit for both ISE 364 and ISE 464.
Prerequisites: CSE 003 or CSE 007 or CSE 017

ISE 365 Applied Data Mining 3 Credits

Introduction to the data mining process including business problem understanding, data understanding and preparation, modeling and evaluation, and model deployment. Emphasis on hands-on data preparation and modeling using techniques from statistics, artificial intelligence, such as regression, decision trees, neural networks, and clustering. A number of application areas are explored. This course is an undergraduate version of ISE 465. A student cannot receive credit for both ISE 365 and ISE 465.
Prerequisites: ISE 121 or ISE 304

ISE 371 Quality and Process Improvement in Healthcare 3 Credits

The dimensions of Healthcare quality and their definitions, quality metrics, accreditation and other benchmarking and evaluation methods. Change management, project planning and team management. Continuous improvement tools including “lean”, “six-sigma”, and “TQM”. This course is an undergraduate version of ISE 471. A student cannot receive credit for both ISE 371 and ISE 471.

ISE 372 Financial Management in Healthcare 3 Credits

Engineering economics in Healthcare; value metrics (net present value, return on investment, etc.), cost-benefit analysis, capital projects and improvements. Accounting methods in Healthcare systems. Reimbursement methods, organizations, and alternatives. Financial strategy, planning, pricing and capital formation in “for”, and “not for” profit settings. This course is an undergraduate version of the graduate level course ISE 472. A student cannot receive credit for both ISE 372 and ISE 472.
Prerequisites: ((ISE 220 or IE 220) or ((ISE 230 or IE 230) and (ISE 240 or IE 240), ), ) and (ISE 275 or IE 275)

ISE 382 Leadership Development 3 Credits

Exploration and critical analysis of theories, principles, and processes of effective leadership. Managing diverse teams, communication, and ethics associated with leadership. Application of knowledge to personal and professional life through projects and team assignments. This course is an undergraduate version of ISE 482. A student cannot receive credit for both ISE 382 and ISE 482.

ISE 401 Convex Analysis 3 Credits

Theory and applications of convex analysis, particularly as it relates to convex optimization and duality theory. Content of the course emphasizes rigorous mathematical analysis as well as geometric and visually intuitive viewpoints of convex objects and optimization problems.

ISE 402 Operations Research Models and Applications 3 Credits

Applied models in operations research, including models in supply chain management, energy, health care, disaster relief, and/or financial optimization. Models, theorems, algorithms, and skills for translating practical problems into mathematical ones.

ISE 403 Research Methods 3 Credits

Skills for conducting doctoral research. Topics include technical reading, technical writing, computing skills, literature review skills, and research ethics.

ISE 406 Fundamentals of Optimization 3 Credits

Introduction to theory and algorithms for linear, discrete, and convex mathematical optimization. Significant portion dedicated to linear optimization theory from both geometric and algebraic perspectives. Basic coverage of discrete optimization, including modeling techniques and algorithmic ideas for solving discrete optimization problems such as branch-and-bound and cutting planes. Basic introduction to convex optimization, including convex sets and functions, duality theory, and optimality conditions.

ISE 407 Numerical Methods and Scientific Computing 3 Credits

Topics in numerical methods, numerical analysis, and scientific computing including floating point arithmetic, conditioning and stability, data structures for scientific computing, analysis of algorithms, and direct and iterative methods for numerical linear algebra. Emphasis on efficient implementations in modern computing languages.

ISE 408 Simulation 3 Credits

Applications of discrete and continuous simulation techniques in modeling industrial systems. Simulation using a highlevel simulation language. Design of simulation experiments. This course is a version of ISE 308 for graduate students, with advanced assignments. A student can receive credit for only one of the following courses: ISE 305, ISE 404, ISE 308, and ISE 408.

ISE 409 Time Series Analysis 3 Credits

Theory and applications of an approach to process modeling, analysis, prediction, and control based on an ordered sequence of observed data. Single or multiple time series are used to obtain scalar or vector difference/ differential equations describing a variety of physical and economic systems. This course is a version of ISE 309 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 309 and ISE 409.

ISE 410 Design of Experiments 3 Credits

Experimental procedures for sorting out important causal variables, finding optimum conditions, continuously improving processes, and trouble shooting. Applications to laboratory, pilot plant and factory. Must have some statistical background and experimentation in prospect. This course is a version of ISE 310 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 310 and ISE 410.

ISE 411 Networks and Graphs 3 Credits

This course examines the theory and applications of networks and graphs. Content of the courses stresses the modeling, analysis and computational issues of network and graph algorithms. Complexity theory, trees and arborescences, path algorithms, network flows, matching and assignment, primal-dual algorithms, Eulerian and Hamiltonian walks and various applications of network models.

ISE 412 Quantitative Models of Supply Chain Management 3 Credits

Analytical models for logistics and supply chain coordination. Modeling, analysis, and computational issues of production, transportation, and other planning and decision models. Logistics network configuration, risk pooling, stochastic decision-making, information propagation, supply chain contracting, and electronic commerce implication.
Prerequisites: ISE 316 or ISE 426

ISE 414 Uncertainty Quantification 3 Credits

In-depth exploration of the principles, methodologies, and practical applications of managing uncertainty in the context of optimization, operations research, data science, and scientific computing.
Prerequisites: ISE 403 and ISE 429

ISE 415 Optimization Under Uncertainty 3 Credits

Modeling, theory, solution algorithms, and applications of optimization models under uncertainty. Topics include stochastic, robust, and distributionally robust optimization techniques, including the mathematics of obtaining their associated deterministic equivalent optimization problems.

ISE 416 Dynamic Programming 3 Credits

This course is concerned with the dynamic programming approach to sequential decision making under uncertainty, exact solution algorithms, and approximate methods adapted to large-scale problems. Value iteration, policy iteration and lambda-policy iteration are introduced and analyzed using fixed-point theory. The linear optimization approach to dynamic programming is introduced. Special policy structures are studied. Algorithms based on sampling and on the use of linear approximation architectures are covered.
Prerequisites: ISE 316 or IE 316

ISE 417 Continuous Optimization 3 Credits

Theoretical principles underlying continuous (nonlinear) optimization problems and the numerical methods that are available to solve them. Topics include the steepest descent method, Newton's method for unconstrained optimization, necessary and sufficient optimality conditions, duality, line search and trust region methods for unconstrained optimization, derivative-free and quasi-Newton techniques, and other numerical methods relevant for solving continuous optimization problems.

ISE 418 Discrete Optimization 3 Credits

Theory, algorithms, and applications of discrete optimization. Focus on mathematical and algorithmic foundations with emphasis on techniques most successful in current software implementations, such as convexification and enumeration. Use of commercial and open source software and frameworks for solving discrete optimization problems will be discussed.

ISE 422 Quantum Computing Optimization 3 Credits

Quantum computers have the potential to efficiently solve optimization problems that are intractable for classical computers. Foundations and basic concepts of quantum computing are discussed. Sample list of topics include: quantum mechanics of qubits; quantum entanglement; quantum circuits, quantum Fourier transform; the Shor factorization algorithm; the Grover search algorithm; elements of quantum linear algebra and quantum tomography; Quantum approximate optimization algorithm and quantum interior point methods.

ISE 424 Industrial Automation and Robotics 3 Credits

Introduction to robotics technology and applications. Robot anatomy, controls, programming, work cell design, sensors, vision systems, using Programmable Logic Controllers. Laboratory exercises. This course is a version of ISE 324 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 324 and ISE 424.

ISE 426 Optimization Models and Applications 3 Credits

Modeling and analysis of operations research problems using techniques from mathematical programming. Linear programming, integer programming, multicriteria optimization, stochastic programming and nonlinear programming using an algebraic modeling language. A student can receive credit for only one of the following courses: ISE 240, ISE 316, and ISE 426.

ISE 427 Facilities Planning and Material Handling 3 Credits

Facilities planning including plant layout design and facility location. Material handling analysis including transport systems, storage systems, and automatic identification and data capture. This course is a version of ISE 327 for graduate students, with advanced assignments. A student can receive credit for only one of the following courses: ISE 316, ISE 327, and ISE 427.

ISE 429 Probability and Stochastic Processes 3 Credits

Mathematical foundations of probability and stochastic processes for modeling and analyzing real-world phenomena. Modeling and analyzing systems that evolve over time, such as queueing systems. Topics include probabilistic models, fundamental theorems of probability, conditional probability, independence, random variables, distribution functions, laws of large numbers, martingales, Markov chains, Poisson processes, and Brownian motion.

ISE 432 Product Quality 3 Credits

Introduction to engineering methods for monitoring, control, and improvement of quality. Statistical models of quality measurements, statistical process control, acceptance sampling, and quality management principles. Some laboratory exercises. This course is a version of ISE 332 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 332 and ISE 432.

ISE 434 Operational Excellence 3 Credits

Provides a comprehensive understanding of Operational Excellence within an organization. From defining business strategy and creating measurable initiatives/metrics, students learn tools, such as Lean and Six Sigma Methodologies, Sales, Operations and Inventory Planning, and Change, and Project Management to optimize the end-to-end value chain. These tools enhance operational and organizational efficiency in complex businesses. This course is a version of ISE 334 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 334 and ISE 434.

ISE 435 Planning and Scheduling in Manufacturing and Services 3 Credits

Models for the planning and scheduling of systems that produce goods or services. Resource allocation techniques utilizing static and dynamic scheduling methods and algorithms. Application areas include manufacturing and assembly systems, transportation system timetabling, project management, supply chains, and workforce scheduling. This course is a version of ISE 335 for graduate students, with advanced assignments. A student can receive credit for only one of the following courses: ISE 335, ISE 419, and ISE 435.

ISE 436 Engineering Project Management 3 Credits

Presents the principles and techniques used in all phases of managing engineering projects that includes the initial phase, planning, execution, control, and closeout. Students develop the analytical skills and awareness necessary for managing engineering projects. This course is a version of ISE 336 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 336 and ISE 436.
Repeat Status: Course may be repeated.

ISE 439 Stochastic Models and Applications 3 Credits

Introduction to stochastic process modeling and analysis techniques and applications. Generalizations of the Poisson process; renewal theory and applications to inventory theory, queuing, and reliability; Brownian motion and stationary processes. This course is a graduate version of ISE 339. A student cannot receive credit for both ISE 339 and ISE 439.

ISE 441 Financial Engineering Projects 3 Credits

Analysis, design and implementation of solutions to problems in financial services using information technology, mathematical modeling, and other financial engineering techniques. Emphasis on realworld problem solving, problem definition, implementation and solution evaluation.

ISE 443 (MSE 443) Automation and Production Systems 3 Credits

Principles and analysis of manual and automated production systems for discrete parts and products. Cellular manufacturing, flexible manufacturing systems, transfer lines, manual and automated assembly systems, and quality control systems.
Prerequisites: ISE 215 or IE 215

ISE 444 Optimization Methods in Machine Learning 3 Credits

Machine learning models and optimization methods that are used to apply these models in practice. Convex models. Gradient and subgradient methods and their stochastic counterparts. Limits and errors of learning, noise reduction, and nonconvex models. Other techniques and algorithms include acceleration, coordinate descent, alternating-direction methods, first-order constrained convex optimization methods, and second-order methods.

ISE 447 Financial Optimization 3 Credits

Making optimal financial decisions under uncertainty. Financial topics include asset/liability management, option pricing and hedging, risk management and portfolio optimization. Optimization covered includes linear/nonlinear optimization, discrete optimization, dynamic programming and stochastic optimization. Emphasis on use of modeling languages and solvers in financial applications. Requires basic knowledge of linear optimization and probability. This course is a graduate version of ISE 347. A student cannot receive credit for both ISE 347 and ISE 447.
Prerequisites: ISE 426

ISE 455 Optimization Algorithms and Software 3 Credits

Basic concepts of large families of optimization algorithms for both continuous and discrete optimization problems. Pros and cons of the various algorithms when applied to specific types of problems; information needed; whether local or global optimality can be expected. Participants practice with corresponding software tools to gain hands-on experience. This course is a version of ISE 355 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 355 and ISE 455.

ISE 456 Conic Optimization 3 Credits

Modeling, theory, solution algorithms, and applications of conic optimization. Topics include mathematics of conic optimization: second-order cones, semidefinite cones, conic duality, interior-point methods. Applications of conic optimization to combinatorial optimization and other areas of optimization are covered.

ISE 458 Game Theory 3 Credits

A mathematical analysis of how people interact in strategic situations. Applications include strategic pricing, negotiations, voting, contracts and economic incentives, and environmental issues. This course is a version of ISE 358 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 358 and ISE 458.

ISE 462 Logistics and Supply Chain Management 3 Credits

Modeling and analysis of supply chain design, operations, and management. Analytical framework for logistics and supply chains, demand and supply planning, inventory control and warehouse management, transportation, logistics network design, supply chain coordination, and financial factors. Students complete case studies and a comprehensive final project. This course is a version of ISE 362 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 362 and ISE 462.

ISE 464 Introduction to Machine Learning 3 Credits

Techniques of applied machine learning rather than deep theory behind the algorithms and methods. Programming solutions for machine learning problems using a high-level programming language and associated machine learning libraries. Regression, clustering, principal component analysis, Bayesian methods, decision trees, random forests, support vector machines, and neural networks. This course is a version of ISE 364 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 364 and ISE 464.

ISE 465 Applied Data Mining 3 Credits

Introduction to the data mining process including business problem understanding, data understanding and preparation, modeling and evaluation, and model deployment. Emphasis on hands-on data preparation and modeling using techniques from statistics, artificial intelligence, such as regression, decision trees, neural networks, and clustering. A number of application areas are explored. This course is a version of ISE 365 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 365 and ISE 465.

ISE 471 Quality and Process Improvement in Healthcare 3 Credits

The dimensions of Healthcare quality and their definitions, quality metrics, accreditation and other benchmarking and evaluation methods. Change management, project planning and team management. Continuous improvement tools including “lean”, “six-sigma”, and “TQM”. This course is a version of ISE 371 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 371 and ISE 471.

ISE 472 Financial Management in Healthcare 3 Credits

Engineering economics in Healthcare; value metrics (net present value, return on investment, etc.), cost-benefit analysis, capital projects and improvements. Accounting methods in Healthcare systems. Reimbursement methods, organizations, and alternatives. Financial strategy, planning, pricing and capital formation in “for”, and “not for” profit settings. This course is a version of ISE 372 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 372 and ISE 472.

ISE 480 ISE Project 1-3 Credits

Intensive study of an area of industrial and systems engineering with emphasis upon design and application. A written report is required.
Repeat Status: Course may be repeated.

ISE 481 HSE Project 1-3 Credits

Intensive study in health systems engineering with an emphasis upon design and application. Written report is required.
Repeat Status: Course may be repeated.

ISE 482 Leadership Development 3 Credits

Exploration and critical analysis of theories, principles, and processes of effective leadership. Managing diverse teams, communication, and ethics associated with leadership. Application of knowledge to personal and professional life through projects and team assignments. This course is a version of ISE 382 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 382 and ISE 482.

ISE 485 Industrial Engineering Special Topics 1-3 Credits

An intensive study of some field of industrial engineering.
Repeat Status: Course may be repeated.

ISE 486 Operations Research Special Topics 1-3 Credits

An intensive study of some field of operations research.
Repeat Status: Course may be repeated.

ISE 487 Professional Development 0 Credits

Discuss and learn how to implement the tools needed to successfully navigate the employment market, as well as guide students through the process of pursuing a job and internship opportunities.

ISE 489 Readings 1-3 Credits

Intensive readings-based course of some topic in industrial and systems engineering.
Repeat Status: Course may be repeated.

ISE 490 Thesis 1-6 Credits

Thesis course.
Repeat Status: Course may be repeated.

ISE 499 Dissertation 1-15 Credits