Courses (organized by level)
Course Descriptions
Undergraduate Courses
ISE 100. Industrial Employment (0) ISE 111. Engineering Probability and Statistics (3)
ISE 112. Computer Graphics (1)
ISE 121. Applied Engineering Statistics (3)
ISE 131. Work Systems and Operations Management(3)
ISE 132. Work Systems Laboratory (1)
ISE 168. Production Analysis (3)
ISE 172. Algorithms in Systems Engineering (4)
ISE 215. Fundamentals of Modern Manufacturing (3)
ISE 216. Manufacturing Laboratory (1)
ISE 224. Information Systems Analysis and Design (3)
ISE 226. Engineering Economy and Decision Analysis (3)
ISE 230. Introduction to Stochastic Models in Operations Research (3)
ISE 240. Introduction to Deterministic Optimization Models in Operations Research (3)
ISE 251. Production and Inventory Control (3)
ISE 254. Senior Project (3)
ISE 255. Senior Thesis I (3)
ISE 256. Senior Thesis II (3)
ISE 275. Fundamentals of Web Applications (3)
ISE 281. Leadership Project (1-3)
ISE 300. Apprentice Teaching (1-4)
ISE 308. Simulation (3)
ISE 309. Time Series Analysis (3)
ISE 310. Design of Experiments (3)
ISE 321. Independent Study in ISE (1-3)
ISE 324. Industrial Automation and Robotics (3)
ISE 327. Facilities Planning and Material Handling (3)
ISE 332. Product Quality (3)
ISE 333. Introduction to Systems Engineering and Decision Analysis (3)
ISE 334. Operational Excellence (3)
ISE 335. Planning and Scheduling in Manufacturing and Services (3)
ISE 336. Engineering Project Management (3)
ISE 339. Stochastic Models and Applications (3)
ISE 347. Financial Optimization (3)
ISE 355. Optimization Algorithms and Software (3)
ISE 358. Game Theory (3)
ISE 362. Logistics and Supply Chain Management (3)
ISE 364. Introduction to Machine Learning (3)
ISE 365. Applied Data Mining (3)
ISE 371. Quality and Process Improvement in Healthcare (3)
ISE 372. Financial Management in Healthcare (3)
ISE 382. Leadership Development (3)
Master's Courses
ISE 304 Introduction to Mathematics and Statistics for Industrial Engineering (3)
ISE 333. Introduction to Systems Engineering and Decision Analysis (3)
ISE 406. Fundamentals of Optimization (3)
ISE 408. Simulation (3)
ISE 409. Time Series Analysis (3)
ISE 410. Design of Experiments (3)
ISE 411. Graphs and Networks (3)
ISE 412. Quantitative Models of Supply Chain Management (3)
ISE 416. Dynamic Programming (3)
ISE 424. Industrial Automation and Robotics (3)
ISE 426. Optimization Models and Applications (3)
ISE 427. Facilities Planning and Material Handling (3)
ISE 432. Product Quality (3)
ISE 434. Operational Excellence (3)
ISE 435. Planning and Scheduling in Manufacturing and Services (3)
ISE 436. Engineering Project Management (3)
ISE 439. Stochastic Models and Applications (3)
ISE 444. Optimization Methods in Machine Learning (3)
ISE 447. Financial Optimization (3)
ISE 455. Optimization Algorithms and Software (3)
ISE 458. (ECO 463). Game Theory (3) (Cross listed course)
ISE 462. Logistics and Supply Chain Management (3)
ISE 464. Introduction to Machine Learning (3)
ISE 465. Applied Data Mining (3)
ISE 471. Quality and Process Improvement in Healthcare (3)
ISE 472. Financial Management in Healthcare (3)
ISE 480. ISE Project (1-3)
ISE 481. HSE Project (1-3)
ISE 482. Leadership Development (3)
ISE 487. Professional Development (0)
ISE 489. Readings (1-3)
ISE 490. Thesis (1-6)
Ph.D. Courses
ISE 401. Convex Analysis (3)
ISE 402. Operations Research Models and Applications (3)
ISE 403. Research Methods (3)
ISE 406. Fundamentals of Optimization (3)
ISE 407. Numerical Methods and Scientific Computing (3)
ISE 411. Graphs and Networks (3)
ISE 412. Quantitative Models of Supply Chain Management (3)
ISE 414. Uncertainty Quantification (3)
ISE 415. Optimization Under Uncertainty (3)
ISE 416. Dynamic Programming (3)
ISE 417. Continuous Optimization (3)
ISE 418. Discrete Optimization (3)
ISE 422. Quantum Computing Optimization (3)
ISE 429. Probability and Stochastic Processes (3)
ISE 444. Optimization Methods in Machine Learning (3)
ISE 447. Financial Optimization (3)
ISE 456. Conic Optimization (3)
ISE 485. Industrial Engineering Special Topics (1-3)
ISE 486. Operations Research Special Topics (1-3)
ISE 489. Readings (1-3)
ISE 499. Dissertation (1-15)
100 Level
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 multi-view 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 MATH 032 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 or IE 131
ISE 168 (EMC 168) Production Analysis (3 Credits)
A course for students not majoring in industrial engineering. Engineering economy; application of quantitative methods to facilities analysis and planning, operations planning and control, work measurement, and scheduling.
Prerequisites: MATH 021 or MATH 031 or MATH 051 or MATH 075 or MATH 076
ISE 172 Algorithms in Systems Engineering (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 017 or CSE 018
For Advanced Undergraduates and Graduate Students
200 Level
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 (1 Credit)
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, 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 Credit)
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 (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 compound 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 275 Fundamentals of Web Applications (1 Credit)
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, repeatable)
The application of statistical techniques to solve industrial problems. Regression and correlation, analysis of variance, quality control, and reliability.
Prerequisites: ISE 382 or IE 382
300 Level
ISE 300 Apprentice Teaching (1-4 Credits)
Offered: As needed
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
Offered: Summer, remote attendance is possible
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
Offered: Spring, remote attendance is possible
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.
Offered: every other Spring (alternates with ISE 339), remote attendance is possible
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
Offered: Summer, remote attendance is possible
ISE 321 Independent Study in Industrial & Systems Engineering (1-3 Credits, repeatable)
Experimental projects in selected fields of industrial engineering, approved by the instructor. A written report is required. Department permission required.
Offered: As needed
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: (MECH 003 or MECH 002) and 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: (MECH 003 or MECH 002) and MATH 205
Offered: every other Fall (alternates with ISE 335)
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
Offered: Spring, remote attendance is possible
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
Offered: Fall
ISE 334 Operational Excellence (was Organizational Planning and Control) (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
Offered: Fall
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.
Offered: every other Fall (alternates with ISE 327), remote attendance is possible
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.
Offered: When possible
ISE 339 Stochastic Models and Applications (was Queueing Systems)(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.
Prerequisites: ISE 230
Offered: every other Spring (alternates with ISE 309), remote attendance is possible
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 techniques covered include linear and 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. Credit will not be given for both ISE 347 and ISE 447.
Prerequisites: ISE 240
Offered: Spring, remote attendance is possible
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
Offered: Spring
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)
Offered: Fall, remote attendance is possible
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
Offered: Spring, remote attendance is possible
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 a version of ISE 364 for graduate students, with advanced assignments. A student cannot receive credit for both ISE 364 and ISE 464.
Prerequisites: CSE 002 or CSE 007 or CSE 017
Offered: Fall, remote attendance is possible
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
Offered: Spring, remote attendance is possible
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.
Offered: Fall, remote attendance is possible
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.
Offered: Spring, remote attendance is possible
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.
Offered: Spring
400 Level
ISE 401 Convex Analysis (4 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.
Offered: When possible
ISE 402 Operations Research Modelling and Applications (3 Credits)
Applied models in operations research, including applications in supply chain, energy, health care, and other fields. Seminal models, theorems, algorithms, and experience in translating practical problems into mathematical ones.
Offered: Spring
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.
Offered: Fall
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.
Offered: Fall
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.
Offered: Fall
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.
Offered: Spring, remote attendance is possible
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.
Offered: every other Spring (alternates with ISE 439), remote attendance is possible
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.
Offered: Summer, remote attendance is possible
ISE 411 Graphs and Networks (3 Credits)
This course examines the theory and applications of networks and graphs. Content of the courses stresses on 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.
Offered: When possible
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.
Offered: When possible
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
Offered: every other Fall (alternates with ISE 422)
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.
Offered: Fall
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.
Offered: When possible
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.
Offered: Spring
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.
Offered: Spring
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.
Offered: Fall (alternates with ISE 414)
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.
Offered: When possible
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.
Offered: Fall, remote attendance is possible
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.
Offered: every other Fall (alternates with ISE 435)
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.
Offered: Fall
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.
Offered: Spring, remote attendance is possible
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.
Offered: Fall
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.
Offered: every other Fall (alternates with ISE 427), remote attendance is possible
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.
Offered: When possible
ISE 439 Stochastic Models and Applications (was Queueing Systems)(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.
Offered: every other Spring (alternates with ISE 409), remote attendance is possible
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.
Offered: Fall
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 techniques covered include linear and nonlinear programming, integer programming, dynamic programming, and stochastic programming. Emphasis on use of modeling languages and solvers in financial applications. Requires basic knowledge of linear programming and probability. This course is a version of IE 347 for graduate students and requires advanced assignments. Credit will not be given for both IE 347 and IE 447.
Prerequisites: ISE 426 or IE 426 or ISE 316 or IE 316
Offered: Spring, remote attendance is possible
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.
Prerequisites: ISE 220 or IE 220 or ISE 240 or IE 240
Offered: Spring
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.
Offered: Spring
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.
Offered: Fall, remote attendance is possible
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.
Offered: Spring, remote attendance is possible
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.
Offered: Fall, remote attendance is possible
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.
Offered: Spring, remote attendance is possible
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.
Offered: Fall, remote attendance is possible
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.
Offered: Spring, remote attendance is possible
ISE 480 ISE Project (3 Credits)
Intensive study of an area of industrial and systems engineering with emphasis upon design and application. A written report is required.
Offered: As needed
ISE 481 HSE Project (3 Credits)
Intensive study in health systems engineering with an emphasis upon design and application. Written report is required.
Offered: As needed
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.
Offered: Spring
ISE 485 Industrial Engineering Special Topics (3 Credits)
An intensive study of some field of industrial engineering.
Offered: As needed
ISE 486 Operations Research Special Topics (3 Credits)
An intensive study of some field of operations research.
Offered: As needed
ISE 487 Professional Development (3 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.
Offered: As needed
ISE 489 Readings (3 Credits)
Intensive readings-based course of some topic in industrial and systems engineering.
Offered: As needed
ISE 490 Thesis (1-6 Credits, repeatable)
Offered: As needed
ISE 499 Dissertation (1-15 Credits, repeatable)
Offered: As needed
To view the entire Lehigh University Course Catalog, click here.
Engineering Elective Course Candidates:
Courses of 3 or more credits with course prefixes of BIOE, CHE, CEE, CSE, ECE, MAT, ME, or MECH for which the prerequisites are met. The courses with these prefixes that are excluded from consideration are listed, below.
The list of excluded courses for an individual ISE major is governed by the catalog in force when admitted to Lehigh. A provisional course offered with one of these prefixes requires departmental approval. Any course meeting these stipulations is denoted “Engineering Elective Requirement” in the ISE program description.
List of courses excluded from consideration as an Engineering Elective:
CHE 171 (CEE 171, EMC 171, ES 171) Fundamentals of Environmental Technology 4 Credits
CEE 010 (ARCH 010) Engineering/Architectural Graphics and Design 3 Credits
CEE 202 CEE Planning and Engineering Economics 3 Credits
CSE 012 Survey of Computer Science 0-3 Credits
CSE 042 (EMC 042) Game Design 3 Credits
CSE 252 (EMC 252, GCP 252, STS 252) Computers, the Internet, and Society 3 Credits
CSE 241 Database Systems and Applications 3 Credits
CSE 379 Senior Project 3 credits
MAT 020 Computational Methods in Materials Science 3 Credits
MAT 221 (STS 221) Materials in the Development of Man 3 Credits
ME 010 Graphics for Engineering Design 3 Credits
ME 240 Manufacturing 3 Credits
A student may take one of the courses in the following course sets for use as an Engineering Elective:
CEE 003 Engineering Statics or MECH 2 Elementary Engineering Mechanics or MECH 3 Fundamentals of Engineering Mechanics 3 Credits
CEE 059 Strength of Materials or MECH 12 Strength of Materials 3 Credits