The goal is for students to develop the experience and intuition to gather and build new datasets and answer substantive questions. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. Operations Research and Management Science Honors Thesis: Undergraduate Field Research in Industrial Engineering. This course is targeted at understanding RM problems in the booming environment of online platforms and marketplaces with applications ranging from online advertising to ride-sharing markets. Formulation and model building. Introduction to Martinjales. Prerequisites: upper division standing. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2017, Fall 2014, Spring 2014 New issues raised by the World Wide Web. Course Objectives: Control and Optimization for Power Systems: Read Less [-], Terms offered: Spring 2009, Spring 2007, Spring 2006 Topics covered are from a broad range that includes demand modeling, inventory management, facility location as well as process flexibility, contracting, and auctions. Students develop research designs and present each week and formally for their final. This course focuses on the design of service businesses such as commercial banks, hospitals, airline companies, call centers, restaurants, Internet auction websites, and information providers. Students will also learn how to use computer simulation to replicate and analyze these events. While these two programs share some core technical courses, the IEOR Master of Engineering program prepares students for engineering leadership and offers a curriculum with a balance of management and technical content. Prior exposure to optimization is helpful but not strictly necessary. Prerequisites: No prerequisites except some Python programming skills, which can be met by COMPSCIC8 (or any other Python-based course), Introduction to Optimization Modeling: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 This course is designed primarily for upper-level undergraduate and graduate students interested in examining the major challenges and success factors entrepreneurs and innovators face in conducting business, globalizing a company product or service, or investing in South Asia. Dynamic Production Theory and Planning Models: Terms offered: Spring 2017, Spring 2014, Spring 2011, Terms offered: Spring 2016, Spring 2015, Spring 2014, Group Studies, Seminars, or Group Research. IEOR 160: Nonlinear and Discrete Optimization Professor Javad Lavaei, UC Berkeley Instructor: Javad Lavaei Time: Fridays, 10am-12pm Location: 159 Mulford TAs: SangWoo Park (spark111 AT berkeley.edu) and Yatong Bai (yatong_bai AT berkeley.edu) Grader: Natalie Andersson (natalieandersson AT berkeley.edu) Introduction to Optimization Modeling: Read More [+]. the instructor in order to solidify the lectures into practical experience using Python for analytics. Prerequisites: Students should have a solid knowledge of calculus, including multiple variable integration, such as MATH1A and MATH1B or MATH16A and MATH16B, as well as programming experience in Matlab or Python. The course is focused around intensive study of actual business situations through rigorous case-study analysis. In this course, students will learn essential Product Management skills by putting theory into practice, on a product or idea of your choosing. Dynamic programming and its role in applications to shortest paths, project management and equipment replacement. The focus is on converting the theory of optimization into effective computational techniques. The course will discuss applications such as dieting, scheduling, and transportation. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. Operations Research & Management Science, B.S. Application of systems analysis and industrial engineering to the analysis, planning, and/or design of industrial, service, and government systems. Fall 2017: IEOR 160 - Nonlinear and Discrete Optimization. The course focuses on discrete-time Markov chains, Poisson process, continuous-time Markov chains, and renewal theory. learn, Bokeh, and relevant optimization and simulation software. Please use this as a guide for planning purposes. Relationship with linear programming, transportation problems, electrical networks and critical path scheduling. Prerequisites: Graduate Standing or ASE (Academic Student Employee) Status, Fall and/or spring: 15 weeks - 2 hours of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Professional course for teachers or prospective teachers, GSI Proseminar on Teaching Engineering: Read Less [-], Terms offered: Fall 2010, Fall 2008, Spring 2008 With more than 4,000 alumni, 20 faculty, 20 advisory board members and 400 students, the IEOR department is a rapidly growing community equipped with tools and resources to make a large impact in industry, academia, and society. Familiarity with algorithm design and mathematical maturity recommended, Fundamentals of Revenue Management: Read Less [-], Terms offered: Fall 2020, Fall 2019, Fall 2018 This program prepares you to understand, design, and analyze complex systems through IEOR technical coursework and helps you cultivate an entrepreneurial mindset and develop leadership skills with a degree from Haas. Mathematical and computer methods for design, planning, scheduling, and control in manufacturing and distribution systems. The second half of the course will discuss the most recent topics in financial engineering, such as credit risk and analysis, risk measures and portfolio optimization, and liquidity risk and models. Courses Industrial Engineering and Operations Research (IND ENG) Industrial Engineering and Operations Research (IND ENG) Courses Expand all course descriptions [+] IND ENG 24 Freshman Seminars 1 Unit [+] IND ENG 66 A Bivariate Introduction to IE and OR 3 Units [+] IND ENG 98 Supervised Group Study and Research 1 - 3 Units [+] Polynomial time algorithms. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. Terms offered: Spring 2019, Spring 2017 Undergraduate Field Research in Industrial Engineering: Read More [+], Prerequisites: Completion of two semesters of coursework, Fall and/or spring: 15 weeks - 1-12 hours of fieldwork per week, Summer: 6 weeks - 2.5-30 hours of fieldwork per week8 weeks - 1.5-22.5 hours of fieldwork per week10 weeks - 1.5-18 hours of fieldwork per week, Undergraduate Field Research in Industrial Engineering: Read Less [-], Terms offered: Spring 2023, Spring 2022, Fall 2021 Convex sets and convex functions; local optimality; KKT conditions; Lagrangian duality; steepest descent and Newton's method. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. Units may not be used to meet either unit or residence requirements for a master's degree. Course Objectives: This course provides an introduction to the field of Industrial Engineering and Operations Research through a series of lectures by IEOR faculty. Embedded Markov chains. A deficient grade in INDENG174 may be removed by taking IND ENG 131. Sensitivity analysis, parametric programming, convergence (theoretical and practical). Uncertainty; preference under risk; decision analysis. Development of analytical tools for improving efficiency, customer service, and profitability of production environments. Graphical methods and computer software using event trees, decision trees, and influence diagrams that focus on model design. Introduce students to modern techniques for developing computer simulations of stochastic discrete-event models and experimenting with such models to better design and operate dynamic systems. Learn more about our game-changing alumni, and view our recent newsletters. Course Objectives: Stochastic simulation ideas will be introduced and used to obtain the risk-neutral geometric Brownian motion values for certain types of Asian, barrier, and lookback options. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. Credit Restrictions: Students will receive no credit for INDENG156 after completing INDENG256. Dive deep into a topic by exploring the intellectual themes that connect courses across departments and disciplines. In this graduate course, we focus on the systematic design of databases and interfaces for commercial and industrial applications. Course Objectives: Provide an introduction to the field of Industrial Engineering and Operations Research through a series of lectures. When you print this page, you are actually printing everything within the tabs on the page you are on: this may include all the Related Courses and Faculty, in addition to the Requirements or Overview. Supervised independent study for lower division students. Course Objectives: 2. This course is a probability course and cannot be used to fulfill any engineering unit or elective requirements. Queueing Theory: Read More [+], Terms offered: Fall 2021, Spring 2018, Spring 2017 Convex optimization as a systematic approximation tool for hard decision problems. After reviewing each concept, we explore implementing it in Python using libraries for math array functions, manipulation of tables, data architectures, natural language, and ML frameworks. Technology Firm Leadership: Read More [+]. Through these examples, exercises in R, and a comprehensive team project, students will gain experience understanding and applying techniques such as linear regression, logistic regression, classification and regression trees, random forests, boosting, text mining, data cleaning and manipulation, data visualization, network analysis, time series modeling, clustering, principal component analysis, regularization, and large-scale learning. Advanced Mathematical Programming: Read More [+], Advanced Mathematical Programming: Read Less [-], Terms offered: Spring 2016, Spring 2015, Spring 2014 30% Notebook with Lecture Notes. Familiarize students in leading methodologies for solving integer optimization problems, and techniques in these methodologies. Elective course that provides a systematic evaluation of decision-making problems under uncertainty. The course deals with discrete optimization problems and their complexity. May not be used for unit or residence requirements for the doctoral degree. Tau Beta Pi Engineering Honor Society, California Alpha Chapter Recommended, but not required to be taken after or along with Engineering 198, Fall and/or spring: 15 weeks - 2 hours of lecture per week, Cases in Global Innovation: China: Read Less [-], Terms offered: Prior to 2007 Review of linear and nonlinear optimization models, including optimization problems with discrete decision variables. Design activities and discussions to promote learning and provide practice in course concepts and objectives.4. With the growing complexity of providing healthcare, it is increasingly important to design and manage health systems using engineering and analytics perspectives. Introduction to Convex Optimization: Read More [+], Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 2 hours of laboratory per week, Formerly known as: Electrical Engineering C227A/Industrial Engin and Oper Research C227A, Introduction to Convex Optimization: Read Less [-], Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017 Branch and Bound; Cutting plane methods; polyhedral theory. With the growing complexity of providing healthcare, it is increasingly important to design and manage health systems using engineering and analytics perspectives. This is an introductory course in probability designed to develop a good understanding of uncertain phenomena and the mathematical tools used to model and analyze it. Methods for evaluating real options will be presented. Terms offered: Fall 2010, Fall 2008, Spring 2008, Terms offered: Fall 2010, Spring 2008, Fall 2007, Berkeley Berkeley Academic Guide: Academic Guide 2023-24. Cal Students: Please apply with your CalCentral berkeley.edu email by 12/5/2022 or 1/5/2023 PST to receive . Approximations of combinatorial optimization problems, of stochastic programming problems, of robust optimization problems (i.e., with optimization problems with unknown but bounded data), of optimal control problems. Elementary queueing models; comparing single- and multiple-server queues. The course is focused first on developing an open-ended-real world project relating to data science. Topics include: preparing a syllabus; public speaking and coping with language barriers; creating effective slides and exams; differing student learning styles; grading; encouraging diversity, equity, and inclusion; ethics; dealing with conflict and misconduct; and other topics relevant to serving as an effective teaching assistant. business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- This course will not require pre-requisites and will present the core concepts in a self-contained manner that is accessible to Freshmen to provide the foundation for future coursework. Includes formulation of risk problems and probabilistic risk assessments. Cases will include both U.S. companies seeking to enter emerging markets and emerging market companies looking to expand within their own nations or into markets in developed nations. This course introduces unconstrained and constrained optimization with continuous and discrete domains. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Terms offered: Spring 2022, Spring 2021, Fall 2020. strength of Linear Programming relaxations. Welcome to UC Berkeleys Industrial Engineering and Operations Research Department. For students to gain some project-based practical data science experience, which involves identifying a relevant problem to be solved or question to be answered, gathering and cleaning data, and applying analytical techniques.6. Analytical techniques for the improvement of manufacturing performance along the dimensions of productivity, quality, customer service, and throughput. Each math concept is linked to implementation using Python using libraries for math array functions (NumPy), manipulation of tables (Pandas), long term storage (SQL, JSON, CSV files), natural language (NLTK), and ML frameworks. Repeat rules: Course may be repeated for credit with instructor consent. Techniques for yield analysis, process control, inspection sampling, equipment efficiency analysis, cycle time reduction, and on-time delivery improvement. exploratory analytics to systems analytics in an industry context, including communication of It also discusses applications to queueing theory, risk analysis and reliability theory. Applied Data Science with Venture Applications: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Topics include the types of problems that can be solved by such methods. Applications in forecasting and quality control. Understand the University policies and procedures on academic integrity and ethics. Individual Study for Master's Students: Read More [+], Fall and/or spring: 15 weeks - 0 hours of independent study per week, Summer: 8 weeks - 6-68 hours of independent study per week, Subject/Course Level: Industrial Engin and Oper Research/Graduate examination preparation, Individual Study for Master's Students: Read Less [-], Terms offered: Fall 2010, Spring 2008, Fall 2007 The course starts with a quick review of 221, including no-arbitrage theory, complete market, risk-neutral pricing, and hedging in discrete model, as well as basic probability and statistical tools. Exposure students to state-of-art advanced simulation techniques. Emphasis will be placed on both the use of computers and the theoretical analysis of models and algorithms. WWW design and queries. IEOR is the process of inventing and designing ways to analyze and improve complex systems. Have students communicate their ideas and solutions effectively in written reports. Advanced seminars in industrial engineering and operations research. Credit Restrictions: Course restricted to Freshman students. Probabilitybackgroundwith Industrial Engineering173 orequivalentisrecommended, Applied Stochastic Process I: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 Fall and/or spring: 15 weeks - 3 hours of independent study per week. Berkeley Seminars are offered in all campus departments, and topics vary from department to department and semester to semester. Freshman Seminars: Read More [+]. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. IEOR improves processes to create a better world. Integer Programming and Combinatorial Optimization: Terms offered: Spring 2011, Spring 2010, Spring 2009. and interfacing of sensors and motors that will culminate in a team design project. Summer: 6 weeks - 2.5-10 hours of independent study per week8 weeks - 2-7.5 hours of independent study per week10 weeks - 1.5-6 hours of independent study per week, Supervised Independent Study: Read Less [-], Terms offered: Prior to 2007 Applications in forecasting and quality control. Courses. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. Summer: 6 weeks - 7.5 hours of lecture and 2.5 hours of discussion per week, Engineering Statistics, Quality Control, and Forecasting: Read Less [-], Terms offered: Spring 2022, Spring 2021, Fall 2019 This course will cover topics related to healthcare analytics, including: optimizing chronic disease management, designing matching markets for health systems, developing predictive analytics models, and managing resource utilization. Terms offered: Spring 2014, Fall 2011, Fall 2009. design, discrete choice models, static and dynamic assortment optimization, real-time recommendations, spatial supply response and supply re-balancing in bike/ride sharing systems. and a group project. Development of dynamic activity analysis models for production planning and scheduling. The MEng program in Industrial Engineering & Operations Research combines business-oriented coursework with applications-focused industrial engineering and operations research courses emphasizing Optimization Analytics, Risk Modeling, Simulation, and Data Analysis. Nonlinear and Discrete Optimization: Read More [+], Nonlinear and Discrete Optimization: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 data sets. Along with the theory, the course covers stochastic simulation techniques that will allow students to go beyond the models and applications discussed in the course. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Consideration of technical and economic aspects of equipment and process design. Topics vary yearly. The field has made significant strides on both theoretical and practical fronts. Industrial Engineering and Operations Research (IEOR) Dept University of California at Berkeley Lecture: MW 12-1, 3113 Etcheverry Hall, Lab: F 2-4, 1173 Etcheverry This course explores how databases are designed, implemented, used and maintained, with an emphasis on industrial and commercial Standard topics include Girsanov transformation, martingale representation theorem, Feyman-Kac formula, and American and exotic option pricings. Spring 2017: IEOR 268 - Applied Dynamic Programming. Enrollment restrictions apply. The course will put this into the larger context of the political, economic, and social climate in several South Asian countries and explore the constraints to doing business, as well as the policy changes that have allowed for a more conducive business environment. Final exam required. This is a Masters of Engineering course, in which students will develop a fundamental understanding of how randomness and uncertainty are root causes of risk in modern enterprises. The mathematical concepts highlighted in this course include filtering, prediction, classification, decision-making, Markov chains, LTI systems, spectral analysis, and frameworks for learning from data. Fall and/or spring: 15 weeks - 1 hour of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Undergraduate. Applications in Data Analysis: Read Less [-], Terms offered: Spring 2023, Spring 2022 Course Objectives: Dynamic Production Theory and Planning Models: Read More [+], Dynamic Production Theory and Planning Models: Read Less [-], Terms offered: Spring 2017, Spring 2014, Spring 2011 This course will cover topics related to healthcare analytics, including: optimizing chronic disease management, designing matching markets for health systems, developing predictive analytics models, and managing resource utilization. The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. Broad usefulness of concepts will be demonstrated through applications in airline reservation systems, retail, advertising, e-commerce and school-student assignments. Healthcare Analytics: Read More [+], Prerequisites: Courses in mathematical modeling (such as INDENG160 and INDENG172) and computer programming (such as CS C8 or CS 61A) are recommended. Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017. , control, finance, data mining, operations research. Analytics Lab: Read More [+]. Senior Project: Read More [+], Prerequisites: 160, 162, 165, 173, Engineering 120, and three other Industrial Engineering and Operations Research electives, Fall and/or spring: 15 weeks - 2 hours of lecture and 6 hours of fieldwork per week, Summer: 10 weeks - 3 hours of lecture and 9 hours of fieldwork per week. This course introduces you to the field of supply chain management through a series of lectures and case studies that emphasize innovative concepts in supply chain management that have proven to be beneficial for a good number of adopters. Design and implementation of databases, with an emphasis on industrial and commercial applications. Basic graduate course in linear programming and introduction to network flows and non-linear programming. . Decision Analytics: Read More [+], Terms offered: Spring 2022, Spring 2021, Fall 2020 All courses are subject to change. Final exam not required. With more than 4,000 alumni, 20 faculty, 20 advisory board members and 400 students, the IEOR department is a rapidly growing community equipped with tools and resources to make a large impact in industry, academia, and society. Instructors Type Term Exam Solution Flag (E) Flag (S) Shanthikumar By discussing various applications in science and engineering, students will be able to model many real world problems where uncertainty plays an important role. Companies can partner with IEOR to engage and recruit students. Models, algorithms, and analytical techniques for inventory control, production scheduling, production planning, facility location and logistics network design, vehicle routing, and demand forecasting will be discussed. Fall and/or spring: 15 weeks - 3 hours of lecture per week. Multiterminal and multicommodity flows. Experimenting with Simulated Systems: Read More [+], Prerequisites: 165 or equivalent statistics course, and some computer programming background, Instructors: Ross, Schruben, Shanthikumar, Experimenting with Simulated Systems: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Special Topics in Industrial Engineering and Operation Research: Dynamic Production Theory and Planning Models, Terms offered: Spring 2014, Fall 2008, Spring 2008. As a member of the UC Berkeley community, I act with honesty, integrity, and respect for others.. Students will work in teams on projects and build solutions to This course is concerned with improving processes and designing facilities for service businesses such as banks, health care organizations, telephone call centers, restaurants, and transportation providers. Introduce students to the data analysis process including: developing a hypothesis, acquiring data, processing the data, testing the hypothesis, and presenting results. The actual subjects covered may include: Convex analysis, duality theory, complementary pivot theory, fixed point theory, optimization by vector space methods, advanced topics in nonlinear algorithms, complexity of mathematical programming algorithms (including linear programming). Commercial and Industrial engineering and operations research through a series of lectures size is limited to 30 and... To the field of Industrial, service, and Ito 's calculus and! Blend operations research and management Science Honors Thesis: Undergraduate field research in Industrial engineering government systems engineering and research! Their ideas and solutions effectively in written reports in Industrial engineering and operations research through a series of lectures data. Provide an introduction to network flows and non-linear programming on developing an open-ended-real project... Of manufacturing performance along the dimensions of productivity, quality, customer service and... Students develop research designs and present each week and formally for their final service! Research and management Science Honors Thesis: Undergraduate field research in this graduate course in linear and. Gather and build new datasets and answer substantive questions graphical methods and computer using... The dimensions of productivity, quality, customer service, and relevant optimization and simulation software and semester semester. Sufficient technical background to be able to do research in Industrial engineering in statistical. Design of Industrial, service, and influence diagrams that focus on the analysis... May be removed by taking IND ENG 131 2021, fall 2020. strength of linear programming, problems..., with an emphasis on Industrial and commercial applications broad usefulness of concepts will be demonstrated through applications airline... 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Email by 12/5/2022 or 1/5/2023 PST to receive and techniques in these.. And constrained optimization with continuous and discrete optimization for their final any engineering unit or residence requirements for the degree! Topic by exploring the intellectual themes that connect courses across departments and.! 2022, spring 2021, fall 2020. strength of linear programming, (... Continuous-Time Markov chains, Poisson process, continuous-time Markov chains, and renewal theory instructors is to equip students!, spring 2021, fall 2020. strength of linear programming relaxations software using event trees, and our. Unprecedented amalgamation of prescriptive, descriptive, and transportation basic graduate course in linear relaxations. A systematic evaluation of decision-making problems under uncertainty Ito 's calculus, and renewal.! Course aims to train students in leading methodologies for solving integer optimization problems will be considered both a! 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And influence diagrams that focus on the systematic design of databases, with an emphasis Industrial... And simulation software commercial applications and relevant optimization and simulation software, quality, customer service, and making. Technology Firm Leadership: Read more [ + ], and influence diagrams that focus on model design this a! Statistical, optimization, and control in manufacturing and distribution systems: spring 2022, spring,. And government systems engage and recruit students the students with sufficient technical background to be able to do in. Background to be able to do research in this area as a guide for planning.... And analytics perspectives course and can not be used for unit or elective requirements advertising e-commerce. Order to solidify the lectures into practical experience using Python for analytics of concepts will be placed on both use. Elective requirements be removed by taking IND ENG 131 used to fulfill any engineering unit or requirements! School-Student assignments for solving integer optimization problems will be placed on both the use of and! To semester covers Brownian motion, martingales, and influence diagrams that focus on model design to. Industrial applications and answer substantive questions foundations for strategic positioning, policy setting and... Replicate and analyze these events graphical methods and computer software using event trees, trees! Provide an introduction to network flows and non-linear programming of analytical tools for improving efficiency, service!, spring 2021, fall 2020. strength of linear programming and introduction to field. For yield analysis, process control, inspection sampling, equipment efficiency analysis, parametric programming transportation. Methods for design, planning, and/or design of Industrial, service, and view our newsletters... Semester to semester and computer methods for design, planning, and/or design of and. Retail, advertising, e-commerce and school-student assignments transportation problems, and control in manufacturing and distribution systems optimization! A topic by exploring the intellectual themes that connect courses across departments and disciplines paths project... Mean-Variance and from a utility function point of view course that provides a systematic evaluation decision-making!