C.
Daganzo, Instructor
Spring semester
3 units; Two 1.5 hr. lectures per week.
Prerequisites: Graduate standing or consent of instructor.
Topics include: characteristics of terminals on a mode-by-mode basis (seaports, railyards, airports, parking lots, etc.); methodologies used to study terminal operations and the management of congestion (chronographs, input-output diagrams, simulation, optimization, queuing); and studies illustrating the use of the methodologies for different modes.
Although the course covers all transportation modes, freight terminals (ports and railyards) receive extra attention; passenger transportation terminals are also examined in other courses. Besides presenting a number of recipes for examining and improving terminal operations, the course also challenges advanced students to think about unsolved problems. Many Ph.D. theses have been motivated by CE 263. Credit for this course can be earned in one of two manners:
1. By Solving Problem sets.
2. By examining an aspect of terminal operations through modeling and
(if necessary) observation. In the past, students have studied: the
performance of baggage handling systems at airports, queuing at ports when
ships follow an underlying schedule, the geometry of airport terminals
to reduce walking, the performance of container storage systems for ports,
the feasibility of mobile lounge airport terminals, etc. The best
projects have traditionally been published as journal articles. (Three,
by Hall, Robust and O'Neil, have won national awards.) The final (professionally
written) report is due at the end of the semester.
CEE 258 LOGISTICS SYSTEMS ANALYSIS
C.
Daganzo, Instructor
Fall semester
3 units; Two 1.5 hr. lectures per week.
Prerequisites: Graduate standing, or consent of instructor.
The course's main objective is to develop an understanding of practical methods for solving difficult logistics and transportation system design problems. The course presents a two-step approach for the planning, design and evaluation of logistics systems. The first step (the most important and the focus of the course) is based on approximations to the real world that replace cumbersome details by concise data summaries, and complex detailed decisions by broader rules that can be described by means of a few decision variables. These rules are then used to guide the design process. Somewhat unconventional, this first step is more an art than a science. In many cases, a more conventional second step can then be used to fine-tune the design and devise the operating rules.
The course should help the student develop: (i) an understanding of practical methods for solving difficult logistics and transportation system design problems, and (ii) the skills necessary to plan, design and evaluate these systems. To help with (i) many problems will be solved in class. Students will also be asked to solve a small subset of these problems on their own, as indicated in the outline. To help with (ii) students will work in groups throughout the semester to plan, design and evaluate the operations and the economic viability of a package delivery carrier for a country of their choice. The students will also choose whether the carrier operates in conjunction with an existing postal network, or independently, and will also choose the main mode for long-haul operations. They will devise a set of efficient operating rules for the local distribution vehicles (e.g. deciding how to load, route and dispatch them) and will also devise the long-haul network and the layout and operation of the terminals.
R. Sengupta, Instructor
Spring semester
3 units; three hours of lecture per week
Prerequisites: Graduate standing or consent of instructor.
Mathematical methods and information technologies for controlling CEE systems. Emphasizes designing component organizations that interact with the world in real-time to control a large system. Methods applied to transportation operations, supply chains, and structures. Management of design complexity by hierarchical specification, systematic use of simulation and verification tools, semantics, polymorphism, information management services, and compilation from high-level design languages.
CEE 298-6 LOGISTICS SYSTEMS SEMINAR
C.
Daganzo, Instructor
Fall semester
This seminar is offered in years when CEE 258 is not offered and may be substituted for it. (Note that the seminar number may vary from year to year.) The seminar should only be considered by students who: (i) have not taken CEE 258 already and (ii) cannot take CEE 258 another year.
While examples will be drawn mainly from freight transport, the methods to be presented in this seminar are also useful in the analysis of many passenger transportation systems. The seminar will emphasize individual study and supervised problem-solving; class meetings will be informal weekly discussions.
Subjects: Transportation/inventory/production cost interrelationships. Design and operation of physical distribution and collection systems. One-to-one, one-to-many, and many-to-many logistics systems, and the role of terminals and transshipments. Relevant analysis methodologies.
Textbook: "Logistics Systems Analysis", 2nd edition, C.F. Daganzo, Springer-Verlag,
1996.
CEE 251 OPERATION OF TRANSPORTATION FACILITIES
M.
Cassidy or C.
Daganzo, Instructor
Fall semester
2 units; Two 1 hr. lectures per week.
Prerequisites: Graduate standing or consent of instructor.
CEE-251 is organized into 6 lecture blocks: basic analysis tools (deterministic and probabilistic), flow analysis of automobile and pedestrian traffic (theory, control and observation), and scheduling concepts. The scheduling portion pertains to the management of vehicle fleets (for both transit and air); the block is also divided into theory, control and observation mini-blocks. Although no textbook is used, course notes are available -- the codes on the course schedule refer to specific portions of the notes. The course requires some knowledge of probability and statistics. Students who must make up for a deficiency in their probability/statistics background can take the course concurrently with either Stat-25 or Stat-134. To this end, probabilistic concepts are not introduced until period 17, when both Stat-25 and Stat-134 have already discussed important subjects. Although not strictly necessary, familiarity with computer spreadsheets is useful. Credit is earned by solving 6 problem sets (see schedule), and taking a final examination.
M. Hansen, S. Madanat, Instructor
Fall semester
3 units; Three hours of lecture per week.
The systems approach and its application to transportation planning and engineering. Prediction of flows and level of service. Production functions and cost minimization. Utility theory and demand modeling. Transportation network analysis and equilibrium assignment. Decision analysis and evaluation of transportation projects.
M.
Hansen or A. Kanafani,
Instructor
Spring semester
3 units; Three hours of lecture per week.
Prerequisites: CEE 252 or consent of instructor.
Application of micro- and macro-economic concepts to transportation
systems. Urban and interegional travel demand analysis. Freight demand.
Project and program evaluation. Social welfare theory. Analysis of social
cost. Investment analysis and pricing theory. Economic impact analysis.
Role of economic analysis in decision making.
B. Ibbs, Instructor
Fall semester
3 units; Three 1 hr. lectures per week.
Prerequisites: CE 167 or equivalent
This course will provide a broad survey of management practices critical to starting and managing a business in the engineering and construction industries. Topics that are covered include the entrepreneurial process; organizing and staffing; establishing and applying production control systems; means of protecting products and services from competitive threat; and financial management.
I. Tommelein, Instructor
Spring Semester
3 units; Three hours of lecture per week
Principles and practices of "lean" production are applied to project delivery in the AEC industry. Case studies illustrate "lean" concepts. Project delivery is viewed holistically with a focus on work structuring and supply chain management. Topics include systems dynamics, uncertainty, and variation; materials management; logistics; e-commerce; building information modeling (BIM); and integrated product and process design. Students use process simulation to assess performance of different system configurations and develop a case study applying concepts on a real project.
IEOR 131 COMPUTER SIMULATION OF INDUSTRIAL ENGINEERING SYSTEMS
Lee Schruben,
Instructor
Spring Semester
Three 1-hour meetings per week.
Introductory course on the design, programming, and statistical analysis of a simulation study. Discussions will include the types of problems that can effectively be solved by such methods. The programming material will also include the theory behind random variable generation for a variety of common types of random variables. Techniques to reduce the variance of the resultant estimator as well as a statistical analysis of the output of the simulation are considered. A final project will be required.
Overview of simulation. Basic discrete-event simulation modeling with some examples. Steps to be followed to build a simulation model. Advantages and disadvantages of using a simulation language. Overview of a simulation software package.
Review of basic probability and statistics. Selecting input probability distributions.
Use of random numbers to generate random variables. Techniques for random variate generation.
Introductory simulation output analysis. Variance reduction techniques.
Experimental design techniques.
IEOR 150 PRODUCTION SYSTEMS ANALYSIS
C.A. Yano or Robert
Leachman , Instructor
Fall Semester
Three hours of lecture per week.
Quantitative models for operational and tactical decision-making in production systems, including production planning, inventory control, forecasting and scheduling.
This course covers quantitative models based on operations research and other analytical techniques for decision-making in manufacturing environments. The focus is on operational and tactical decisions, including production planning, inventory control, scheduling, forecasting and workforce and capacity planning. Other topics include just-in-time systems, and manufacturing resource planning (MRP).
Classroom time is divided between lectures on the models and methodology, and case studies that provide an opportunity to apply the models in complex, real-world scenarios.
Required Textbooks: Production and Operations Analysis, Nahmias, S.,
3rd ed., Irwin, 1997
51
IEOR 151 SERVICE OPERATIONS DESIGN AND ANALYSIS
R. Righter, Instructor
Fall semester
Three hours of lecture per week.
Prerequisites: 161, 162, and a course in statistics.
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. Major topics in the course include design of service processes, layout and location of service facilities, demand forecasting, demand management, employee scheduling, service quality management, and capacity planning.
IEOR 153 LOGISTICS NETWORK DESIGN AND SUPPLY CHAIN MANAGEMENT
P.M. Kaminsky, Instructor
Fall Semester
Three hours of discussion per week.
Prerequisites: IEOR 160, IEOR 162, or senior standing in Manufacturing Engineering.
This course focuses on both quantitative and qualitative issues which arise in the integrated design and management of the entire supply chain. We consider a variety of issues in supply chain management, including distribution network design, centralized versus decentralized network control, variability in the supply chain, strategic partnerships and supply contract design, global supply network design, ecommerce, and product design for logistics, through discussions and cases. Models and solution techniques for strategic issues such as facility location and logistics network design, and operational issues such as inventory control, will also be considered.
IEOR 250 INTRODUCTION TO PRODUCTION PLANNING AND LOGISTICS MODELS
P.M.
Kaminsky, Instructor
Fall Semester
Three hours of lecture per week.
This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. 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.
IEOR 251 FACILITIES DESIGN AND LOGISTICS
P.M. Kaminsky, Instructor
Spring Semester
Three hours of lecture per week.
Prerequisite: IEOR 262A and Stat 134
This course focuses on design and analysis of models and algorithms for facility location, vehicle routing, and facility layout problems. Emphasis will be placed on both the use of computers and the theoretical analysis of models and algorithms.
We will explore quantitative approaches to making facility location, vehicle routing, and facility layout decisions. In particular, we will focus on understanding algorithms for these problems. By the end of the course, you should understand how to apply the approaches and techniques we have discussed to problems we have not specifically considered in class.
IEOR 254 PRODUCTION AND INVENTORY SYSTEMS
C.A. Yano or Robert
Leachman , Instructor
Spring Semester
Three hours of lecture each week.
Prerequisites: IEOR 262A or IEOR 150; IEOR 263A or IEOR 161 recommended
Required Textbook: Course Reader
Mathematical and computer methods for design, planning, scheduling and control in manufacturing and distribution systems.
This course will focus on advanced models to aid in the design, planning
and control of complex production and distribution systems. Topics may
include: lot sizing for multi-stage systems, flexible manufacturing systems
design and control, just-in-time systems, inventory control in distribution
systems. Readings will be from recent journal articles. A small project
is required, which may be of a practical or research nature.
IEOR 261 EXPERIMENTING WITH SIMULATED SYSTEMS
Lee Schruben,
Instructor
Spring Semester
Three hours of lecture each week.
Prerequisites: IEOR IEOR 263A and an upper division statistics course
The course will introduce graduate and upper division undergraduate students to modern methods for simulating discrete event models of complex stochastic systems. About a third of the course will be devoted to system modeling with the remaining two-thirds concentrating on simulation experimental design and analysis.
IEOR 266 NETWORK FLOWS AND GRAPHS
D.S. Hochbaum or I.
Adler, Instructor
Spring Semester
Three hours of lecture per week.
Prerequisites: IEOR 262A (may be taken concurrently)
Required Textbook: Network Flows, Ahuja, Magnanti, Orlin, Prentice Hall,
1993
Survey of solution techniques and problems that have formulations in terms of flows in networks. Max-flow min-cut theorem. Minimum cost flows. Multi-terminal and multi-commodity flows. Relationship with linear programming, integer programming, transportation problems, electrical networks and critical path scheduling.
Properties of flows in networks and fundamental graph properties. The development of efficient algorithms to achieve optimal solutions for problems defined on graphs and network is an important theme in this course. The topics covered include the max-flow min-cut theorem, shortest paths through a network, minimum cost flows and flow with gains, multi-terminal and multi-commodity network flows, transportation problems, matching and independent set problems. Related problems for which no efficient algorithms are known are introduced as well, including the integer multi commodity problem the clique problem, travelling salesperson problem, location problems and more. Applications to critical path scheduling, production scheduling, inventory problems routing problems and communication networks will be addressed.
Coursework includes periodic problem sets, one midterm and a final exam
(both are take-home exams). Network applications will be discussed in class
and participation is highly encouraged.
J.G. Shanthikumar,
Instructor
Spring Semester
Three hours of lecture per week.
The result "L = (lambda)w" and other conservation laws. Elementary queuing models; comparing single-and multiple-server queues. PASTA. Work. Markovian queues; product-form results. Overflow models. Embedded Markov chains. Random walks and the GI/G/1 queue. Work conservation; priorities. Bounds and approximations.
Early exposure to and numerous applications of two important results: (1) L = (lambda)w, the relations between time-average work and average delay and other conservation laws, and (2) Poisson arrivals see time averages (PASTA).
Brief treatment of deterministic queues. Elementary queuing models; Markovian queues and the use of phase-type distributions. Comparing single-and multiple-server queues; one fast with several slow servers, the notion of "plugging up" the server, and pooling. Contrary behavior.
Queuing networks; product-form results. Reversibility and quasi-reversibility. Overflows and retrials; approximation methods including the equivalent random method.
The M/G/1 and GI/M/c queues; embedded Markov chains. Random walks and the GI/G/1 queue; relations between work and delay. Work-in-system and work conservation; applications to priority queues and for obtaining bounds and approximations.
Comparison methods and tail properties of distributions; the GI/G/c queue; bonds and approximations for single- and multiple-server queues. Results for tandem queues.
Prerequisites: IEOR 263A
Two units; Two hours of lecture per week.
Prerequisites: 263A and Statistics 200B, or equivalent.
Statistical design and analysis of discrete event simulation of stochastic
models. Methods of simulating random variables and stochastic processes.
Variance estimation methods including the bootstrap technique. Variance
reduction approaches including control variates, stratified sampling, importance
sampling, conditional expectations, and the use of hazard variables will
be studied.
P.M. Kaminsky, Instructor
Fall Semester
Three hours of lecture per week.
Prerequisites: IEOR 262A and IEOR 263A, or consent of instructor
Advanced course focusing on research in the area of modeling and analysis of logistics systems. Initial topics include analytical techniques such as worst-case and average case analysis. Later topics include the application of these techniques to routing, inventory, and integrated distribution models and algorithms.
Hamid Noori, Instructor
Fall Semester
Three hours of lecture per week.
This course is designed to develop skills and knowledge in understanding the characteristics of agile and responsive supply chain systems required within e-business frameworks whether it is Business-to-Business, Business-to-Consumer, Consumer-to-Consumer, or Consumer-to-Business. The objective is to help students build a solid foundation in electronic commerce, supply chain management, and how the Internet facilitates supply chain activities. The emphasis will be on the basic supply chain infrastructure required in support of electronic commerce, and examination of issues in supply chain strategy and management.
This course is to have the participants develop an: