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1 - 8 of 8 results for: OIT

OIT 245: Optimization and Simulation Modeling

This course provides basic skills in quantitative modeling. The objective is to familiarize students with the main steps in an analytical approach to business decision making: constructing an abstract model for a relevant business problem, formulating it in a spreadsheet environment such as Microsoft Excel, and using the tools of optimization, Monte Carlo simulation and sensitivity analysis to generate and interpret recommendations. The class will be taught in a lab style, with short in-class exercises done in small teams, focusing on a variety of applications drawn from online advertising, healthcare, finance, supply chain management, revenue and yield optimization.
Units: 3 | Grading: GSB Letter Graded

OIT 247: Optimization and Simulation Modeling - Accelerated

The course is aimed at students who already have a background or demonstrated aptitude for quantitative analysis, and thus are comfortable with a more rapid coverage of the topics, in more depth and breadth, than in OIT 245.
Units: 3 | Grading: GSB Letter Graded

OIT 248: The Art and Science of Optimization Modeling in Practice

This is the Advanced Applications option in the menu of courses that satisfy the Management Perspectives requirement in Optimization and Simulation Modeling (OSM). The course is tailored to students who already have command of basic optimization and modeling techniques, or who have a quantitative background that will allow them to catch up quickly. Some basic programming will be required, so experience with at least one programming language is recommended. The course will focus on using optimization techniques in practice. We will start by discussing different types of optimization models, including linear, integer, and quadratic optimization models. We will then discuss modeling techniques to make these models more realistic, such as multi-objective approaches and using regression models within optimization formulations. Lastly, we will cover tips and tricks for solving large models in practice, such as setting solving limits and heuristics.
Units: 3 | Grading: GSB Letter Graded
Instructors: O'Hair, A. (PI)

OIT 691: PhD Directed Reading (ACCT 691, FINANCE 691, GSBGEN 691, HRMGT 691, MGTECON 691, MKTG 691, OB 691, POLECON 691, STRAMGT 691)

This course is offered for students requiring specialized training in an area not covered by existing courses. To register, a student must obtain permission from the faculty member who is willing to supervise the reading.
Units: 1-15 | Repeatable for credit | Grading: GSB Pass/Fail

OIT 692: PhD Dissertation Research (ACCT 692, FINANCE 692, GSBGEN 692, HRMGT 692, MGTECON 692, MKTG 692, OB 692, POLECON 692, STRAMGT 692)

This course is elected as soon as a student is ready to begin research for the dissertation, usually shortly after admission to candidacy. To register, a student must obtain permission from the faculty member who is willing to supervise the research.
Units: 1-15 | Repeatable for credit | Grading: GSB Pass/Fail

OIT 698: Doctoral Practicum in Teaching

Doctoral Practicum in Teaching
Units: 1 | Repeatable for credit | Grading: GSB Letter Graded

OIT 699: Doctoral Practicum in Research

Doctoral Practicum in Research
Units: 1 | Repeatable for credit | Grading: GSB Letter Graded

OIT 802: TGR Dissertation (ACCT 802, FINANCE 802, GSBGEN 802, HRMGT 802, MGTECON 802, MKTG 802, OB 802, POLECON 802, STRAMGT 802)

Units: 0 | Repeatable for credit | Grading: GSB Pass/Fail
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