Advanced Optimization

taught by Cliff Ragsdale

This course covers a number of advanced topics in optimization.  You will learn: 1) how to formulate and solve network flow problems, 2) how to model and solve optimization problems where some or all of the decision variables must be integers, 3) how to deal with multiple objectives in optimization problems, and 4) techniques for handling optimization problems where the objective function or constraints are not linear functions of the decision variables.

Business analysts with responsibility for specifying, creating, deploying or interpreting quantitative decision models.  Users of optimization software who need to attain a more solid grounding in network optimization, integer programming, non-convex optimization, and multi-criteria optimization.

Advanced Optimization

taught by Cliff Ragsdale

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Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise. Multiple course registrations may be entitled to tuition discounts; read more.

Advanced Optimization

taught by Cliff Ragsdale

Many business problems involve flows through a network - transportation, stages of an industrial process, routing of data.  Students taking this course will learn to specify and implement optimization models that solve network problems (what is the shortest path through a network, what is the least cost way to route material through a network with multiple supply nodes and multiple demand nodes).  Students will also learn how to solve Integer Programming (IP) problems (constrained optimization problems except with one or more decision variable constrained to be an integer: e.g. a firm setting up a wi-fi hotspot could use 2 routers or 3 routers, but not 2.5 routers), and Nonlinear Programming (NLP) problems (where the objective function and constraints are not linear functions of the decision variables.  Students will use spreadsheet-based software to specify and implement models.

SESSION 1: Network Flow Problems

• Characteristics (nodes, arcs, decision variables)
• The objective function & constraints
• Modeling in a spreadsheet

SESSION 2: Integer Linear Programming

• Integrality condition, relaxation
• Rounding
• Stopping rules
• Binary variables
• Implementing/solving the model
• Branch & bound

SESSION 3: Multiple goals

• Soft/hard constraints
• Defining the objective
• Analysis/solution
• Tradeoffs & goal revision
• Multiple objective linear programming (MOLP)
• Minimax

SESSION 4: Nonlinear Programming (NLP)

• Generalized reduced gradient (GRG) overview
• Local vs. Global optimality
• Economic Order Quantity (EOQ) problem
• Location problem
• Evolutionary Optimization

HOMEWORK:

Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Spreadsheet Modeling & Decision Analysis, Sixth edition by Cliff Ragsdale, which can be ordered from the publisher here.  Please be aware that if you order the ebook or rent it, you will also need to purchase the companion resources which will give you the access to the software.  This text is also used in Introduction to Optimization and Risk Simulation and Queueing.

Note:  It is important to get the sixth edition of the text; earlier editions do not contain correct assignments, nor do they provide the needed access to the software.

The course uses Risk Solver Platform for Education software by Frontline systems.  Risk Solver Platform for Education is a new add-in for Excel that performs risk analysis, simulation, optimization, decision trees and other analytical methods.  With the purchase or rental of the book, you will have a course code that will enable you to download and install the software for 140 days.

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