Tuesday, 18 September 2012

Advanced Optimization

Optimization methods such as network modeling and integer programming are among the most engaging analytics techniques - almost magical in the way they deliver cost savings (or revenue boosts) in problems that feature both transparency and complexity.  Our online course "Advanced Optimization" covers:

- Network Flow Problems
- Integer Programming
- Problems with Multiple Goals
- Nonlinear Programming

Learn in online course "Advanced Optimization" taught by Dr. Cliff Ragsdale at Statistics.com. For more details please visit at http://www.statistics.com/optimization-advanced/.

Aim of Course:
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.  Students will use spreadsheet-based software to specify and implement models.

Who Should Take This Course:
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.

Course Program:

Course outline: The course is structured as follows
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

The instructor, Dr. Cliff T. Ragsdale, is Bank of America Professor of Business Information Technology at Virginia Tech, and author of the #1 optimization text "Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Management Science," now in its sixth edition. Dr. Ragsdale has served as a financial, statistical and information systems consultant for General Mills and the public accounting firm of Deloitte and Touche.

Software: Risk Solver Platform for Education, the Excel add-in from Frontline systems that performs risk analysis, simulation, optimization, decision trees and more.  With the purchase or rental of the course text, you will have a course code that will enable you to download and install the software for 140 days.

You will be able to ask questions and exchange comments with Dr. Cliff T. Ragsdale via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Call: 020 66009116


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