The talk will describe the speaker's experience in designing and implementing optimization algorithms for applications in industry. Discussion will focus on a retail price optimization algorithm that uses stochastic methods to handle uncertainties. The project started with a textbook approach (stochastic optimization with recourse) and evolved into a special purpose solution suited to the business case. The speaker was directly involved in gathering requirements, prototyping a mathematical model and algorithmic approach, investigating issues with real world data, and writing production software for the final implementation. The completed project currently recommends optimal prices on over 10,000 items per day. Dr. Plantenga obtained a PhD from Northwestern University in 1994 studying large-scale nonlinear optimization methods. He has developed optimization software for PeopleSoft/Oracle, Gap Inc, Ziena Optimization, and his current employer, Sandia National Laboratories.