Tag: optimization

Analytics | Programming Tips
Rick Wicklin 0
Quadratic optimization in SAS

At SAS Global Forum last week, I saw a poster that used SAS/IML to optimized a quadratic objective function that arises in financial portfolio management (Xia, Eberhardt, and Kastin, 2017). The authors used the Newton-Raphson optimizer (NLPNRA routine) in SAS/IML to optimize a hypothetical portfolio of assets. The Newton-Raphson algorithm

Advanced Analytics | Analytics | Customer Intelligence
Simon Waller 0
Customer journey optimization: A real-world example

There are so many ways in which a customer’s journey of experiences can be negatively affected, from forms on websites that are unclear or complicated, to inconsistent or non-relevant interactions over many channels. It is important that these interactions are measured and reduced to maximize customer engagement and increase customer

Learn SAS
Rick Wicklin 0
Solve linear programming problems in SAS

In some applications, you need to optimize a linear objective function of many variables, subject to linear constraints. Solving this problem is called linear programming or linear optimization. This article shows two ways to solve linear programming problems in SAS: You can use the OPTMODEL procedure in SAS/OR software or

Rick Wicklin 0
Ten tips before you run an optimization

Optimization is a primary tool of computational statistics. SAS/IML software provides a suite of nonlinear optimizers that makes it easy to find an optimum for a user-defined objective function. You can perform unconstrained optimization, or define linear or nonlinear constraints for constrained optimization. Over the years I have seen many

Advanced Analytics
Emily Lada 0
Simulate to validate

The primary objective of many discrete-event simulation projects is system investigation.  Output data from the simulation model are used to better understand the operation of the system (whether that system is real or theoretical), as well as to conduct various "what-if"-type analyses.   However, I recently worked on another model

Advanced Analytics
Matthew Galati 0
The kidney exchange problem

Suppose someone needs a kidney transplant and a family member is willing to donate one. If the donor and recipient are incompatible (because of blood types, tissue mismatch, and so on), the transplant cannot happen. Now suppose two donor-recipient pairs A and B are in this situation, but donor A

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