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Introduction to Optimization |
This chapter describes how to use SAS/OR software to solve a wide variety of optimization problems. The basic optimization problem is that of minimizing or maximizing an objective function subject to constraints imposed on the variables of that function. The objective function and constraints can be linear or nonlinear; the constraints can be bound constraints, equality or inequality constraints, or integer constraints.
Traditionally, optimization problems are divided into Linear Programming (LP; all functions are linear) and Nonlinear Programming (NLP). Variations of LP problems are assignment problems, network flow problems, and transportation problems. Nonlinear Regression (fitting a nonlinear model to a set of data and the subsequent statistical analysis of the results) is a special NLP problem. Since these applications are so common, SAS/OR software has separate procedures or facilities within procedures for solving each type of these problems. Model data are supplied in a form suited for the particular type of problem. Another benefit is that an optimization algorithm can be specialized for the particular type of problem, reducing solution times. Optimizers can exploit some structure in problems such as imbedded networks, special ordered sets, least squares, and quadratic objective functions.
SAS/OR software has five procedures used for optimization:
SAS/OR procedures use syntax that is similar to other SAS procedures. In particular, all SAS retrieval, data management, reporting and analysis can be used with SAS/OR software. Each optimizer is designed to integrate with the SAS System to simplify model building, maintenance, solution, and report writing. Data for models are supplied to SAS/OR procedures in SAS data sets. These data sets can be saved and easily changed and the problem can be re-solved. Because the models are in SAS data sets, problem data that can represent pieces of a larger model can be concatenated and merged. The SAS/OR procedures output SAS data sets containing the solutions. These can then be used to produce customized reports. This structure allows decision support systems to be constructed using SAS/OR procedures and other tools in the SAS System as building blocks.
The following list suggests application areas where decision support systems have been used. In practice, models often contain elements of several applications listed here.
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