Introduction
Stochastic Programming (SP) is a special class of mathematical programming that involves optimization under uncertainty. Such problems occur in various streams of industry, e.g., supply chain management, financial optimization, network optimization, energy sector, etc. The Xpress stochastic programming suite provides a range of tools and functionalities for modeling, solving, and analyzing these problems.
We begin by understanding the basics of SP in Chapter Stochastic Programming (SP) basics, where we study what attributes of SP problems distinguish them from deterministic problems. Chapter Xpress-SP architecture describes the design of the Xpress-SP framework. There we look at various devices embedded in the Xpress-SP suite for an efficient and rapid modeling of SP problems and other tools for solving and analyzing them. Chapter Building stochastic models gives a detailed description of these tools and functionalities required to model and solve an SP problem in this framework. Finally, Chapter Illustrative examples illustrates how stochastic models in various fields can be built using the Xpress-SP suite.
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