Stochastic optimization

Abstract

In this chapter the authors use the methods of optimization to determine how to make good decisions in a stochastic environment and they consider more complex problems. There will be a need to set up a model of what is happening and then to analyze this model. Because of this additional complexity, the focus will switch back to the normative, rather than the descriptive, so they will ask what managers should do, rather than what they will do. For most of the models that they deal with in the chapter it is necessary to carry out an analysis using some computational tool like a spreadsheet. Now they turn to the solution of stochastic optimization problems where the decision maker has to make a string of successive decisions with more information becoming available as time goes on. The aim is to use the Monte Carlo simulation approach in this multistage environment.

Cite this paper

@misc{anderson2013stochastic,
  title = {{Stochastic optimization}},
  author = {Anderson, Edward},
  journal = {Business risk management},
  pages = {198--231},
  year = {2013},
  doi = {10.1002/9781118749388.ch7}
}

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