Decision Analysis for Civil and Environmental Engineers

CEE206

Stanford School of Engineering


Decision Analysis for Civil and Environmental Engineers

Description

Current challenges in selecting an appropriate construction or development site, alternate designs, or retrofit strategies based on economic, environmental, and social factors can be best addressed through applications of decision science. Fundamentals of decision theory, including development of decision trees with discrete and continuous random variables, modeling the uncertainty of various components of the decision tree through probability models, expected value decision making, utility theory, expected utility decision making, value of information, and elementary multi-attribute decision making will be covered in the class. Examples will cover many areas of civil and environmental engineering problems. Class final project is based on student’s personal area of interest.

Recommended for CEE MS Programs: Environmental Engineering (ENV), Atmosphere/Energy (A/E), Structural Engineering and Geomechanics (SEG), Sustainable Design & Construction Programs (SDC)

What you will learn

  • What are the components of simple and complex decision-making
  • How to model the uncertainties in potential future outcomes of specific decisions
  • How to develop utility functions
  • The fundamentals of single and multi-utility decision making

Prerequisites

Students taking this course must have taken a course in probability theory, such as CEE203 or equivalent.

 

Topics include

  • Probability modeling of states of nature
  • Basics of decision theory, including decision trees
  • Bayesian analysis
  • Multi-attribute decisions

Notes

This course is only offered annually during Summer Quarter.