Design of engineering systems using stochastic decomposition: Water supply planning application

Walid E. Elshorbagy, Diana S. Yakowitz, Kevin E. Lansey

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

To effectively design engineering systems, the future operation of the system which usually involves many uncertainties must be considered. A two-stage stochastic programming formulation can aid in satisfying this requirement The first stage of this formulation represents the design criteria at the present time when a decision must be made. The second stage represents the future operation or the system response to the design where other actions (recourse decisions) are to be made after observing the random input. To solve this type of problem, the Regularized Stochastic Decomposition (RSD) algorithm, which allows the consideration of continuous random variables, was employed and extensions to better handle real engineering problems were investigated. The algorithm is applied to a regional water supply problem that seeks the optimal design capacities of water treatment plants, secondary and tertiary wastewater treatment plants, and recharge facilities while meeting future demands. Results are generated based on different forms of uncertainties for both linear and nonlinear first-stage objective functions. The advantages of using stochastic programming in engineering decision making are evaluated.

Original languageEnglish (US)
Pages (from-to)279-302
Number of pages24
JournalEngineering Optimization
Volume27
Issue number4
DOIs
StatePublished - 1997

Keywords

  • Decomposition
  • Operation
  • Planning
  • Stochastic programming
  • Uncertainty
  • Water supply

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Design of engineering systems using stochastic decomposition: Water supply planning application'. Together they form a unique fingerprint.

Cite this