Optimization of water resource system using genetic optimization with both deductive and inductive simulation models

Lindell Ormsbee, Sirinavasa Lingireddy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The optimal control problem associated with many water resource systems may be formulated as a nonlinear optimization problem involving a nonlinear objective function subject to both implicit system (state) constraints and implicit bound constrains. A general solution is proposed that uses a disaggregated or dual level approach in which the system state equations are removed from the control formulation and evaluated externally using mathematical simulation while the resulting optimization formulation is solved using a genetic optimization routine. Potential algorithm performance enhancement may be obtained by replacement of the simulation algorithm with a neural network representation. The resulting network may be trained on-line using real time data or it may be obtained using multiple off-line state predictions obtained from a simulation model. Potential applications of the approach are presented along with a discussion of potential problems.

Original languageEnglish
Title of host publicationWRPMD 1999
Subtitle of host publicationPreparing for the 21st Century
DOIs
StatePublished - 1999
Event29th Annual Water Resources Planning and Management Conference, WRPMD 1999 - Tempe, AZ, United States
Duration: Jun 6 1999Jun 9 1999

Publication series

NameWRPMD 1999: Preparing for the 21st Century

Conference

Conference29th Annual Water Resources Planning and Management Conference, WRPMD 1999
Country/TerritoryUnited States
CityTempe, AZ
Period6/6/996/9/99

ASJC Scopus subject areas

  • Computer Networks and Communications

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