Show simple item record

dc.contributorOhio State University. Water Resources Center
dc.contributorUnited States. Office of Water Research and Technology
dc.creatorWhitlatch, Elbert E. (Elbert Earl), 1942-
dc.creatorBhaskar, Nageshwar R.
dc.date.accessioned2009-02-16T16:49:15Z
dc.date.available2009-02-16T16:49:15Z
dc.date.issued1978-12
dc.identifier.otherOCLC #8378018 (print)en
dc.identifier.urihttp://hdl.handle.net/1811/36350
dc.descriptionThis study was supported in part by the Office of Water Research and Technology, U.S. Department of the Interior under Project A-046-0HI0en
dc.description(print) xviii, 263 p. : ill. ; 28 cm.en
dc.descriptionThis report constitutes the doctoral dissertation of Nageshwar R. Bhaskar, Department of Civil Engineering, The Ohio State Universityen
dc.description.abstractOptimal monthly release policies are derived for Hoover Reservoir, Columbus, Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Simulation procedures are used to examine and compare the overall performance of the optimal policies derived by the two methods. Results suggest that for a two-sided quadratic loss function, linear release policies are more optimal. It is also established that the maximum R2 criterion, generally used for model selection, does not exactly produce the best form of a release policy, particularly for nonlinear forms. At target releases at or below the safe yield of the case study reservoir, and for a one-sided quadratic loss function, the standard policy is optimal. At higher targets, nonlinear policies give better performance than the standard policy. Other observations are made concerning the performance of the two optimization approaches in a real case study.en
dc.description.tableofcontentsAbstracts, Keywords -- Project Personnel, Acknowledgements -- List of Tables -- List of Figures -- List of Symbols -- Chapter I: Introduction -- Chapter II: Background and Objectives -- Chapter III: Case-Study Description -- Chapter IV: Case-Study Simulation Analysis -- Chapter V: Optimization Models -- Chapter VI: Chance-Constrained Linear Programming Results -- Chapter VII: Dynamic Programming - Regression Results -- Chapter VIII: Comparison of Optimization Models -- Chapter IX: Summary, Conclusions and Recommendations -- Appendix -- Bibliographyen
dc.language.isoen_USen
dc.publisherOhio State University. Water Resources Centeren
dc.relation.ispartofseriesProject completion report (Ohio State University. Water Resources Center) ; no. 525Xen
dc.subject.lcshReservoirs -- Ohio -- Designen
dc.subject.lcshReservoirs -- Ohio -- Mathematical modelsen
dc.subject.lcshReservoirs -- Ohio -- Managementen
dc.titleApplication of Mathematical Optimization Techniques in Reservoir Design and Management Studiesen
dc.typeBooken


Files in this item

Thumbnail

Items in Knowledge Bank are protected by copyright, with all rights reserved, unless otherwise indicated.

This item appears in the following Collection(s)

Show simple item record