Water resources decision making using meta-heuristic optimization methods

Persistent Link:
http://hdl.handle.net/10150/191266
Title:
Water resources decision making using meta-heuristic optimization methods
Author:
Eusuff, Muzaffar M.
Issue Date:
2004
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation work is part of a larger research effort involving soil-aquifer treatment (SAT). The dissertation's focus was to investigate meta-heuristic (global) optimization methods suitable for developing water resources decision support system (DSS), particularly to optimally design and operate groundwater storage and recovery projects. The effort included developing an integrated simulation-optimization management model for complex aquifer recharge/extraction operation considering water quality transformation. The research demonstrated successful integration of three-dimensional hydraulic, water quality, and particle tracking models with shuffled complex evolution (SCE) optimization algorithm. It also included developing the shuffled frog leaping algorithm (SFLA), a meta-heuristic optimization technique for solving discrete/combinatorial problems, and its application to aid decision making in water supply and distribution system optimization issues. SFLA is a memetic, meta-heuristic population-based cooperative search metaphor inspired by natural memetics. SFLA was developed by extending the logic of two existing global optimization techniques for continuous optimization problems. The local search is completed using an extension of the particle swami optimization (PSO) method, and the global exploration is performed by a technique similar to that used in the shuffled complex evolution (SCE) algorithm. SFLA was tested favorably on several literature test functions and engineering problems that present difficulties to many global optimization problems. The effectiveness and suitability of this algorithm has also been demonstrated by applying it to a groundwater model calibration problem and several water distribution system design problems that are considered as benchmark problems in the literature. The comparison of SFLA with other existing global optimization methods, such as genetic algorithms (GA), in terms of the likelihood and efficiency of converging to a global optimal solution, suggests that SFLA can be an effective algorithm for solving discrete/combinatorial optimization problems.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Water resources development -- Decision making -- Statistical methods.; Water quality management.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Civil Engineering and Engineering Mechanics; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Lansey, Kevin E.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleWater resources decision making using meta-heuristic optimization methodsen_US
dc.creatorEusuff, Muzaffar M.en_US
dc.contributor.authorEusuff, Muzaffar M.en_US
dc.date.issued2004en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation work is part of a larger research effort involving soil-aquifer treatment (SAT). The dissertation's focus was to investigate meta-heuristic (global) optimization methods suitable for developing water resources decision support system (DSS), particularly to optimally design and operate groundwater storage and recovery projects. The effort included developing an integrated simulation-optimization management model for complex aquifer recharge/extraction operation considering water quality transformation. The research demonstrated successful integration of three-dimensional hydraulic, water quality, and particle tracking models with shuffled complex evolution (SCE) optimization algorithm. It also included developing the shuffled frog leaping algorithm (SFLA), a meta-heuristic optimization technique for solving discrete/combinatorial problems, and its application to aid decision making in water supply and distribution system optimization issues. SFLA is a memetic, meta-heuristic population-based cooperative search metaphor inspired by natural memetics. SFLA was developed by extending the logic of two existing global optimization techniques for continuous optimization problems. The local search is completed using an extension of the particle swami optimization (PSO) method, and the global exploration is performed by a technique similar to that used in the shuffled complex evolution (SCE) algorithm. SFLA was tested favorably on several literature test functions and engineering problems that present difficulties to many global optimization problems. The effectiveness and suitability of this algorithm has also been demonstrated by applying it to a groundwater model calibration problem and several water distribution system design problems that are considered as benchmark problems in the literature. The comparison of SFLA with other existing global optimization methods, such as genetic algorithms (GA), in terms of the likelihood and efficiency of converging to a global optimal solution, suggests that SFLA can be an effective algorithm for solving discrete/combinatorial optimization problems.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectWater resources development -- Decision making -- Statistical methods.en_US
dc.subjectWater quality management.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineCivil Engineering and Engineering Mechanicsen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairLansey, Kevin E.en_US
dc.contributor.committeememberValdes, Juan B.en_US
dc.contributor.committeememberContractor, Dinshawen_US
dc.contributor.committeememberSorooshiam, Sorooshen_US
dc.contributor.committeememberKundu, Tribikramen_US
dc.identifier.oclc225863991en_US
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