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dc.contributor.authorYoung, Kevin D.en
dc.date.accessioned2014-03-14T20:40:50Zen
dc.date.available2014-03-14T20:40:50Zen
dc.date.issued2006-05-30en
dc.identifier.otheretd-06292006-152309en
dc.identifier.urihttp://hdl.handle.net/10919/33815en
dc.description.abstractThe efficiency of a best management practice (BMP) is defined simply as a measure of how well the practice or series of practices removes targeted pollutants. While this concept is relatively simple, mathematical attempts to quantify BMP efficiency are numerous and complex. Intuitively, the pollutant removal capability of a BMP should be fundamental to the BMP selection process. However, as evidenced by the absence of removal efficiency as an influential criterion in many BMP selection procedures, it is typically not at the forefront of the BMP selection and design process. Additionally, of particular interest to any developer or municipal agency is the financial impact of implementing a BMP. Not only does the implementation cost exist, but there are long-term maintenance costs associated with almost any BMP. Much like pollutant removal efficiency, implementation and maintenance costs seem as though they should be integral considerations in the BMP selection process. However, selection flow charts and matrices employed by many localities neglect these considerations. Among the categories of criteria to consider in selecting a BMP for a particular site or objective are site-specific characteristics; local, state, and federal ordinances; and implementation and long-term maintenance costs. A consideration such as long-term maintenance cost may manifest itself in a very subjective fashion during the selection process. For example, a BMPs cost may be of very limited interest to the reviewing locality, whereas cost may be the dominant selection criterion in the eyes of a developer. By contrast, the pollutant removal efficiency of a BMP may be necessarily prioritized in the selection process because of the required adherence to governing legislation. These are merely two possible criteria influencing selection. As more and more selection criteria are considered, the task of objectively and optimally selecting a BMP becomes increasingly complex. One mathematical approach for optimization in the face of multiple influential criteria is the Analytic Hierarchy Process. â The analytic hierarchy process (AHP) provides the objective mathematics to process the inescapably subjective and personal preferences of an individual or a group in making a decisionâ (Schmoldt, 2001, pg. 15). This paper details the development of two categories of comprehensive BMP selection matrices expressing long-term pollutant removal performance and annual maintenance and operations cost respectively. Additionally, the AHP is applied in multiple scenarios to demonstrate the optimized selection of a single BMP among multiple competing BMP alternatives. Pairwise rankings of competing BMP alternatives are founded on a detailed literature review of the most popular BMPs presently implemented throughout the United States.en
dc.publisherVirginia Techen
dc.relation.haspartkyoung_thesis_revised.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectmulti-criteria decision makingen
dc.subjectBMP maintenance costsen
dc.subjectBMP pollutant removal performanceen
dc.subjectBMP optimizationen
dc.titleApplication of the Analytic Hierarchy Process Optimization Algorithm in Best Management Practice Selectionen
dc.typeThesisen
dc.contributor.departmentCivil Engineeringen
dc.description.degreeMaster of Scienceen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineCivil Engineeringen
dc.contributor.committeechairKibler, David F.en
dc.contributor.committeememberBenham, Brian L.en
dc.contributor.committeememberLoganathan, G. V.en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06292006-152309/en
dc.date.sdate2006-06-29en
dc.date.rdate2006-09-29en
dc.date.adate2006-09-29en


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