Graduation date: 1977Facility location studies involve the selection of a preferred\ud course of action from an array of multiattributed alternatives. The\ud factors affecting this selection are defined in both quantifiable and\ud qualifiable terms. The former comprises primarily monetary or operational\ud data, and the latter consists of nonmonetary and environmental\ud parameters; where the term "environmental" encompasses all forms of\ud ecological and societal influences at the proposed locations.\ud Most current techniques developed for multiattributed analysis\ud are strictly mathematical in nature and do not adequately consider the\ud possible effect of subjective variables. Additionally, those procedures\ud which do include techniques for evaluating subjective factors usually\ud employ data in the form of point estimates and make no provisions for\ud the incorporation of probabilistic variability. Recently increasing\ud environmental concern and the high degree of uncertainty which currently\ud exists in construction and operating cost estimates have limited\ud the usefulness of models which are not designed to incorporate such\ud factors.\ud The intent of this paper is to present a detailed procedure to\ud overcome the weaknesses of currently available comparison models. It\ud does so by examining existing models and then developing a methodology\ud based on extensions to the linear additive weighting model.\ud Methods of obtaining relative factor importance are surveyed and\ud weightings are obtained through the utilization of procedures based\ud on the partial paired comparison technique.\ud Significant improvements over conventional comparison models\ud include the facility for evaluating subjective input through the\ud application of utility or impact scaling functions. These functions\ud are the bases for transforming probabilistic site-design performance\ud estimates into relative impact measurements. Aggregate potential\ud environmental impact profiles are next developed for each alternative\ud by Monte Carlo simulation techniques. The resulting qualitative\ud ratings are then combined with qualitative data by means of a relative\ud importance ratio to obtain a single measure of an alternative's desirability.\ud Finally, a method for determining the sensitivity of the\ud selection procedure is illustrated through simulation.\ud The development and discussion of the evaluation procedure is\ud paralleled by an example problem based in part on data collected during\ud siting studies for a large electrical generating facility. Examples\ud of computer input data forms and simulation results are provided\ud along with FORTRAN IV program listings
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