54,479 research outputs found

    "Integrating Optimization and Strategic Conservation to Achieve Higher Efficiencies in Land Protection"

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    Strategic land conservation seeks to select the highest quality lands given limited financial resources. Traditionally conservation officials implement strategic conservation by creating prioritization maps that attempt to identify the lands of highest ecological value or public value from a resource perspective. This paper describes the history of using optimization in strategic conservation and demonstrates how the combination of these approaches can significantly strengthen conservation efforts by making these programs more efficient with public monies.Mathematical Programming, Conservation Optimization, Cost Effectiveness Analysis, Strategic Conservation

    A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

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    The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

    Applying Optimization and the Analytic Hierarchy Process to Enhance Agricultural Preservation Strategies in the State of Delaware

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    Using agricultural preservation priorities derived from an analytical hierarchy process by 23 conservation experts from 18 agencies in the state of Delaware, this research uses weighted benefit measures to evaluate the historical success of Delaware’s agricultural protection fund, which spent nearly 100millioninitsfirstdecade.Thisresearchdemonstrateshowtheseoperationresearchtechniquescanbeusedinconcerttoaddressrelevantconservationquestions.Resultssuggestthatthestatessealedbidofferauction,whichdeterminestheyearlyconservationselections,issuperiortobenefittargetingapproachesfrequentlyemployedbyconservationorganizations,butisinferiortotheoptimizationtechniqueofbinarylinearprogrammingthatcouldhaveprovidedadditionalbenefitstothestate,suchas12,000additionalacresworthanestimated100 million in its first decade. This research demonstrates how these operation research techniques can be used in concert to address relevant conservation questions. Results suggest that the state’s sealed-bid-offer auction, which determines the yearly conservation selections, is superior to benefit-targeting approaches frequently employed by conservation organizations, but is inferior to the optimization technique of binary linear programming that could have provided additional benefits to the state, such as 12,000 additional acres worth an estimated 25 million.conservation optimization, farmland protection, analytic hierarchy process, binary linear programming, Environmental Economics and Policy, Land Economics/Use, Research and Development/Tech Change/Emerging Technologies,

    "Maximizing Conservation and In-Kind Cost Share: Applying Goal Programming to Forest Protection"

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    This research evaluates the potential gains in benefits from using Goal Programming to preserve forestland. Two- and three-dimensional Goal Programming models are developed and applied to data from applicants to the U.S. Forest Service’s Forest Legacy Program, the largest forest protection program in the United States. Results suggest that not only do these model yield substantial increases in benefits, but by being able to account for both environmental benefits and in-kind partner cost share, Goal Programming may be flexible enough to facilitate adoption by program managers needing to account for both ecological and political factors.Goal programming, multi-objective programming, conservation optimization, forest conservation, environmental services, in-kind cost sharing, matching grants
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