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An aspiration-level interactive model for multiple criteria decision making

dc.contributor.authorLotfi, Vahiden_US
dc.contributor.authorStewart, Theodor J.en_US
dc.contributor.authorZionts, Stanleyen_US
dc.date.accessioned2006-04-10T15:04:11Z
dc.date.available2006-04-10T15:04:11Z
dc.date.issued1992-10en_US
dc.identifier.citationLotfi, Vahid, Stewart, Theodor J., Zionts, Stanley (1992/10)."An aspiration-level interactive model for multiple criteria decision making." Computers &amp; Operations Research 19(7): 671-681. <http://hdl.handle.net/2027.42/29826>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6VC5-48MYG0H-8N/2/e0282564a22aaf52691856a32a6fe9c5en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/29826
dc.description.abstractA simple, eclectic approach for solving discrete alternative multiple criteria decision problems is presented. It is based on the concept of the level of aspiration, and draws on ideas of various researchers. It assumes that the user has a set of alternatives with each alternative having a score on each of a number of objectives or measures of performance. The user determines his levels of aspiration for different objectives. He is then provided with considerable feedback as to the degree of feasibility of each level of aspiration as well as the degree of feasibility with respect to all levels of aspiration as a whole. The closest nondominated solution to the solution specified by the levels of aspiration is provided. The proposed method is easy to use and easy to understand and has been implemented on a personal computer (an IBM PC or compatible with 512K RAM). We describe an experimental application in which 49 students in an MBA program used the method to solve two discrete alternative multiple criteria decision problems.en_US
dc.format.extent1119982 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleAn aspiration-level interactive model for multiple criteria decision makingen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelManagementen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumSchool of Management, The University of Michigan-Flint, Flint, MI 48502, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Mathematical Statistics, University of Cape Town, Cape Town, Republic of South Africa.en_US
dc.contributor.affiliationotherSchool of Management, State University of New York at Buffalo, Buffalo, NY 14260, U.S.A.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/29826/1/0000173.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0305-0548(92)90036-5en_US
dc.identifier.sourceComputers &amp; Operations Researchen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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