001482900 000__ 03562cam\\22005657i\4500
001482900 001__ 1482900
001482900 003__ OCoLC
001482900 005__ 20231128003356.0
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001482900 008__ 231108s2023\\\\sz\a\\\\ob\\\\001\0\eng\d
001482900 019__ $$a1407278433$$a1407315845
001482900 020__ $$a9783031405389$$q(electronic bk.)
001482900 020__ $$a3031405382$$q(electronic bk.)
001482900 020__ $$z9783031405372
001482900 020__ $$z3031405374
001482900 0247_ $$a10.1007/978-3-031-40538-9$$2doi
001482900 035__ $$aSP(OCoLC)1408384191
001482900 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dOCLCO
001482900 0411_ $$aeng$$hpol
001482900 049__ $$aISEA
001482900 050_4 $$aHD30.23
001482900 08204 $$a658.4/03$$223/eng/20231108
001482900 1001_ $$aNermend, Kesra,$$eauthor.$$1https://orcid.org/0000-0002-4309-7434
001482900 24010 $$aMetody wielokryterialnej i wielowymiarowej analizy we wspomaganiu decyzji.$$lEnglish
001482900 24510 $$aMulti-criteria and multi-dimensional analysis in decisions :$$bdecision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /$$cKesra Nermend.
001482900 264_1 $$aCham :$$bSpringer,$$c2023.
001482900 300__ $$a1 online resource (xvi, 354 pages) :$$billustrations.
001482900 336__ $$atext$$btxt$$2rdacontent
001482900 337__ $$acomputer$$bc$$2rdamedia
001482900 338__ $$aonline resource$$bcr$$2rdacarrier
001482900 4901_ $$aVector optimization,$$x1867-898X
001482900 504__ $$aIncludes bibliographical references and index.
001482900 5050_ $$aChapter 1 Introduction -- Chapter 2 Problems of multi-criteria and multidimensionality in decision support -- Part I: Methods of multidimensional comparative analysis -- Chapter 3 Initial data analysis procedure -- Chapter 4 Methods for building aggregate measures -- Part II: Multi-criteria decision support methods -- Chapter 5 Methods based on the outranking relationship -- Chapter 6 Methods based on the utility function -- Chapter 7 Multi-criteria methods using function points -- Chapter 8 Conclusions.
001482900 506__ $$aAccess limited to authorized users.
001482900 520__ $$aA new era is emerging in which a group of quantitative methods featuring characteristics of multidimensional comparative analysis (MCA) and multi-criteria decision-making analysis (MCDA) can be used to automate objective decision-making processes. This book introduces the character of the criteria (desirable, non-desirable, motivating, demotivating, and neutral) to MCDA and MCA methods. It presents the author’s own developed methods, the preference vector method (PVM), for solving multi-criteria problems in decision making; and, vector measure construction method (VMCM), which is dedicated to solving typical problems in the field of multidimensional comparative analysis. All methods are explained step by step with relevant examples, primarily in the fields of economics and management.
001482900 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 8, 2023).
001482900 650_6 $$aDécision multicritère.
001482900 650_0 $$aMultiple criteria decision making.$$0(DLC)sh 89005914
001482900 655_0 $$aElectronic books.
001482900 77608 $$iPrint version: $$z3031405374$$z9783031405372$$w(OCoLC)1389339054
001482900 830_0 $$aVector optimization,$$x1867-898X
001482900 852__ $$bebk
001482900 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-40538-9$$zOnline Access$$91397441.1
001482900 909CO $$ooai:library.usi.edu:1482900$$pGLOBAL_SET
001482900 980__ $$aBIB
001482900 980__ $$aEBOOK
001482900 982__ $$aEbook
001482900 983__ $$aOnline
001482900 994__ $$a92$$bISE