Promethee Methods

Brans, Jean Pierre; Mareschal, Bertrand

doi:10.1007/0-387-23081-5_5

Cited by 509 publications

(222 citation statements)

References 80 publications

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“…For the purposes of this study, we are targeting two QoS attributes as our criteria, namely VM price and application execution time. Various methods are being used by multi-criteria decision making such as weighted sum [18], weighted product [19], VIKOR [17], and PROMETHEE [4] (see [26] for more details). We intend for our decision making support to include such multi-criteria techniques while considering more than two QoS attributes (i.e.…”

Section: Planning Phasementioning

confidence: 99%

Daleel: Simplifying cloud instance selection using machine learning

Samreen

Elkhatib

Rowe

et al. 2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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Decision making in cloud environments is quite challenging due to the diversity in service offerings and pricing models, especially considering that the cloud market is an incredibly fast moving one. In addition, there are no hard and fast rules; each customer has a specific set of constraints (e.g. budget) and application requirements (e.g. minimum computational resources). Machine learning can help address some of the complicated decisions by carrying out customer-specific analytics to determine the most suitable instance type(s) and the most opportune time for starting or migrating instances. We employ machine learning techniques to develop an adaptive deployment policy, providing an optimal match between the customer demands and the available cloud service offerings. We provide an experimental study based on extensive set of job executions over a major public cloud infrastructure.

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Section: Planning Phasementioning

confidence: 99%

Daleel: Simplifying cloud instance selection using machine learning

Samreen

Elkhatib

Rowe

et al. 2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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“…Metoda može pružiti rezultate kao potpuno unaprijed predodređene, djelomično unaprijed predodređene ili sofisticirane kao kombinaciju prethodno navedenog (Brans, Mareschal, 2005). Sukladno tome, postoji šest verzija te metode pri čemu I predstavlja djelomično rangiranje, II potpuno rangiranje, III rangiranje bazirano na intervalima, IV kontinuirani slučaj, V rangiranje koje uključuje ograničenja, dok VI verzija pokušava predstaviti prikaz ljudskog mozga.…”

Section: Metodologijaunclassified

“…Osim navedenog, u ovom koraku je potrebno usporediti alternative u parovima za svaki kriterij (Goumas, Lygerou, 2000). Nakon toga se konstruira sljedeća funkcija (Brans, Mareschal, 2005). Takva preferencija može poprimiti vrijednost na skali od 0 do 1 što se može vidjeti iz sljedećih relacija: (Tomić et al, 2011).…”

Section: Metodologijaunclassified

Primjena AHP i PROMETHEE metode na problem diverzifikacije

Klanac

Perkov

Krajnović

2017

oec

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U današnjem okruženju, prepunom konkurencije i promjena, poduzeća moraju znatno vrijeme posvetiti odabiru odgovarajuće poslovne strategije. Jedna od takvih strategija je i diverzifikacija koja postaje atraktivna kada poduzeću ponestane mogućnosti za povećanje profitabilnosti u osnovnoj djelatnosti. Glavni problem koji se pritom javlja je odlučiti u koju industriju je najbolje diverzificirati. Kako bi se odabrala industrija, konačan broj alternativa treba biti rangiran s obzirom na nekoliko ponekad proturječnih kriterija. Stoga donositelj odluke treba razviti model odlučivanja za odabir najbolje industrije. Iz toga proizlazi i glavna svrha ovog rada, a to je kreiranje modela odlučivanja o diverzifikaciji primjenom dviju metoda višekriterijskog odlučivanja (AHP i PROMETHEE). U radu su uspoređeni rezultati primjene navedenih dviju metoda za odabir jedne od pet industrija temeljem tri kriterija te su objašnjene njihove sličnosti i razlike te prednosti i nedostatci prilikom korištenja u ovakvom problemu odlučivanja.

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“…In order to build the appropriate multi-criteria outranking method, some requisites have to be considered, as explained in the following (Brans and Mareschal, 2005):…”

Section: -4mentioning

confidence: 99%

“…The preference function can be defined in various ways (Brans and Mareschal, 2005). In this work, the v-shape function is used for all criteria, which can be defined as:…”

Section: Aip Advances 5 057123 (2015)mentioning

confidence: 99%

A multi-criteria decision aid methodology to design electric vehicles public charging networks

et al. 2015

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This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city’s urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE’s characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

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Promethee Methods

Cited by 509 publications

References 80 publications

Daleel: Simplifying cloud instance selection using machine learning

Daleel: Simplifying cloud instance selection using machine learning

Primjena AHP i PROMETHEE metode na problem diverzifikacije

A multi-criteria decision aid methodology to design electric vehicles public charging networks

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