scholarly journals INTEGRATED FUZZY MULTIPLE CRITERIA DECISION MAKING MODEL FOR ARCHITECT SELECTION / INTEGRUOTAS NERAIŠKUSIS DAUGIATIKSLIS SPRENDIMŲ PRIĖMIMO MODELIS ARCHITEKTUI ATRINKTI

2012 ◽  
Vol 17 (4) ◽  
pp. 645-666 ◽  
Author(s):  
Violeta Keršulienė ◽  
Zenonas Turskis

The philosophy of decision making in economics is to assess and select the most preferable solution, implement it and to gain the biggest profit. Important issues such as competitive market, changing technical, political and social environment have a key role in personnel selection. It is the crucial task which determines the company's present and future. Many decisions made cannot be accurately forecast or assessed. Understanding of the multiple criteria method and knowledge to calculate the algorithm of the method allows a decision maker to trust solutions offered by solution support systems to a greater extent. Many individual attributes considered for personnel selection such as organizing ability, creativity, personality, and leadership exhibit vagueness and imprecision. The fuzzy set theory appears as an essential tool to provide a decision framework that incorporates imprecise judgments inherent in the personnel selection process. In this paper, a fuzzy multi-criteria decision making (MCDM) algorithm using the principles of fusion of fuzzy information, additive ratio assessment (ARAS) method with fuzzy numbers (ARAS-F) and step-wise weight assessment ratio analysis (SWARA) technique are integrated. The proposed method is apt to manage information assessed using both linguistic and numerical scales in a decision making problem with a group of information sources. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set. The computational procedure of the proposed framework is illustrated through an architect's selection problem. Santrauka Sprendimų priėmimas ekonomikoje pagrįstas galimų sprendinių įvertinimu, tinkamiausio sprendinio atrinkimu, įgyvendinimu ir didžiausio pelno gavimu. Tokie svarbūs klausimai, kaip užsitikrinti vietą konkurencingoje rinkoje, besikeičianti techninė, politinė ir socialinė aplinka, yra vieni svarbiausių parenkant personalą. Tai labai svarbus uždavinys, tiesiogiai veikiantis bendrovės gyvavimą dabar ir ateityje. Daug sprendinių negali būti tiksliai prognozuojami arba įvertinti. Supratimas apie daugiatikslius metodus ir skaičiavimo metodo algoritmo išmanymas yra prielaidos sprendimų priėmėjui pasitikėti sprendiniais, kuriuos pateikia sprendimų priėmimo sistemos. Yra pateikiama daug atskirų rodiklių personalui atrinkti: organizaciniai gebėjimai, kūrybiškumas, asmeninės ir lyderio savybės. Visi šie rodikliai turi vieną bendrą savybę – jie negali būti tiksliai apirėžti. Tokiems uždaviniams spręsti neraiškiųjų aibių teorija gali pateikti sprendimo būdus, kurie įvertina netikslumus, būdingus personalo atrankos procesui. Šiame straipsnyje neraiškusis daugiatikslis sprendimų priėmimo (MCDM) algoritmas, taikant neraiškiosios informacijos sintezės principus, suminį santykinių dydžių vertinimo (ARAS) metodą, kurio reikšmės aprašomos neraiškiaisiais skaičiais (ARAS-F), ir laipsnišką rodiklių svorio santykinių dydžių analizės (SWARA) metodą, yra integruotas. Siūlomas metodas tinkamas informacijai, vertinamai tiek žodžiais, tiek skaitmenimis, išreiškiamoms skalėms, uždaviniui, kurio informacija surenkama iš grupės informacijos šaltinių, apdoroti. Sujungimo procesas grindžiamas informacija, taikant neraiškiųjų aibių teoriją pagrindinėms žodžiais aprašomoms reikšmėms pakeisti. Siūlomo algoritmo taikymas pavaizduotas sprendžiant architekto parinkimo uždavinį.

Author(s):  
Reza Farzipoor Saen

Supplier selection is a multiple criteria decision making problem that the selection process mainly involves evaluating a number of suppliers according to a set of common criteria for selecting suppliers to meet business needs. Suppliers usually offer volume discounts to encourage the buyers to order more. To select suppliers in the presence of both volume discounts and imprecise data, this chapter proposes an optimization method. A numerical example demonstrates the application of the proposed method.


Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luis Pérez-Domínguez ◽  
Luis Alberto Rodríguez-Picón ◽  
Alejandro Alvarado-Iniesta ◽  
David Luviano Cruz ◽  
Zeshui Xu

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method.


2019 ◽  
Vol 84 ◽  
pp. 49-58 ◽  
Author(s):  
Gabrijela Popovic ◽  
Dragisa Stanujkic ◽  
Miodrag Brzakovic ◽  
Darjan Karabasevic

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