Multiple Criteria Decision Making with Fuzzy Sets: MS Excel® and Other Software Solutions PDF
Preview Multiple Criteria Decision Making with Fuzzy Sets: MS Excel® and Other Software Solutions
Multiple Criteria Decision Making Babek Erdebilli Gerhard-Wilhelm Weber Editors Multiple Criteria Decision Making with Fuzzy Sets MS Excel® and Other Software Solutions Multiple Criteria Decision Making SeriesEditor Constantin Zopounidis, School of Production Engineering and Management, TechnicalUniversityofCrete,Chania,Greece This book series focuses on the publication of monographs and edited volumes of wideinterestforresearchersandpractitionersinterestedinthetheoryofmulticriteria analysis and its applications in management and engineering. The book series publishes novel works related to the foundations and the methodological aspects of multicriteria analysis, its applications in different areas in management and engineering, as well as its connections with other quantitative and analytic disci- plines. In recent years, multicriteria analysis has been widely used for decision makingpurposesbyinstitutionsandenterprises.Researchisalsoveryactiveinthe field,withnumerouspublicationsinawiderangeofpublicationoutletsanddifferent domains such as operations management, environmental and energy planning, financeandeconomics,marketing,engineering,andhealthcare. (cid:129) Babek Erdebilli Gerhard-Wilhelm Weber Editors Multiple Criteria Decision Making with Fuzzy Sets ® MS Excel and Other Software Solutions Editors BabekErdebilli Gerhard-WilhelmWeber DepartmentofIndustrialEngineering PolitechnikaPoznańskaWydziałInżynierii AnkaraYıldırımBeyazıtUniversity Zarządzania Ankara,Turkey Poznań,Poland ISSN2366-0023 ISSN2366-0031 (electronic) MultipleCriteriaDecisionMaking ISBN978-3-030-98871-5 ISBN978-3-030-98872-2 (eBook) https://doi.org/10.1007/978-3-030-98872-2 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerland AG2022 Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether thewholeorpartofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseof illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similarordissimilarmethodologynowknownorhereafterdeveloped. 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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface ItgivesmegreatpleasuretoannouncethepublicationofthebookMultipleCriteria Decision-MakingwithFuzzySets.Itfeaturesthirteenchaptersandinterestingpapers writtenbyresearcherswithcompetenceinfuzzysetsandmultiplecriteriadecision- making(MCDM).Ineverydaylife,thereareseveralexamplesofMCDMproblems: in general, clearly considering multiple factors results in more informed and better decisions. MCDM models are typically highly complicated, and it is frequently required to use the decision-maker’s preferences to distinguish between various solutionsandfindtheoptimumcompromise.Makingachoiceisanintegralelement ofdailylife.Makingchoicesisanecessarycomponentofourdailylife.Theprimary issue is that nearly all choice problems involve several, frequently contradictory, factors. There has been a huge amount of research into how to tackle such chal- lenges.Asdiverseasthesechallengesare,theyfallundertwomajorcategories: (cid:129) MultipleAttributeDecision-Making(MADM) (cid:129) MultipleObjectiveDecision-Making(MODM) From apracticalpoint ofview,MADMisconnectedwithissuesthat haveaset numberofpossibilities.TheDecision-Maker(DM)istaskedwiththeresponsibility of selecting/prioritizing/ranking a finite number of alternative courses of action. MODM, on the other hand, is not connected with problems whose solutions are predetermined. The DM’s principal objective is to provide the “most” promising optionpossiblegivenrestrictedresources.TomanageproblemsinvolvingMultiple Attribute Decision-Making and to comprehend uncertainty and the vagueness of humanbeings,MCDMandFuzzyMCDMmathematicalmethods. MCDM is often regarded as a comprehensive decision-making technique that combines both quantitative and qualitative variables into the decision-making pro- cess.Inrecentyears,anumberoffuzzyMCDMalgorithmshavebeenpresentedfor the purpose of selecting the optimal solutions. Fuzzy set theory and MCDM were bothdevelopedintheearly1970s,whichcombinedwiththedevelopmentoffuzzy settheory.Ithasbeenshownthatthetheoryiswell-suitedtodecision-making,which v vi Preface has resulted in the development of a large number of novel techniques for fuzzy multi-criteriadecision-making. ThisbookprovidesanoverviewoffuzzyMCDMcategorytheoryanddiscusses someofitsoldestandmostrecentapplications.Numerousreal-worldexampleswere offered to illustrate the concept of category in fuzzy MCDM and its applications. Despite its success in a variety of knowledge fields, MCDM is still imperfect at combining imprecise, vague, and incomplete data. The flexibility, dynamic, and receptive nature of MCDM enables a plethora of new possibilities for utilizing decision theory. When Bellman and Zadeh, followed by Zimmermann a few years later,addedfuzzysetsintotheequation,theypavedthewayforanewcategoryof decision procedures capable of addressing situations that were previously inacces- sible or unsolvable using normal MCDM techniques. When fuzzy set theory was incorporatedintoMCDMresearch,themethodologiesfollowedasimilarpath.The first category of fuzzy MCDM includes a variety of methods for ranking. This comprisesthedegreeofoptimality,theHammingdistance,thecomparisonfunction, thefuzzymeanandspread,theproportiontotheideal,theleftandrightscores,the centroidindex,theareameasurement,andlinguisticrankingalgorithms.Thesecond category consists of strategiesthat make use of a number of techniques inorder to calculate the relative importance of various characteristics and alternatives. The majority of the methods mentioned in this category were aimed at determining the weightofvariousobjects.Fuzzysimpleadditiveweighingmethods,fuzzyanalytic hierarchy processes, fuzzy conjunctive or disjunctive weighting methods, fuzzy outranking methods, and max-min weighting methods are some of the approaches covered. Fuzzy mathematical programming is the third category, and it is also the onetowhichthemostofcontributionshavebeenmade. Thefollowingarethemaintopicspresentedandanalyzedinthisspecialvolume: Multi-Criteria Group Decision-Making Under Heterogeneous Information, q-rung orthopair fuzzy-based MCDM, integrated intuitionistic Fuzzy MCDM, FuzzyMCDM,interval type-2fuzzy MCDM,Interval-ValuedPythagorean Fuzzy, HesitantFuzzyMCDM,anextensionMCDM,Reflectingbarrierandfuzzydemands and applications to Environment, Health care, economics, Industry, engineering, management,andsocialsciences. The Chapter “Data-Driven Multi-Criteria Group Decision Making Under Het- erogeneous Information” as a result of Nurullah Güleç and Özgür Kabak’s discus- sion of complicated decision-making (GDM) challenges involving various stakeholders, interest in group decision-making methodologies continues to grow. The success of GDM processes is directly tied to the decision-makers’ (DMs) evaluations. When DMs contribute differently due to their knowledge, experience, orconsistencywithoneanother,theyareassignedweightstoreflecttheirvalueinthe finaloutput.Accordingtothem,acumulativebeliefdegree(CBD)strategybasedon beliefstructureandfuzzylinguistictermsisofferedtodealwithsuchheterogeneous informationinstances.Todeterminethefinalranksofthealternatives,theinforma- tion provided in intuitionistic fuzzy numbers, hesitant fuzzy linguistic terms, and hesitantfuzzynumbersisconvertedtobeliefdegrees. Preface vii InChapter“SupplierEvaluationwithQ-RungOrthopairFuzzy-BasedCOPRAS Method”, Adem Pınar highlights the importance of developing long-term business relationships in supply chain management, specifically evaluating and selecting an appropriate supplier. Introduce a new modification of the Complex Proportional Assessment (COPRAS) method based on q-Rung Orthopair Fuzzy Sets that suc- cessfully handle the uncertainty associated with real-world subjective decisions. COPRAS takes into account the influence of maximizing criteria and the total of theweightednormalizedvaluesofminimizingcriteria,whicharebasicallycostand benefitcriteria. InChapter“AnIntegratedIntuitionisticFuzzyMCDMModel:ItsApplicationto RIS”, Babek Erdebilli and Adel Hatami-Marbini demonstrate how to construct a hybrid model using the intuitionistic fuzzy TOPSIS (IFTOPSIS) technique, data envelopment analysis (DEA), and the analytical hierarchy process (AHP). IFTOPSIS is used to handle more difficult issues in which the decision-maker is unsure or hesitant to assign qualitative preference ratings to the objects being evaluated. In this chapter, integration of models that can benefit from both tech- niques’ strengths and flaws is discussed extensively. Using the model provided in this work has various advantages, the most significant of which is the capacity to makeaccurateassessmentsontheperformanceofdecision-makingunits(DMUs). In Chapter “Prioritization of Automotive Dealers According to Environmental Sustainability Criteria Using Fuzzy EDAS Method”, Burcu Elmas, Gülin Feryal Can, and Mamak Ekinci provide an evaluation using the Distance from Average Solution (EDAS) method, one of the MCDMs, in combination with fuzzy logic to establishdealerrankings.Thismethodtakestheaveragesolutionintoaccountwhen determining the optimal alternative. The EDAS technique, which compares the alternatives’ negative and positive distances to the average solution, is useful becauseitmayrankthealternativesusingtwodistinctreferencepoints.Thepurpose of incorporating EDAS with fuzzy logic is to simulate uncertainty in the measure- ment values of many criteria that affect dealers’ environmental sustainability per- formancelevelsandtorelatethisuncertaintytodealers’priorities. In Chapter “Ranking of the Bottled Water Brands Using Interval Type-2 Fuzzy ELECTRE Method”, Mükerrem Bahar Başkir and Pelin Toktaş emphasize the importance of Type-1 fuzzy sets and their primary memberships for handling uncertainty in the traditional ELECTRE. The interval type-2 fuzzy ELECTRE method was used in this study to rate bottled water brands according to five analyticalcriteria.Ithasbeendeterminedthatthemostappropriatebrandalternative outperformstheremainingbrandsintermsofmeetingeachcostcriterion. InChapter“Interval-ValuedPythagoreanFuzzyEntropyWeightMethodandIts ApplicationtoSupplierSelection”,ElifHaktanirandCengizKahramanintroducean EntropyWeightMethod(EWM)forweighingcriteriaviavaluedispersionmeasure- ments.Thegreaterdispersionanddegreeofdifferentiationinthismethodimplythat it contains more information. In MCDM with some degree of uncertainty, humans often prefer linguistic assessments. This uncertainty is addressed in this chapter usinginterval-valuedPythagoreanfuzzy(IVPF)sets.TheIVPFweightedgeometric (IVPFWG)operatorisusedtoaggregatethejudgmentsofseveraldecision-makers. viii Preface InChapter“HospitalPerformanceEvaluationinCOVID-19PandemicbyUsing Hesitant Fuzzy MABAC”, Yavuz Selim Özdemir and Nihan Çağlayan emphasize theneedofevaluatinghospitals’intensivecareunitperformanceduringtheCOVID- 19pandemicusingtheHesitantFuzzyMABAC(Multi-AttributiveBorderApprox- imationAreaComparison)approach.Therearenumeroussetsofcriteriaforevalu- ating hospitals in the literature. The technical competence of the COVID-19 emergency service, patient satisfaction, health personnel sufficiency, and patient follow-upprocedurecriteriawereusedinthischapter. InChapter“AMultipleCriteriaRankingMethodBasedonOutrankingRelations: An Extension for Prospect Theory”, Esra Karasakal, Orhan Karasakal, and Hazel Şentürk Prospect Theory is integrated into a well-known multiple criteria ranking approach, PROMETHEE. PROMETHEE investigates the outranking relations among options based on the preference functions. Prospect Theory examines the options with a difference function based on profits and losses. The preference functions of PROMETHEE are modified to capture the choosing behavior of the decision-maker.ThesuggestedmethodisageneralizationofPROMETHEE. InChapter“DevelopmentofaCuttingInsertSelectionModelUsingtheHesitant FuzzyTOPSIS”,YusufTanselİç,KumruDidemAtalay,andEsraDinlerdeveloped a cutting tool selection model for the turning process based on a hesitant Fuzzy Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS). They categorized several well-known cutting tool inserts into a hesitant valued choice matrixbasedontheuncertaintyassociatedwiththeevaluationofthecriteriavalues. TheythenprocessedtheTOPSISmodel’shesitantstepstowardsolvingthecutting toolselectionproblem. In Chapter “Comparing SMEs According to Industry 4.0 Adaptations for Miti- gating the Bullwhip Effect”, Babek Erdebilli, Emine Nur Nacar, Mete Gündoğan, andSujanPiyaintroduceanIntuitionisticFuzzyTOPSISforsupplychainmanage- mentevaluation.Theterm“Industry4.0”isgainingpopularity.Transparencyacross thesupplychainhasbeendemonstratedtobecritical,ashassuccessfulcooperation betweensuppliers,manufacturers,distributors,wholesalers,retailers,andcustomers. However,conflictsbetweensupplychainenterprisesareunavoidablethroughoutthe flowofinformationfromonestagetothenext,withnegativeconsequencesforthe entirechain. In Chapter “Evaluating Industry 4.0 Barriers by Intuitionistic Fuzzy VIKOR Method”, Ibrahim Yilmaz presents an Intuitionistic fuzzy VIKOR technique for identifying the most and least essential barriers that organizations may encounter duringtheIndustry4.0transitionprocess.Industry4.0isincreasinglydemonstrating its effects today, as technology advancements accelerate. Working and daily life continue to evolve as a result of technological advancements. As a result of the changes, new business lines, job prospects, and opportunities develop. Due to the advancements brought about by Industry 4.0, firms may now reach new levels of efficiency, especially in terms of manufacturing, developing, and distributing their products. In Chapter “An Application of Interval Valued Pythagorean Fuzzy WASPAS Method for Drone Selection to Last Mile Delivery Operations”, Ahmet Aktas, Preface ix Mehmet Kabak an analytic model based on Interval-Valued Pythagorean Fuzzy Weighted Aggregated Sum Product Assessment (IVPF-WASPAS) method is pro- posedtodeterminethemostsuitabledronealternative.Therearenumeroustypesof drones, each with a unique capacity and function. For last mile delivery firms, selecting the best appropriate drone is a strategic decision. The applicability of the suggested methodology is proved in this study through a case study including the evaluationoffouralternativedronesusingfivecriteria.Alternativedronesarelisted inaggregatedperspectivesofrelativeimportance. InChapter“StationaryCharacteristicsforRenewal-RewardProcesswithGener- alized Reflecting Barrier and Fuzzy Demands”, Basak Gever and Tahir Khaniyev describearewardprocesswithbarriersasavaluabletoolthatiscommonlyusedin quantumphysicsandinavariety ofengineering challenges. Some issues ininven- tory theory, in particular, can be modeled using renewal-reward processes with a generalized reflecting barrier. However, in inventory models, for example, when predictingthedistributionofrandomvariablessuchasdemandorinterarrivaltimes, theentiredistributionorpartofitsparametersmaybefuzzyasaresultofimprecise information or subjective evaluations. Thus, when the demands are fuzzy random variables, an inventory model is examined using a renewal-reward process with a generalizedreflectingbarrier. Ankara,Turkey BabekErdebilli Poznań,Poland Gerhard-WilhelmWeber
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