Uncertain Multi-Criteria Optimization Problems
Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many arti...
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Pamučar, Dragan edt Uncertain Multi-Criteria Optimization Problems Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (86 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems. English Information technology industries bicssc multiple-criteria decision-making underground mines mining methods expert knowledge failure mode and effects analysis solar panel systems step-wise weight assessment ratio analysis grey relational analysis Z-number theory B2C e-commerce factors website MCDM Fuzzy AHP TOPSIS-Grey China IoT platform selection multi criteria decision analysis (MCDA) AHP PROMETHEE-II Industry 4.0 data envelopment analysis conjoint analysis experimental design criteria importance weight restrictions subjective and objective teacher efficiency multi-objective planning reverse supply chain robust optimization uncertainty meta-heuristic algorithm steel making industry fuzzy PIPRECIA fuzzy EDAS railway multi-criteria decision-making transport policy Six Sigma (6σ) DMAIC vehicle fleet optimization text mining Multi-Attribute Decision Making (MADM), criteria selection weighting Prospective MADM Latent Semantic Analysis (LSA) SIMUS decision tree transport plan Laplace’s criterion Hurwitz’s criterion q-rung orthopair fuzzy numbers q-rung orthopair fuzzy prioritized weighted average operator q-rung orthopair fuzzy prioritized weighted geometric operator green supply chain management fuzzy theory sustainable development SCOR model FAHP PROMETHEE II textile and garments industry sustainable supplier selection MCDA efficiency DEA SFA classification dimensionality reduction q-ROFNs Einstein operators prioritized aggregation operators multi-criteria group decision making hazardous materials vehicle route model (VRP) uncertainty theory chance constrained programming model hybrid intelligent algorithm linear Diophantine fuzzy set linear Diophantine fuzzy soft rough set soft rough linear Diophantine fuzzy set upper reduct and lower reduct core set multi-criteria decision making q-Rung orthopair fuzzy sets geometric aggregation operators based on generalized and group-generalized parameters water loss management decision making intuitionistic fuzzy sets the COMET method service quality fuzzy set Jensen–Shannon divergence shapley function TODIM port-hinterland transportation system bi-objective programming intermodal transportation carbon emissions uncertain demand distributionally robust chance constraint Yangtze River Economic Belt multi-criteria decision-analysis MCDA benchmark normalization entropy decision-making methods multi-criteria problems evolutionary algorithms machine learning fuzzy logic uncertain data consistency weights fuzzy preference relation (FPR) hesitant fuzzy preference relation (HFPR) Łukasiewicz consistency normal hesitant fuzzy preference relation (NHFPR) multiple criteria decision-making (MCDM) outsourcing provider DEMATEL CRITIC TOPSIS comparison measure representation disjoint multiplicative preference relation (MPR) group decision-making (GDM) incomplete fuzzy preference relation (IFPR) TL-consistency cubic m-polar fuzzy set Dombi’s operations cubic m-polar fuzzy aggregation operators with P-order (R-order) SIR technique complex networks social networks viral marketing information propagation crisp probability interval probability influence diagrams circuit breakers granular computing interval-valued intuitionistic fuzzy set multiple granulation ordered information system 3-0365-1574-7 3-0365-1573-9 Pamučar, Dragan oth |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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Uncertain Multi-Criteria Optimization Problems |
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uncertain multi-criteria optimization problems |
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MDPI - Multidisciplinary Digital Publishing Institute |
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2021 |
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1 electronic resource (86 p.) |
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3-0365-1574-7 3-0365-1573-9 |
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