Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management
Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to bu...
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Year of Publication: | 2019 |
Language: | English |
Physical Description: | 1 electronic resource (320 p.) |
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520 | |a Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches, in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. Particular attention is devoted to information aggregation operators; 65% of papers dealt with this item. The topics of this Special Issue gained attention in Europe and Asia. A total of 48 authors from seven countries contributed to this Issue. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community. | ||
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653 | |a supplier | ||
653 | |a green supplier | ||
653 | |a trust interval | ||
653 | |a ANFIS | ||
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653 | |a multiple criteria decision-making | ||
653 | |a adaptive neuro-fuzzy inference system (ANFIS) | ||
653 | |a multi-attribute group decision-making | ||
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653 | |a Muirhead mean | ||
653 | |a subcontractor evaluation | ||
653 | |a fuzzy sets | ||
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653 | |a supplier selection | ||
653 | |a unbalanced linguistic set | ||
653 | |a projection model | ||
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653 | |a Dombi operations | ||
653 | |a interaction operational laws | ||
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653 | |a multiple criteria decision making (MCDM) | ||
653 | |a rough ANP | ||
653 | |a MADM | ||
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653 | |a interactive approach | ||
653 | |a weighted aggregation operator | ||
653 | |a logistics | ||
653 | |a rough analytical hierarchical process (AHP) | ||
653 | |a linguistic cubic variable | ||
653 | |a multiobjective optimization | ||
653 | |a aggregation operators | ||
653 | |a bi-directional projection model | ||
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653 | |a prioritized average operator | ||
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653 | |a deterministic finite automata | ||
653 | |a rough weighted aggregated sum product assessment (WASPAS) | ||
653 | |a hesitant probabilistic fuzzy element (HPFE) | ||
653 | |a multiple attribute decision making (MADM). | ||
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700 | 1 | |a Chatterjee, Prasenjit |4 auth | |
700 | 1 | |a Zavadskas, Edmundas Kazimieras |4 auth | |
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