An algorithmic approach to group decision making problems under fuzzy and dynamic environment
| Autor: | Mahima Gupta, B. K. Mohanty |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Aggregate (data warehouse) General Engineering 02 engineering and technology computer.software_genre Fuzzy logic Synthetic data Computer Science Applications Group decision-making Set (abstract data type) 020901 industrial engineering & automation Ranking Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining Preference (economics) computer Selection (genetic algorithm) Mathematics |
| Zdroj: | Expert Systems with Applications. 55:118-132 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2016.02.002 |
| Popis: | Our work gives an algorithm for GDM in a fuzzy and dynamic environment.The pair-wise comparison of alternatives is used to obtain ranked list of alternatives.Concept of recentness of members is defined for decision process in dynamic environment.The efficiency of algorithm is tested with many synthetic data sets.The methodology is compared with movie ranking case study discussed in the literature. Our paper introduces a new methodology to solve group decision-making problems under fuzzy and dynamic environment. The methodology takes group members' linguistically defined pair wise preferences of alternatives in different time intervals and aggregates them across the intervals to obtain each member's net preference levels. Each member's net preference levels are again aggregated across the members to obtain the group's preference. Our paper attaches higher importance to the members whose involvement in the decision process is more recent than the members who opined their views in the past. The fuzzy aggregation operator, IOWA (Induced Ordered Weighted Average) is used to aggregate their views in accordance to their importance in the group. The Ranked_List algorithm, introduced in our paper, inputs the aggregated views of the members in pair wise form and produces the set of sequences of ranked list of alternatives representing the group's consensus view as output. The Ranked_List algorithm is validated and analyzed through a series of synthetic data sets and its results are compared with a movie selection case study. The methodology is illustrated with a numerical example. |
| Databáze: | OpenAIRE |
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