Recommending Turmeric Variety for Higher Production Using Interval-Valued Fuzzy Soft Set Model and PSO

R. K. Mohanty and B. K. Tripathy
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R. K. Mohanty: Vellore Institute of Technology, India
B. K. Tripathy: Vellore Institute of Technology, India

International Journal of Swarm Intelligence Research (IJSIR), 2021, vol. 12, issue 2, 94-110

Abstract: Soft set is one of the latest mathematical models to handle uncertainty. In a soft set, every element of its parameter set is associated with a subset of the universe of discourse under consideration. In recent times, soft set and its hybrid models have been used extensively to handle decision making problems with uncertain data. It's established that an appropriate hybrid model works better than its basic components. In this article, an algorithm is proposed that is used to recommend the best variety of turmeric having a given set of parameters using Interval valued fuzzy soft sets. Most importantly, the priorities of parameters are taken as fuzzy interval values so that higher uncertainty can be handled properly. Reduction of parameters helps in getting down the complexity of the process under consideration. A metaheuristic optimization technique is a better option to handle these kinds of problems. The authors use particle swarm optimization (PSO) to achieve parameter reduction.

Date: 2021
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