title: Genetic algorithm based hybrid approach to solve fuzzy multi-objective assignment problem using exponential membership function.
abstract: This paper presents a genetic algorithm based hybrid approach for solving a fuzzy multi-objective assignment problem (FMOAP) by using an exponential membership function in which the coefficient of the objective function is described by a triangular possibility distribution. Moreover, in this study, fuzzy judgment was classified usingα-level sets for the decision maker (DM) to simultaneously optimize the optimistic, most likely, and pessimistic scenarios of fuzzy objective functions. To demonstrate the effectiveness of the proposed approach, a numerical example is provided with a data set from a realistic situation. This paper concludes that the developed hybrid approach can manage FMOAP efficiently and effectively with an effective output to enable the DM to take a decision.
authors.affiliation: Department of Applied Mathematics and Humanities, S. V. National Institute of Technology, Surat, 395007 India.
authors.forename: Jayesh M
authors.initials: JM
authors.lastname: Dhodiya
authors.affiliation: Department of Applied Mathematics and Humanities, S. V. National Institute of Technology, Surat, 395007 India.
authors.forename: Anita Ravi
authors.initials: AR
authors.lastname: Tailor
keywords: Fuzzy membership function; Multi-objective assignment problem; Triangular fuzzy number; α-Level sets