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Optimality criteria for fuzzy-valued fractional multi-objective optimization problem

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Abstract

This paper presents optimality criteria for fuzzy-valued fractional multi-objective optimization problem. There are numerous optimality criteria which have been established for the deterministic fractional multi-objective optimization problems. Very few studies are available on the establishment of optimality criteria for fuzzy-valued multi-objective optimization problem. So, Karush–Kuhn–Tucker optimality criteria for fuzzy-valued fractional multi-objective problem are established by using Lagrange multipliers. First, the original problem is modified using the parametric approach of Dinkelbach into multi-objective non-fractional optimization problem, and then, the optimality conditions are established for the modified problem using the Hukuhara derivative. The established optimality criteria are verified by two numerical examples.

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Authors and Affiliations

  1. Department of Mathematics, Motilal Nehru National Institute of Technology Allahabad, Allahabad, 211004, India

    Deepika Agarwal & Pitam Singh

  2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China

    Xiong Li

  3. Department of Mathematics, C.C.S University, Meerut, India

    Saru Kumari

Authors
  1. Deepika Agarwal
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  2. Pitam Singh
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  3. Xiong Li
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  4. Saru Kumari
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Correspondence to Pitam Singh.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by A. K. Sangaiah, H. Pham, M.-Y. Chen, H. Lu, F. Mercaldo.

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Agarwal, D., Singh, P., Li, X. et al. Optimality criteria for fuzzy-valued fractional multi-objective optimization problem. Soft Comput 23, 9049–9067 (2019). https://doi.org/10.1007/s00500-018-3508-z

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