On optimistic, pessimistic and mixed approaches under different membership functions for fully intuitionistic fuzzy multiobjective nonlinear programming problems

• Published in: Expert systems with applications Vol. 168; p. 114309
• Main Authors: Mahajan, Sumati, Gupta, S.K.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.04.2021; Elsevier BV
• Subjects: Accuracy function; Algorithms; Equivalence; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Intuitionistic fuzzy variables; Membership functions; Multiobjective programming problem; Nonlinear programming; Optimistic; Pessimistic and mixed approaches; Production planning; Transportation problem; Membership functions; Accuracy function; Intuitionistic fuzzy variables; Optimistic; Pessimistic and mixed approaches; Multiobjective programming problem
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2020.114309

The concept of measuring the membership degree along with a non-membership degree, gives rise to the intuitionistic fuzzy set theory. The present study formulates a nonlinear programming problem with multiple objectives, including all the parameters and decision variables as intuitionistic fuzzy numbers. The problem is further investigated subject to optimistic, pessimistic and mixed approaches under linear, exponential and hyperbolic membership functions. The article redefines pessimistic and mixed point of view to be in the true spirit compatible with the definition of an intuitionistic fuzzy number. Accuracy function is used to reduce the problem to an equivalent crisp multiobjective nonlinear programming problem and then optimal compromise solution is obtained under different approaches using various membership/non-membership functions. At appropriate places, theorems have also been proved to establish the equivalence between the original formulation and its crisp counterparts under each approach. Further, practical applications in production planning and transportation problem are illustrated to explain the optimistic, pessimistic and mixed approaches using the proposed algorithm and finally a comparison is also drawn. •A fully intuitionistic fuzzy multiobjective nonlinear problem is formulated.•Optimistic, pessimistic and mixed approaches are proposed.•Linear, exponential and hyperbolic memberships are used to illustrate the concept.•Theorems are proved to show equivalence with the original formulation.•Two practical examples are investigated and a comparison is drawn.