Optimization in an interval-valued fuzzy environment

Ju, Hongmei; Li, Nianwei

doi:10.1109/car.2010.5456896

Cited by 2 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further, FPT has been widely studied and various modifications and generalizations have presented. One of them is the concept of interval-valued fuzzy programming technique (IV FPT), has been extended by Hongmei and Nianwei (2010), furthermore, Shih et al (2008) presented a method to find optimal solution of multiobjective programming in interval-valued fuzzy environment where multiobjective programming converted into an interval-valued fuzzy programming using intervalvalued fuzzy membership functions for each crisp inequalities.…”

Section: Literature Reviewmentioning

confidence: 99%

Hesitant intuitionistic fuzzy algorithm for multiobjective optimization problem

Bharati¹

2022

Oper Res Int J

View full text Add to dashboard Cite

Every real-life optimization problem with uncertainty and hesitation can not be with a single objective, and consequently, a class of multiobjective linear optimization problems (MOLOP) appears in the literature. Further, the experts assign values of uncertain parameters, and the expert’s opinions about the parameters are conflicting in nature. There are concerning methods based on fuzzy sets, or their other versions are available in the literature that only covers partial uncertainty and hesitation, but the hesitant intuitionistic fuzzy sets provides a collective understanding of the real-life MOLOP under uncertainty and hesitation, and it also reflects better practical aspects of decision-making of MOLOP. In this context, the paper defines the hesitant fuzzy membership function and nonmembership function to tackle the uncertainty and hesitation of the parameters. Here, a new solution called hesitant intuitionistic fuzzy Pareto optimal solution is defined, and some theorems are stated and proved. For the decision-making of MOLOP, we develop an iterative method, and an illustrative example shows the superiority of the proposed method. And lastly, the calculated results are compared with some popular methods.

show abstract

Section: Literature Reviewmentioning

confidence: 99%