Solution of multiobjective linear programming problems in interval-valued intuitionistic fuzzy environment

The present paper gives a new computational algorithm for the solution of multiobjective linear programming (MOLP) problem in interval-valued intuitionistic fuzzy (IV-IF) environment. In MOLP problem which occurs in agricultural production planning, industrial planning and waste management. The para...

Full description

Saved in:
Bibliographic Details
Published in:Soft computing (Berlin, Germany) Vol. 23; no. 1; pp. 77 - 84
Main Authors: Bharati, S. K., Singh, S. R.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2019
Springer Nature B.V
Subjects:
Agricultural production
Agricultural wastes
Algorithms
Artificial Intelligence
Computational Intelligence
Control
Decision making
Engineering
Fuzzy logic
Fuzzy sets
Linear programming
Mathematical Logic and Foundations
Mechatronics
Methodologies and Application
Multiple objective analysis
Objectives
Optimization techniques
Production planning
Robotics
Simplex method
Uncertainty
Waste management
Pareto optimal solution
Positive deal solution
Interval-valued intuitionistic fuzzy sets
Multiobjective programming
ISSN:1432-7643, 1433-7479
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The present paper gives a new computational algorithm for the solution of multiobjective linear programming (MOLP) problem in interval-valued intuitionistic fuzzy (IV-IF) environment. In MOLP problem which occurs in agricultural production planning, industrial planning and waste management. The parameters involved in real-life MOLP problems are impure, and several pioneer works have been done based on fuzzy or intuitionistic fuzzy sets for its compromise solutions. But many times the degree of membership and non-membership for certain element is not defined in exact numbers, so we observe another important kind of uncertainty. Thus fixed values of membership and non-membership cannot handle such uncertainty involved in real-life MOLP problem. Atanassov and Gargov first identified it and presented concept of IV-IF sets which is characterized by sub-intervals of unit interval. In this paper, we study IV-IF sets and develop a new computational method for the solution of real-life MOLP problems based on IV-IF sets. Further, the developed method has been presented in the form of a computational algorithm and implemented on a production problem, and solutions are compared with other existing methods.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-018-3100-6