More on intuitionistic fuzzy sets
Fuzzy Sets and Systems
Vague sets are intuitionistic fuzzy sets
Fuzzy Sets and Systems
An application of intuitionistic fuzzy sets in medical diagnosis
Fuzzy Sets and Systems
New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions
Pattern Recognition Letters
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Multiattribute decision making models and methods using intuitionistic fuzzy sets
Journal of Computer and System Sciences
Clustering algorithm for intuitionistic fuzzy sets
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A method based on distance measure for interval-valued intuitionistic fuzzy group decision making
Information Sciences: an International Journal
Fuzzy Sets and Systems
Linear programming method for MADM with interval-valued intuitionistic fuzzy sets
Expert Systems with Applications: An International Journal
Bayesian system reliability assessment under the vague environment
Applied Soft Computing
Expert Systems with Applications: An International Journal
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Fuzzy global optimization of complex system reliability
IEEE Transactions on Fuzzy Systems
Multi-objective reliability-redundancy allocation problem using particle swarm optimization
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
An approach for analyzing the reliability of industrial systems using soft-computing based technique
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. This paper presents a methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data. The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions. A conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering linear as well as the nonlinear degree of membership and non-membership functions. The resultants max-min problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Finally, a numerical instance is presented to show the performance of the proposed approach.