Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
On choosing rationally when preferences are fuzzy
Fuzzy Sets and Systems
Introduction to algorithms
Boolean programming problems with fuzzy constraints
Fuzzy Sets and Systems
Fuzzy Boolean programming problems with fuzzy costs: a general study
Fuzzy Sets and Systems - Special issue on fuzzy optimization
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Acyclic fuzzy preferences and the Orlovsky choice function: a note
Fuzzy Sets and Systems
A general approach to solving a wide class of fuzzy optimization problems
Fuzzy Sets and Systems
VSOP fuzzy numbers and their fuzzy ordering
Fuzzy Sets and Systems
A new approach for ranking fuzzy numbers by distance method
Fuzzy Sets and Systems
Reasonable properties for the ordering of fuzzy quantities (I)
Fuzzy Sets and Systems
Reasonable properties for the ordering of fuzzy quantities (II)
Fuzzy Sets and Systems
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Operations Research and Artificial Intelligence: The Integration of Problem-Solving Strategies
Operations Research and Artificial Intelligence: The Integration of Problem-Solving Strategies
Discrete Optimization Algorithms with Pascal Programs
Discrete Optimization Algorithms with Pascal Programs
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Paper: Rating and ranking of multiple-aspect alternatives using fuzzy sets
Automatica (Journal of IFAC)
A method for ranking fuzzy numbers and its application to decision-making
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
Synthetic realization approach to fuzzy global optimization via gamma algorithm
Mathematical and Computer Modelling: An International Journal
When the greedy algorithm fails
Discrete Optimization
Ranking function-based solutions of fully fuzzified minimal cost flow problem
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Average misbelief criterion in the minimal fuzzy covering problem
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
Research on two different mathematical theories on control
Journal of Computational and Applied Mathematics
Computers and Industrial Engineering
Information Sciences: an International Journal
WSEAS Transactions on Information Science and Applications
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Fuzzy covering problem based on the expert valuations
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
QoS-based cooperative algorithm for integral multi-commodity flow problem
Computer Communications
Multicriteria decision making for reactive power compensation in distribution systems
ECC'11 Proceedings of the 5th European conference on European computing conference
A dynamic consensus scheme based on a nonreciprocal fuzzy preference relation modeling
Information Sciences: an International Journal
A Hopfield neural network applied to the fuzzy maximum cut problem under credibility measure
Information Sciences: an International Journal
Linguistic multi-criteria decision making for energy and environmental corporate policy
Information Sciences: an International Journal
Hi-index | 0.07 |
An approach to solving optimization problems with fuzzy coefficients in objective functions and constraints is described. It consists in formulating and solving one and the same problem within the framework of mutually related models with constructing equivalent analogs with fuzzy coefficients in objective functions alone. It enables one to maximally cut off dominated alternatives ''from below'' as well as ''from above''. Since the approach is applied within the context of fuzzy discrete optimization problems, several modified algorithms of discrete optimization are discussed. These algorithms are associated with the method of normalized functions, are based on a combination of formal and heuristic procedures, and allow one to obtain quasi-optimal solutions after a small number of steps, thus overcoming the computational complexity posed the NP-completeness of discrete optimization problems. The subsequent contraction of the decision uncertainty regions is associated with reduction of the problem to multiobjective decision making in a fuzzy environment with using techniques based on fuzzy preference relations. The techniques are also directly applicable to situations in which the decision maker is required to choose alternatives from a set of explicitly available alternatives. The results of the paper are of a universal character and can be applied to the design and control of systems and processes of different purposes as well as the enhancement of corresponding CAD/CAM systems and intelligent decision making systems. The results of the paper are already being used to solve problems of power engineering.