Group decision making with a fuzzy linguistic majority
Fuzzy Sets and Systems
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Optimization by simulated evolution with applications to standard cell placement
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Stochastic evolution: a fast effective heuristic for some generic layout problems
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Group decision making and consensus under fuzzy preferences and fuzzy majority
Fuzzy Sets and Systems - Special issue dedicated to Professor Claude Ponsard
Second order structures in multi-criteria decision making
International Journal of Man-Machine Studies
Topological design of local-area networks using genetic algorithms
IEEE/ACM Transactions on Networking (TON)
Experiments with simulated annealing
DAC '85 Proceedings of the 22nd ACM/IEEE Design Automation Conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Fuzzy group decision-making for facility location selection
Information Sciences—Informatics and Computer Science: An International Journal
Multiobjective VLSI cell placement using distributed genetic algorithm
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
A fuzzy evolutionary approach with Taguchi parameter setting for the set covering problem
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
A parallel tabu search algorithm for optimizing multiobjective VLSI placement
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Preferences and their application in evolutionary multiobjectiveoptimization
IEEE Transactions on Evolutionary Computation
Linguistic labels for expressing fuzzy preference relations infuzzy group decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A linguistic modeling of consensus in group decision making basedon OWA operators
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Application of fuzzy logic in computer-aided VLSI design
IEEE Transactions on Fuzzy Systems
Combinatorial optimization by stochastic evolution
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
ESp: Placement by simulated evolution
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Topological design of interconnected LAN/MAN networks
IEEE Journal on Selected Areas in Communications
Fuzzy quantifiers in sensitivity analysis of OWA operator
Computers and Industrial Engineering
Information Sciences: an International Journal
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
A genetic algorithm with the heuristic procedure to solve the multi-line layout problem
Computers and Industrial Engineering
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Topology design of distributed local area networks can be classified as a hard combinatorial optimization problem. The problem has several conflicting objectives, such as cost, reliability, network delay, and number of hops between source and destination. These objectives can conveniently be expressed in linguistic terms - a key component of fuzzy logic. This paper presents an approach based on fuzzy logic that combines the conflicting objectives into a single optimization function. A new fuzzy operator, namely, the unified AND-OR (UAO) operator is also proposed, and a decision-making approach based on fuzzy rules and preference rules is introduced. The UAO operator is empirically compared with the well-known ordered weighted averaging (OWA) operator through application to an evolutionary algorithm. Results show that the UAO operator exhibits comparatively better performance than the OWA operator.