Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A course in fuzzy systems and control
A course in fuzzy systems and control
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
Expert Systems: Design and Development
Expert Systems: Design and Development
Fuzzy Sets, Neural Networks and Soft Computing
Fuzzy Sets, Neural Networks and Soft Computing
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research
INFORMS Journal on Computing
Generating trading rules on the stock markets with genetic programming
Computers and Operations Research
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Comparative analysis of fuzzy ART and ART-2A network clustering performance
IEEE Transactions on Neural Networks
A hybrid intelligent system for multiobjective decision making problems
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
A hybrid system for multiobjective problems - A case study in NP-hard problems
Knowledge-Based Systems
Soft computing in engineering design - A review
Advanced Engineering Informatics
Intelligent fuzzy multi-objective optimization: analysis and new research directions
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
A hybrid intelligent system for multiobjective decision making problems
Computers and Industrial Engineering
Fuzzy Sets and Systems
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This paper studies an application of hybrid systematic design in multiobjective market problems. The target problem is suggested as unstructured real world problem such that the objectives cannot be expressed mathematically and only a set of historical data is utilized. Obviously, traditional methods and even meta-heuristic methods are broken in such cases. Instead, a systematic design using the hybrid of intelligent systems, particularly fuzzy rule base and neural networks can guide the decision maker towards noninferior solutions. The system does not stay in search phase. It also supports the decision maker in selection phase (after the search) to analyze various noninferior points and select the best ones based on the desired goal levels. In addition, numerical examples of real crude oil markets are provided to clarify the accuracy and performance of the developed system.