International Journal of Computational Intelligence Systems

Metaheuristics has attained increasing interest for solving complex real-world problems. This paper studies the principles and the state-of-the-art of metaheuristic methods for engineering optimization. Both the classic and emerging approaches to optimization using metaheuristics are reviewed and analyzed....

Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers...

Since their first appearance in 1997 in the prestigious journal Science, algorithm portfolios have become a popular approach to solve static problems. Nevertheless and despite that success, they have not received much attention in Dynamic Optimization Problems (DOPs). In this work, we aim at showing...

Nan et al. [J.-X. Nan, D.-F. Li and M.-J. Zhang, A lexicographic method for matrix games with payoffs of triangular intuitionistic fuzzy numbers, International Journal of Computational Intelligence Systems 3(3) (2010) 280-289] pointed out that there is no method in the literature to find the solution...

Hesitant fuzzy linguistic term sets (HFLTSs) are very useful for dealing with the situations in which the decision makers hesitate among several linguistic terms to assess an alternative. Some multi-criteria decision-making (MCDM) methods have been developed to deal with HFLTSs. These methods are derived...

The Truck and Trailer Routing Problem consists of a heterogeneous fleet composed of trucks and trailers to serve a set of customers. This problem has been solved previously considering accurate data available. But in a real-world the available knowledge about some data and parameters involves a vague...

Currently, researches on content based image copy detection mainly focus on robust feature extraction. However, most of existing approaches use only a single feature to represent an image for copy detection, which is often insufficient to characterize the image content. Besides, with the exponential...

A two-phase online anomaly detection method based on support vector clustering (SVC) in the presence of non-stationary data is developed in this paper which permits arbitrary-shaped data clusters to be precisely treated. In the first step, offline learning is performed to achieve an appropriate detection...

Motivated by intuitionistic fuzzy sets and fzzy linguistic approach, this article proposes the concept of linguistic intuitionistic fuzzy numbers (LIFNs) where membership and and nonmembership are represented as linguistic terms. In order to process the multiple attribute decision making (MADM) with...

The performance of machine learning algorithms is affected by the imbalanced distribution of data among classes. This issue is crucial in various practical problem domains, for example, in medical diagnosis, network intrusion, fraud detection etc. Most efforts so far are mainly focused upon binary class...

Multibiomitric systems are expected to be more accurate due to the presence of multiple evidences, score level fusion is the most commonly used approach in multibiometrics. In this paper, A novel approach is proposed for the fusion at score level fusion based on False Reject Rate(FRR) and False Accept...

The finite-range voter system, one of stochastic particle systems, is applied to model a financial price process for further description and investigation of fluctuations of Shanghai Composite Index. For different parameter values of the intensity and the range , we investigate the statistical behaviors...