this paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. during recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. however, the nature of these decisions is usually complex and unstructured. in general, many quantitative and qualitative factors, such as quality, price, and fl...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

the dogleg severity is one of the most important parameters in directional drilling. improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and d...

This paper suggests an approach to neural network training through the simultaneous optimization of architectures and weights with a Particle Swarm Optimization (PSO)-based multiobjective algorithm. Most evolutionary computation-based training methods formulate the problem in a single objective manner by taking a weighted sum of the objectives from which a single neural network model is generat...

With ever increasing size and use of social networks, there is a large amount of information which users implicitly or explicitly leave behind on social media. This information can be used to identify their personal traits and preferences. In this work, we have proposed a Particle Swarm Optimization (PSO) based approach for clustering users on Facebook (FB) data to identify similar users. Propo...

The development of mathematical neural networks was based on an analogy with biological neural networks found in nature. Recently there has been a resurgence in research and understanding in self-organizing networks that are based on other metaphors: genetics, immune systems etc. In this paper a new methodology is presented for creating Complex Adaptive Functional Networks (CAFN) that are based...

The problem of coordinating construction vehicles in formations is tackled using the particle swarm optimization algorithm. Coordinated multi-vehicles are anticipated to outperform single vehicles in terms of economy and flexibility. A possible approach is to apply control theoretic methods to vehicle coordination but this may require complicated system models to be employed. The particle swarm...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...