Power flow control and transmission loss minimization model with TCSC for practical power networks " , in proc. Purnomo, " Fuzzy clustering based on multiobjective optimization problem for decision support of non player character in serious game " ,

Evolving intelligent systems (EISs), particularly, the zero-order ones have demonstrated strong performance on many real-world problems concerning data stream classification while offering high model transparency and interpretability thanks to their prototype-based nature. Zero-order EISs typically learn prototypes by clustering streaming online in a “one pass” manner for greater computation ef...

Every real-life optimization problem with uncertainty and hesitation can not be a single objective, consequently, class of multiobjective linear problems (MOLOP) appears in the literature. Further, experts assign values uncertain parameters, expert’s opinions about parameters are conflicting nature. There concerning methods based on fuzzy sets, or their other versions available literature that ...

Bilevel optimization problems with multivalued objective functions in both levels are first replaced by a problem with a parametric lower level using a convex combination of the lower level objectives. Thus a nonconvex multiobjective bilevel optimization problem arises which is then transformed into a parametric bilevel programming problem. The investigated problem has been considered in the pa...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective problem with competing and non-commensurable objectives....

A method for incorporating fuzzy preferences into evolutionary multiobjective optimization is proposed. After introducing three commonly used models for describing fuzzy preferences, a method to convert fuzzy preferences into realvalued weight intervals is suggested. It is argued that to convert fuzzy preferences into interval-based weights is more consistent with the motivation of using fuzzy ...