This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization Based on Gaussian Process Models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These relations minimize the possibility of wrongly performed comparisons of solutions due to inaccurate s...

In this participation are discussed principles of bioinformatics, datamining, evolutionary computing and its mutual intersection. Datamining by means of selected evolutionary techniques are discussed with attention on protein structure, segmentation and state of art on the field of evolutionary algorithms use. Basic principles and terminology of evolutionary algorithms, as well as two evolution...

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in this paper, we study the existence of generalized solutions for the infinite dimensional nonlinear stochastic differential inclusions $dx(t) in f(t,x(t))dt +g(t,x(t))dw_t$ in which the multifunction $f$ is semimonotone and hemicontinuous and the operator-valued multifunction $g$ satisfies a lipschitz condition. we define the it^{o} stochastic integral of operator set-valued stochastic pr...

This paper presents the method of selecting an optimum design of turboalternator using Multi-objective Differential Evolution (MODE) algorithms. In this paper a theoretical problem of turbo-alternator design is considered. In recent years, Genetic Algorithms have been recognized as potent tool in design optimization of electrical machinery. Initially the complete design of turbo-alternator is w...

The article considers the task of fuzzy clustering in a multi-objective optimization (MO) framework. It compares the relative performance of four recently developed multi-objective variants of Differential Evolution (DE) on over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from each algorit...

Keywords: Scheduling Flexible job shop Differential evolution Local search Neighborhood structure Makespan a b s t r a c t This paper proposes hybrid differential evolution (HDE) algorithms for solving the flexible job shop scheduling problem (FJSP) with the criterion to minimize the makespan. Firstly, a novel conversion mechanism is developed to make the differential evolution (DE) algorithm t...

The fast convergence of particle swarm algorithms can become a downside in multi-objective optimization problems when there are many local optimal fronts. In such a situation a multi-objective particle swarm algorithm may get stuck to a local Pareto optimal front. In this paper we propose a new approach in selecting leaders for the particles to follow, which in-turn will guide the algorithm tow...

Motion estimation is one of the major problems in developing video coding applications. Among all motion estimation approaches, Block matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM approach assumes that the movement of pixels within a defined region of the current frame (Macro-Block, MB) can be...