Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

One of sheet severe plastic deformation (SPD) operation, namely constrained groove pressing (CGP), is investigated here in order to specify the optimum values for geometrical variables of this process on pure aluminium sheets. With this regard, two different objective functions, i.e. the uniformity in the effective strain distribution and the necessary force per unit weight of the specimen, are...

in this study, we present a mrcpsp/max (multi-mode resource-constrained project scheduling problem with minimum and maximum time lags) model with minimization tardiness costs and maximization earliness rewards of activities as objective. the proposed model is nearby to real-world problems and has wide applications in various projects. this problem is not available in the literature exactly and ...

Abstract An improved genetic algorithm is proposed to solve the traveling salesman problem. On basis of traditional algorithm, greedy introduced initialize population. The parameters are adjusted adaptively from two aspects evolution algebra and individual fitness function value, which can speed up optimization prevent falling into local optimum. In mutation operation, adaptive used select oper...

Genetic Algorithms have been successfully used for a long time in solving optimization problems in so many diversified fields. Most of the research effort focused on devising a suitable mapping for the problem in hand, or proposing efficient types of operations, finding an optimal set of parameters like crossover and mutation rates, mutation step size and crossover format, or selection methods ...

The objective of this paper is path planning of a 3 DOF planer robot with hydraulic actuator using genetic algorithm. First the geometric and kinematic parameters of robot were established. The equations of motion are derived by Lagrange method. We proposed the model for proportional valve and hydraulic actuators. Then using the genetic algorithm we minimized the hydraulic energy consumption as...

Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. I...

Electric Sheep is a distributed screen-saver that harnesses idle computers into a render farm with the purpose of animating and evolving artificial life-forms known as sheep. The votes of the users form the basis for the fitness function for a genetic algorithm on a space of fractal animations. Users also may design sheep by hand for inclusion in the gene pool. This paper describes the system a...

This paper represents a genetic algorithmic approach to the congestion aware routing problem in Mobile Ad hoc Networks. Variable-length chromosomes (strings) and their genes (parameters) are the sources for encoding the problem. The crossover operation exchanges partial chromosomes (partial routes) and the mutation operation maintains the genetic diversity of the population. The proposed conges...

Unit Commitment (UC) is an important optimization task in the daily operation planning of the utilities. In mathematical terms, UC is a nonlinear optimization problem with a varied set of constraints. In recent years, Genetic Algorithm (GA), as a powerful tool to achieve global optima, has been successfully used for the solution of this complex optimization problem. Nevertheless, since the GA d...