Papers by Keyword: Evolutionary Algorithm

Abstract: Using density function theory (DFT), evolutionary simulations for crystal structure prediction, the most stable compositions of Mg₂Si in the pressure range 0–30 GPa were obtained. The DFT results reproduce experimentally observed pressure-induced phase transitions and predict a new high-pressure structure Cmcm (space group 63).

Abstract: This article introduces evolutionary algorithms and their utilization in mechanical engineering. First part of this work describes evolutionary algorithms and their characteristica. The main body of evolutionary algorithms, the selection methods for parents and the types of reproduction are explained in the next part of this article. Termination conditions are also discussed. Finally, the application of evolutionary algorithms to a problem in mechanical engineering is described. Thereby, the material parameters for a Bodner-Partom model describing visco-elastoplastic material behavior are determined by fitting data from experiments on Aluminum test samples under tension load.

Abstract: Selecting the optimum machine configurations for any product flow line has direct implications on the system performance. In the present paper, an evolutionary algorithm based methodology has been proposed for optimal machine assignment based on a weighted objective function. The objective function includes reliability, cost, production time and operational capability as performance indicators. The methodology demonstrates how several performance parameters can be dealt with, in order to select optimal machine configurations for distinct stages across any serial product flow line. The proposed approach can possibly be employed in handling the RMS performance issues and optimal trade-offs among the various performance parameters.

Abstract: Linear layout is the commonly major preferred arrangement of the flexible manufacturing systems (FMS). The proposed enhanced sheep flock heredity algorithm to solving the unequal area linear layout problem through the real case study problem. The proposed model is to minimize the transportation cost with non-overlapping. Computational results show that proposed sheep flock heredity algorithm (SFHA) can obtain better than particle swarm optimization (PSO) and existing method.