... algorithm and genetic algorithm (GA) for the optimal design of CDPR with different configurations and masses of end-effectors, respectively. In this section, the mechanical design of the CDPR is introduced. Thus, the kinematic and static models are established. In this paper, the mechanical model...

..., finds the optimal build layout of the parts, and optimizes which parts to consolidate using a genetic algorithm. Results are presented for both minimal production time and minimal production costs, respectively. The production time and cost models consider each step of the manufacturing process...

... a decomposition method that exploits parallel computing, including the determination of an optimal number of subsystems by using a multi-objective optimization formulation and a messy genetic algorithm (GA) modified to handle discrete design variables. In the suggested method, an MDA process is decomposed...

... is implemented successfully using a genetic algorithm. In traditional optimization methods, the multiple objectives are usually transformed into a single objective through mathematical operations. By using a set of weighting coefficients, the multi-objective problems can be expressed in the following...

... exist multiple design solutions. To overcome this problem, a nonlinear approach using a genetic algorithm is used to search for an optimal solution. Finally, a design simulation is performed on an example MRR, and the results show the effectiveness of the proposed design method. A modular...

... as a tool to facilitate the modeling of a product’s upgradability based on its technical characteristics and the reutilization mode. In the optimization phase, a new DFU optimization program is developed by using genetic algorithm techniques. The objective of a product’s DFU optimization is defined so...

.... As a consequence, a suitable multi-objective genetic algorithm (MOGA) has been adopted to reduce vibration effects and to improve the quality of the robot motion with optimal motion profiles. In comparison with the traditional cutting techniques, the proposed one allows, as a result of the optimal motion...

... decision perspective. It is embedded within a genetic algorithm setup to capture the buried, transient, yet inherent data pattern in the design evolution based on the principles of data mining, which are then used to improve the overall performance and effectiveness of surrogate-model-based design...

... characteristic of the product (the intonation) as a multicriteria optimization problem. The design of the inner shape (the bore) of a “new” instrument is finally made by solving the multicriteria optimization problem using genetic algorithms. 19 07 2006 31 05 2007 genetic algorithms hearing...

...., to maximize the availability of real information where assumptions might otherwise be made instead. In this paper, we apply Genetic Algorithms (GAs) to an information flow model to find an optimized sequence for a set of design activities. The optimality of a solution depends on the objective of rearrangement...

... design schemes. Additionally, multiple gradations of structural resolution and a variety of configurations can be generated without increasing the number of design variables. By treating topology synthesis as a discrete optimization problem, the synthesis approach is incorporated in a genetic algorithm...