This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

A combination of improved genetic algorithm and neural networks is proposed to find the optimal weight of structures subject to multiple natural frequency constraints. The structural optimization is carried out by an evolutionary algorithm employing the discrete design variables. To reduce the computational time of the optimization process, the natural frequencies of structures are evaluated by...

This paper presents three performance indices developed by using the scaling design approach for assisting the selection of optimal topologies for the minimum-weight design of continuum structures subject to stress and displacement constraints. These performance indices are incorporated in the Evolutionary Structural Optimization (ESO) method to monitor the optimization process from which optim...

in this paper, lift and drag coefficients were numerically investigated using numeca software in a set of 4-digit naca airfoils. two metamodels based on the evolved group method of data handling (gmdh) type neural networks were then obtained for modeling both lift coefficient (cl) and drag coefficient (cd) with respect to the geometrical design parameters. after using such obtained polynomial n...

We contribute to the theoretical understanding of evolutionary algorithms and carry out a parameterized analysis of evolutionary algorithms for the Euclidean traveling salesperson problem (Euclidean TSP). We exploit structural properties related to the optimization process of evolutionary algorithms for this problem and use them to bound the runtime of evolutionary algorithms. Our analysis stud...

1 Abstract Multi-objective optimization addresses problems with several design objectives, which are often conflicting, placing different demands on the design variables. In contradiction to traditional optimization methods, which combine all objectives into a single figure of merit, parallel optimization strategies such as evolutionary algorithms allow direct convergence to the Pareto front. T...

1. Abstract In structural sizing optimization problems the aim is to minimize an objective function under certain constraints. The design variables of the optimization problem are generally discrete and belong to certain discrete sets. In the context of the present work the design set is implemented and efficiently treated as a database that contains the required geometric properties for all de...

During the last 20 years, structural optimization has become one of the most important topics of engineering applications. Design optimization of structure has been an interesting area of research in the field of engineering design for its ability to short the design cycle and to enhance product quality. Significant research activity has occurred in the area of structural optimization in the la...

0045-7949/$ see front matter Crown Copyright 2 doi:10.1016/j.compstruc.2010.11.003 ⇑ Corresponding author. Tel.: +82 32 860 7310; fax E-mail addresses: [email protected], jhp@h [email protected] (H.G. Beom), [email protected] (Y. W (S. Lin), [email protected] (B. Liu). This paper proposes an evolutionary accelerated computational level set algorithm for structure topology optimization. It integ...