Problem domain information extraction is a critical issue in many real-world optimization problems. Increasing the repertoire of techniques available in evolutionary algorithms with this purpose is fundamental for extending the applicability of these algorithms. In this paper we introduce a unifying information mining approach for evolutionary algorithms. Our proposal is based on a division of ...

The paper presents results of computational experiments in which the impact of design representations on the performance of an evolutionary multiobjective structural design processes was investigated. Specifically, two classes of design representations (i.e., direct representations and generative representations) were used to minimize the total weight and the maximum horizontal displacement of ...

Evolutionary multiobjective algorithms have been a successful stochastic tool for engineering global optimum design since the final nineties. In a context of conflicting objectives where improving one of them implies the worsening of others, evolutionary multiobjective algorithms allow to obtain in one single run a set of non-dominated solutions in the sense of Pareto criterion. Among their fie...

Nowadays, dust phenomenon is one of the important challenges in warm and dry areas. Forecasting the phenomenon before its occurrence helps to take precautionary steps to prevent its consequences. Fuzzy expert systems capabilities have been taken into account to assist and cope with the uncertainty associated to complex environments such as dust forecasting problem. This paper presents novel hyb...

the multivariate exponentially weighted moving average (mewma) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. the economic design of mewma control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function ...

one of the most important goals in geomagnetic investigations is detecting local anomaly locations. regional anomaly can be simulating as a trend surface, and local anomalies will be detected by comparison of measured data and simulated trend surface. the problem is trying to find best coefficients of trend surface model using inverse methods based on modern optimization techniques, which are f...

Within the robust design optimization, the statistical variability of the design parameter is considered. The most general method for solving optimization problems under uncertainties is the well established Monte Carlo simulation method. However, the major shortcoming of this approach is its vast need of computational resources (the number of solver runs required), and these cannot be presumed...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

In this paper, we propose a stress-based crossover (SX) operator to solve the checkerboardlike material distributation and disconnected topology that is common for simple genetic algorithm (SGA) to structural topology optimization problems (STOPs). A penalty function is defined to evaluate the fitness of each individual. A number of constrained problems are adopted to experiment the effectivene...