Most complex scheduling problems are combinatorial problems and difficult to solve. That is why, several methods focus on the optimization according to a single criterion such as makespan, workloads of machines, waiting times, etc. In this paper, the Choquet integral is introduced as a general...

This research describes the development of a generic road shape modelling algorithm for simulation of traffic scenes. The proposed algorithm simulates horizontal road alignment, according to the road geometry design standards, in the form of alternating straight section and curve segment...

This is an example of simulation optimization by genetic search. We compare a new technique, genetic search, to two old techniques the pattern search and the response surface method search. The pattern search uses the Hooke–Jeeves algorithm and the response surface method search uses the...

A new technique for efficient training of Hopfield network models using iterative training algorithms is described and demonstrated. This technique is useful for producing stable Hopfield networks, using recently derived results concerning stability conditions for the Hopfield network. Since the...

The multi-criteria predictive control of nonlinear dynamical systems based on Artificial Neural Networks (ANNs) and genetic algorithms (GAs) are considered. The (ANNs) are used to determine process models at each operating level; the control action is provided by minimizing a set of control...

Shaft crack is a very dangerous and frequent fault in rotating machine, but how to locate and configure it is just an inverse problem and not easy to tackle. In this paper, a genetic algorithms based method for shaft crack detection is proposed and described, which formulates the shaft crack...

The Proportional, Integral and Derivative (PID) controllers are widely used in industrial applications. Their popularity comes from their robust performance and also from their functional simplicity.

In the conventional H∞ optimal output feedback control design, the order of the controller is higher than that of the plant. Thus, it is not easy to implement H∞ optimal control in real world engineering problems. This paper tries to bridge the gap between the theoretical H∞ control and...

The paper is concerned about the application of genetic algorithms to the estimation of magnetic hysteresis model parameters, based on the description of magnetization process proposed by Jiles and Atherton. The genetic algorithm approach has been applied to estimation of model parameters for...

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid geno-fuzzy controllers, are introduced and discussed. A new hybrid geno-fuzzy controller based on the algebraic model...