In the paper an approach to automatic drawing of UML diagrams based on Genetic Algorithms is presented. The approach is a development of the ideas proposed in [[4]][[9]]. Our solution is oriented on the domain of UML diagrams, where the main emphasis is put on Class Diagrams and Use Case Diagrams. A set of aesthetic rules is introduced. The rules are used for the assessment of the layout of dia...

This paper presents a genetic algorithm based approach for solving the thermal generation dispatch with emission constraints. New encoding/decoding techniques are developed in the work. The chromosome contains only an encoding of the normalized system incremental cost. Therefore, the total number of bits of chromosome is entirely independent of the number of units. Moreover, the approach can ta...

In this paper is presented a navigation scheme, based on a genetic algorithm, for autonomous robot navigation. Potential fields are used to attract the robot by the goal position and reject it by the obstacles. In the scheme presented here obstacles are automatically detected by simulated sonar sensors. The configuration of the optimum potential field is determined by the genetic algorithm. Int...

This paper presents a training method for radial basis function neural network (RBFNN) based on GA and dynamic optimal learning rate. Genetic algorithm (GA) is applied to search for the optimal centers from input space of the RBF. Dynamic optimal learning rate approach is also appended to the genetic algorithms’ searching procession to obtain a set of weighting factors so that the network actua...

In this paper we present an hybrid approach which integrate Fuzzy C-Means (FCM) algorithms and Genetic Algorithms (GAs) to design an optimal classifier for the specific classification problem. This integration allows automatic generation of an classifier system, with an optimized subset of features, from a database of examples. The generated classifier strongly outperform the classic FCM algori...

A method for solving satisfiability (SAT) instances is presented. It is based on two basic components: An Epistasis Reducer Algorithm (ERA) and a simple Genetic Algorithm (GA). ERA is implemented by a simulated annealing algorithm (SA), which preprocess the original SAT problem by rearranging the variables to satisfy the condition that the most related ones are in closer positions inside the ch...

In this paper, we propose digital image watermarking algorithm in the multiwavelet transform domain. The embedding technique is based on the quantization index modulation technique and this technique does not require the original image in the watermark extraction. We have developed an optimization technique using the genetic algorithm to search for optimal quantization steps to improve the qual...

We studied a logistics network design model composed of plants, warehouses and customers. For designing this integrated model, we had to make two decisions simultaneously; the location of plants and warehouses, and the product distribution from plants to customers through warehouses. We provided a heuristic using the genetic algorithm. The chromosome presents the location of plants and the allo...

The paper deals with the extraction of features for statistical pattern recognition. In particular, the case of recognition with learning is considered. Bayes probability of correct classification is adopted as the extraction criterion. The problem with incomplete probabilistic information is discussed and Bayes-optimal feature extraction procedure is presented in detail. As method of solution ...