It has become more and more important and difficult to minimize makespan in the global competitive markets. The purpose of this paper is to develop a decision support system to assist managers in making decisions for minimal makespan. There are too many and complex factors for senior managers to make suitable decisions. By traditional methods to allocate orders for minimum makespan, it often ma...

This contribution gives an overview about new procedures for the parameter identification for the material characterisation of rubber blends. They are based on a Newton-Raphson procedure and a genetic algorithm. As basis serves an experimental investigation of the viscous properties of rubber blends by means of a capillary-viscometer. Because of simultaneous consideration of wall slippage, temp...

A functional equivalence of feed-forward networks has been proposed to reduce the search space of learning algorithms. A novel genetic learning algorithm for RBF networks and perceptrons with one hidden layer that makes use of this theoretical property is proposed. Experimental results show that our procedure outperforms the standard genetic learning. Key-Words: Feedforward neural networks, gen...

Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...

In this paper an extensive empirical analysis of recently introduced Particle Swarm Optimization algorithm with Convergence Related parameters (CR-PSO) is presented. The algorithm is tested on extended set of benchmarks and the results are compared to the PSO with time-varying acceleration coefficients (TVAC-PSO) and the standard genetic algorithm (GA). Key-Words: Global Optimization, Particle ...

The paper presents aspects regarding genetic algorithms, their use in data mining and especially about their use in the discovery of classification rules. A synthetic presentation of the fitness functions of the genetic algorithms used for mining the classification rules is performed. A genetic algorithm with a new fitness function for mining the classification rules is suggested. The proposed ...

This paper presents a method of searching for the shortest route via the most designated points with the length not exceeding the preset upper bound. The proposed algorithm can obtain the quasi-optimum route efficiently and its effectiveness is verified by applying the algorithm to the actual map data. key words: routing, genetic algorithm, designated points, upper bound constraint, building bl...

The aim of this study is to present a hybrid algorithm based on two meta-heuristic algorithms named Vibration Damping Optimization (VDO) algorithm and Genetic Algorithm (GA) for solving the stochastic capacitated location-allocation problem. For solving the model more efficiently, the simplex algorithm, stochastic simulation and the proposed hybrid algorithm are integrated to design a powerful ...

-This paper discusses the deployment of Genetic algorithm optimization method for synthesis of antenna array radiation pattern in adaptive beam forming. The synthesis problem discussed is to find the weights of the antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the side lobe level. This technique proved its effectiveness in improving the perfo...

Series of measurements should be planned carefully in order to reduce the costs and to allow an efficient execution at measuring devices. For this planning process, we present a multi-step optimization method using genetic algorithms. As a concrete application, we arrange a set of Design of Experiment measuring points appearing during the calibration of combustion engines in an optimal way. Key...