This paper represents an approach of using simulation models and genetic algorithms for generating an aggregative production plan to maximize the total profit of the firm. The described methodology provides a tool which assists the company management in decision which of the suitable solutions will become the production plan. The entire system is composed by a business information system a data...

Almost all real-world problems are dynamic and as such not all problem instances are known a priori. Many strategies to deal with dynamic problems exist in the literature, however they are not fully tested on combinatorial problems due to the deficiency of benchmarks. This paper presents a benchmark generator that uses Genetic Algorithms to produce benchmark problems for the dynamic traveling s...

This paper presents an approach for the automated cryptanalysis of substitution ciphers based on a recent evolutionary metaheuristic called Scatter Search. It is a population-based metaheuristic founded on a formulation proposed two decades ago by Fred Glover. It uses linear combinations on a population subsets to create new solutions while other evolutionary approaches like genetic algorithms ...

Neural network has been popular in time series prediction in financial areas, because of their advantages in handling nonlinear systems. This paper hybridizes genetic algorithm and artificial neural network method (GABP), and hybridizes principal component analysis and support vector machine (PCA-SVM) to predict the next opening price in stock markets. Principal component analysis method is app...

A new method based on adaptive GA(genetic algorithm) for optimizing the parameters of CMOS operational amplifier is presented in this paper. The synthesis of the Op-amp (operational amplifier) can be translated into multiple-objective optimization task, in which a large number of specifications have to be taken into account. Such as DC-gain, bandwidth of unity gain, phase-margin, power, noise a...

A novel method of the IIR filter design using the genetic algorithm is described in the paper. Newly, a simplex direct search method is included to the algorithm to enable its faster convergence. The design procedure is implemented in the MATLAB program environment. The genetic algorithm applied is able to find a solution of the task successfully. Filter coefficients quantization process is inc...

One important issue regarding the implementation of cellular manufacturing systems relates to deciding whether to convert an existing job shop into a cellular manufacturing system comprehensively in a single go, or in stages incrementally by forming cells one after the other taking the advantage of the experiences of implementation. In this paper two heuristic methods based on multi-stage progr...

Genetic algorithms are well suited to hybridization. Problem division between components of the hybrid varies by problem type and by the mechanisms included in the hybrid. We propose a hybridization technique for combining genetic algorithms (GAs) and deterministic algorithms based on solution candidate partitioning. We conduct a set of experiments to evaluate several instances of this hybridiz...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...