In this paper, we describe the use of an evolutionary algorithm (EA) to solve dynamic control optimization problems in engineering. In this class of problems, a set of control variables must be manipulated over time to optimize the outcome, which is ...

Evolutionary Algorithms (EAs) have been largely applied to optimisation and synthesis of controllers. In spite of several successful applications and competitive solutions, the stochastic nature of EAs and the uncertainty of the results have ...

This paper presents an efficient technique of designing two-dimensional IIR digital filters using a new algorithm involving the tightly coupled synergism of particle swarm optimization and differential evolution. The design task is reformulated as a ...

We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data ...

Mobile ad hoc networks are typically designed and evaluated in generic simulation environments. However the real conditions in which these networks are deployed can be quite different in terms of RF attentution, topology, and traffic load. Furthermore, ...

Wavelet-based image coders like the JPEG2000 standard are the state of the art in image compression. Unlike traditional image coders, however, their performance depends to a large degree on the choice of a good wavelet. Most wavelet-based image coders ...

This paper describes how genetic programming was used as an invention machine to automatically synthesize complete designs for six optical lens systems that duplicated the functionality of previously patented lens systems. The automatic synthesis was ...

We present a multi-objective evolutionary algorithm approach to the map-labelling problem. Map-labelling involves placing labels for sites onto a map such that the result is easy to read and usable for navigation. However, map-users vary in their ...

This paper examines a real-world application of genetic algorithms -- solving the United States Navy's Sailor Assignment Problem (SAP). The SAP is a complex assignment problem in which each of n sailors must be assigned one job drawn from a set of m ...

Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of symbolic regression in GP, from the viewpoint of Statistical Learning Theory,...

This paper proposes a novel technique for a program evolution based on probabilistic models. In the proposed method, two probabilistic distribution models with probabilistic dependencies between variables are used together. We empirically comfirm that ...

This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by the existence of multiple chromosomes in natural evolution, particularly ...

Most existing research on robust design using evolutionary algorithms (EA) follows the paradigm of traditional robust design, in which parameters of a design solution are tuned to improve the robustness of the system. However, the topological structure ...

The well-known Griewangk function, used for evaluation of evolutionary algorithms, becomes easier as the number of dimensions grows. This paper suggests three alternative implementations that maintain function complexity for high-dimensional versions of ...

In order to overcome the low convergence speed and prematurity of classical genetic algorithm, an improved method named directional self-learning of genetic algorithm (DSLGA) is proposed in this paper. Through the self-learning operator directional ...

A genetic algorithm is proposed with real value variables, spatially based crossover operator, a small mutation, large scale mutation, vector sum local search and geometric only based objective function to generate candidate molecule conformations from ...

Several researchers have used Price's equation (from biology theory literature) to analyze the various components of an Evolutionary Algorithm (EA) while it is running, giving insights into the components contributions and interactions. While their ...

Conservation of functionally identical copies of the same gene throughout the generations is not an easy task. In this study, based on the biological evidence that suggests the existence of the developmental error as one of the ways to preserve ...

A need for solving more and more complex problems drives the Evolutionary Computation community towards advanced models of Evolutionary Algorithms. One such model is the island model which, although the subject of a variety of studies, still needs ...