Evolutionary Computation

Misyurov D.A. Dialectical formulas based on the binary notation as the development formulas // Credo New. 2012. №2

by Dmitry Misyurov

The article suggests dialectical formulas based on the binary notation as the development formulas: formula with... more The article suggests dialectical formulas based on the binary notation as the development formulas: formula with dominant and the non-dominant elements; universal formula; formula with symbolic weight of elements; tautological formula. For example, it suggests an opportunity to use the dialectical formulas for modeling and artificial intelligence creation, etc.

Multidisciplinary design optimization of long endurance unmanned aerial vehicle wing

by Ranjan Ganguli

Rajagopal, S., and Ganguli, R., "Multidisciplinary design optimization of long endurance unmanned aerial vehicle wing", CMES - Computer Modeling in Engineering and Science

The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The... more The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The first step performs a single objective aerodynamic optimization and the second step involves a coupled dual objective aerodynamic and structural optimization. During the first step, airfoil geometry is optimized to get maximum endurance parameter at a 2D level with maximum thickness to chord ratio and maximum camber as design variables. Leading edge curvature, trailing edge radius, zero lift drag coefficient and zero lift moment coefficient are taken as constraints. Once the airfoil geometry is finalized, the wing planform parameters are optimized with minimization of wing weight and maximization of endurance. Four design variables from aerodynamics discipline namely taper ratio, aspect ratio, wing loading and wing twist are considered. Also, four more design variables from the structures discipline namely the upper and lower skin thicknesses at root and tip of the wing are added. Constraints are stall speed, maximum speed, rate of climb, strength and stiffness. The 2D airfoil and 3D wing aerodynamic analysis is performed by the XFLR5 panel method code and the structural analysis is performed by the MSC-NASTRAN finite element code. In the optimization process, a multi-objective evolutionary algorithm named NSGA-II (non-dominated sorting genetic algorithm) is used to discover the full Pareto front for the dual objective problem. In the second step, in order to reduce the time of computation, the analysis tools are replaced by a Kriging meta-model. For this dual objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the preliminary design of UAV wing.

Multidisciplinary Design Optimization of Long Endurance

by Ranjan Ganguli

Rajagopal, S., and Ganguli, R., “Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing”, Computer Modeling in Engineering and Science, Vol. 81, No. 1, 2011, pp. 1-34.

Exploring Isospectral Spring-Mass Systems with Firefly Algorithm

by Ranjan Ganguli

Dutta, R., Ganguli, R., Mani, V., “Exploring Isospectral Spring-Mass Systems with Firefly Algorithm”, Proceedings of the Royal Society A, Vol. 467, No. 2135, 2011, pp. 3222-3240.

This paper investigates in-line spring–mass systems (An), fixed at one end and free at the other, with n-degrees of... more This paper investigates in-line spring–mass systems (An), fixed at one end and free at the other, with n-degrees of freedom (d.f.). The objective is to find feasible in-line systems (Bn) that are isospectral to a given system. The spring–mass systems, An and Bn, are represented by Jacobi matrices. An error function is developed with the help of the Jacobi matrices An and Bn. The problem of finding the isospectral systems is posed as an optimization problem with the aim of minimizing the error function. The approach for creating isospectral systems uses the fact that the trace of two isospectral Jacobi matrices An and Bn should be identical. A modification is made to the diagonal elements of the
given Jacobi matrix (An), to create the isospectral systems. The optimization problem is solved using the firefly algorithm augmented by a local search procedure. Numerical results are obtained and resulting isospectral systems are shown for 4 d.f. and 10 d.f.
systems.

Heuristic techniques for variable and value ordering in CSPs

by Malek Mouhoub

Malek Mouhoub, Bahareh Jafari Jashmi: Heuristic techniques for variable and value ordering in CSPs. GECCO 2011: 457-464

A Constraint Satisfaction Problem (CSP) is a powerful framework for representing and solving constraint problems. When... more A Constraint Satisfaction Problem (CSP) is a powerful framework for representing and solving constraint problems. When solving a CSP using a backtrack search method, one important factor that reduces the size of the search space drastically is the order in which variables and values are examined. Many heuristics for static and dynamic variable ordering have been proposed and the most popular and powerful are those that gather information about the failures during the constraint propagation phase, in the form of constraint weights. These later heuristics are called conflict driven heuristics. In this paper, we propose two of these heuristics respectively based on Hill Climbing (HC) and Ant Colony Optimization (ACO) for weighing constraints. In addition, we propose two new value ordering techniques, respectively based on HC and ACO, that rank the values based on their ability to satisfy the constraints attached to their corresponding variables. Several experiments were conducted on various types of problems including random, quasi random and patterned problems. The results show that the proposed variable ordering heuristics, are successful especially in the case of hard random problems. Also, when using the proposed value and variable ordering together, we can improve the performance particularly in the case of random problems.

Genetic and Evolutionary Computation for Image Processing and Analysis

by Stefano Cagnoni

HCS: a new local search strategy for memetic multiobjective evolutionary algorithms

by Gustavo Sanchez

Velocity predictions in compound channels with vegetated floodplains using genetic programming

by Roger Falconer - Cardiff University

Paper 72:  Harris, E. L., Babovic, V. and Falconer, R. A. 2003. Velocity predictions in compound channels with vegetated floodplains using genetic programming. International Journal of River Basin Management, IAHR. 1(2), 117-125

Abstract
Data collection and storage methods have improved vastly over recent years however the process of... more Abstract
Data collection and storage methods have improved vastly over recent years however the process of information and knowledge extraction from data has not mirrored this.  The application of computer supported scientific knowledge discovery processes to carefully collected observations aims to improve the understanding of the processes that generated or produced these data.  In this paper, these new techniques have been applied to the complex and poorly understood phenomena of flow through vegetation. The ability to predict, with improved accuracy, velocities within wetlands and other vegetated areas would be advantageous as these regions are increasingly being recognised for their natural flood alleviation properties.
In this study, laboratory data collected in a flume with steady flows over a deep channel with relatively shallow vegetated floodplains was used to induce the formulation of expressions using a data driven discovery technique, genetic programming (GP), to gain further understanding of the floodplain processes within vegetated areas. The performance of the genetic program is reported for three variations of the GP.  The reported results of the experiments were found to be encouraging.

An Eco-inspired Evolutionary Algorithm Applied to Numerical Optimization

by Rafael Stubs Parpinelli

Adaptive terrain-based memetic algorithms

by Carlos R. B. Azevedo

Improving image vector quantization with a genetic accelerated k-means algorithm

by Carlos R. B. Azevedo

An Evolutionary Approach for Vector Quantization Codebook Optimization

by Carlos R. B. Azevedo

Selection of Minimal Variable Subsets with the help of Genetic Algorithms in Economic Analysis

by Esmail Bonakdarian

Journal of Interdisciplinary EconomicsApril 9, 2010 with Hans J. Czap, Natalia V. Czap

Walk the talk? The effect of voting and excludability in public goods experiments

by Esmail Bonakdarian

The Use of Evolutionary Algorithms in the Analysis of Economics Experiments

by Esmail Bonakdarian

Grouping genetic operators for the delineation of functional areas based on spatial interaction

by José M. Casado-Díaz

Martínez-Bernabeu, L.; Flórez-Revuelta, F. y Casado-Díaz, J.M. (2012) “Grouping genetic operators for the delineation of functional areas based on spatial interaction”, Expert Systems with Applications, Volume 39, Issue 8, 15 June 2012, Pages 6754–6766 - doi:10.1016/j.eswa.2011.12.026.

The delineation of functional economic areas, or market areas, is a combinatorial optimisation problem, defined as the... more The delineation of functional economic areas, or market areas, is a combinatorial optimisation problem, defined as the partition of a given set of indivisible spatial units (covering a territory) into regions with high cohesion and self-containment —in terms of spatial interaction data: flows— under constraints of size, self-containment and/or continuity, typicaly solved with greedy methods. An evolutionary algorithm with many tailored operators for the delimitation of Labour Market Areas was recently proposed. This algorithm allowed finding better solutions but was very time consuming, this hampering its use in large real-world problems.
In this paper we present several group-based mutation operators featuring general unary and binary operations over disjoint groups, tailored to tackle with that problem. A comparative analysis of our approach with a greedy algorithm and the previous evolutionary proposals shows that our algorithm always gives better results concerning both quality and time consumed (except for the greedy), and is able to tackle with large real-world problems in reasonable time.

Keywords: functional areas, local market, evolutionary algorithm, grouping problem, regionalisation, combinatorial optimisation

Evolving experience-dependent robust behaviour in embodied agents

by Jose A. Fernandez

In this work, based on behavioural and dynamical evidence, a study of simulated agents with the capacity to change... more In this work, based on behavioural and dynamical evidence, a study of simulated agents with the capacity to change feedback from their bodies to accomplish a one-legged walking task is proposed to understand the emergence of coupled dynamics for robust behaviour. Agents evolve with evolutionary-defined biases that modify incoming body signals (sensory offsets). Analyses on whether these agents show further dependence to their environmental coupled dynamics than others with no feedback control is described in this article. The ability to sustain behaviours is tested during lifetime experiments with mutational and sensory perturbations after evolution. Using dynamical systems analysis, this work identifies conditions for the emergence of dynamical mechanisms that remain functional despite sensory perturbations. Results indicate that evolved agents with evolvable sensory offset depends not only on where in neural space the state of the neural system operates, but also on the transients to which the inner-system was being driven by sensory signals from its interactions with the environment, controller, and agent body. Experimental evidence here leads discussions on a dynamical systems perspective on behavioural robustness that goes beyond attractors of controller phase space.

Evolving cognitive-behavioural dependencies in situated agents for behavioural robustness

by Jose A. Fernandez

This article investigates the emergence of robust behaviour in agents with dynamically limited controllers (monostable... more This article investigates the emergence of robust behaviour in agents with dynamically limited controllers (monostable agents), and compares their performance to less limited ones (bistable agents). ‘Dynamically limited’ here refers to a reduced quantity of steady states that an agent controller exhibits when it does not receive stimulus from the environment. Agents are evolved for categorical perception, a minimal cognitive task, and must correlate approaching or avoiding movements based on (two) different types of objects. Results indicate a significant tendency to better behavioural robustness by monostable in contrast to bistable agents in the presence of sensorimotor, mutational, and structural perturbations. Discussions here focus on a further dependence to coupled dynamics by the former agents to explain such a tendency.

Stiffness identification and damage localization via differential evolution algorithms

by Sara Casciati

Casciati S. (2008). “Stiffness identification and damage localization via differential evolution algorithms”. Structural Control & Health Monitoring, 15(3), 436-449. ISSN: 1545-2255.

DATA E LUOGO DI PUBBLICAZIONE: April 2008; John Wiley & Sons, Ltd., Chichester PO19 8SQ, W Sussex, England.

ABSTRACT. The goal of structural health monitoring is to identify which discrepancies between the actual behaviour of... more ABSTRACT. The goal of structural health monitoring is to identify which discrepancies between the actual behaviour of a structure and its reference undamaged state are indicative of damage. For this purpose, an objective function, which minimizes the difference between the measured and theoretical modal characteristics of the structure, is formulated. By selecting the stiffness parameters as optimization variables, a differential evolution algorithm is applied to create successive generations that better reflect the measured response, until a certain tolerance is met. At each step of the algorithm, the current modal parameters are recalculated from the new generation of stiffness matrices to estimate the value of the objective function. This procedure represents a favourable path to solve the so-called ‘inverse problem’. Furthermore, the comparison of the identified stiffness matrix with the initial one allows for damage detection and localization. A numerical example, where a generic structure is discretized into finite elements, is provided.

KEYWORDS: damage; element stiffness matrix; differential evolution algorithm; finite element analyses; modal parameters; objective function; optimization problem

Interactive evolutionary computing for the binarization of degenerated handwritten images

by Lambert Schomaker

Van der Zant, T., Schomaker, L.R.B., Brink, A.A. (2008). Interactive Evolutionary Computing for the binarization of degenerated handwritten images, In: B.A. Yanikoglu and K. Berkner (Eds.), Proceedings of Document Recognition and Retrieval XV, IS&T/SPIE International Symposium on Electronic Imaging, pp. 6815-6

The digital cleaning of dirty and old documents and the binarization into a black/white image can be a tedious... more The digital cleaning of dirty and old documents and the binarization into a black/white image can be a tedious process. It is usually done by experts. In this article a method is shown that is easy for the end user. Untrained persons are able to do this task now while before an expert was needed. The method uses interactive evolutionary computing to program image processing operations that act on the document image.