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Fitness Function (fitness + function)
Selected AbstractsFast computation evolutionary programming algorithm for the economic dispatch problemEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 1 2006P. Somasundaram Abstract This paper essentially aims to propose a new EP based algorithm for solving the ED problem. The ED problem is solved using EP with system lambda as decision variable and power mismatch as fitness function. The algorithm is made fast through judicious modifications in initialization of the parent population, offspring generation and selection of the normal distribution curve. The proposed modifications reduce the search region progressively and generate only effective offsprings. The proposed algorithm is tested on a number of sample systems with quadratic cost function and also on a 10-unit system with piecewise quadratic cost function. The computational results reveal that the proposed algorithm has an excellent convergence characteristic and is superior to other EP based methods in many respects. Copyright © 2005 John Wiley & Sons, Ltd. [source] Survivable wavelength-routed optical network design using genetic algorithmsEUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 3 2008Y. S. Kavian The provision of acceptable service in the presence of failures and attacks is a major issue in the design of next generation dense wavelength division multiplexing (DWDM) networks. Survivability is provided by the establishment of spare lightpaths for each connection request to protect the working lightpaths. This paper presents a genetic algorithm (GA) solver for the routing and wavelength assignment problem with working and spare lightpaths to design survivable optical networks in the presence of a single link failure. Lightpaths are encoded into chromosomes made up of a fixed number of genes equal to the number of entries in the traffic demand matrix. Each gene represents one valid path and is thus coded as a variable length binary string. After crossover and mutation, each member of the population represents a set of valid but possibly incompatible paths and those that do not satisfy the problem constraints are discarded. The best paths are then found by use of a fitness function and these are assigned the minimum number of wavelengths according to the problem constraints. The proposed approach has been evaluated on dedicated path protection and shared path protection. Simulation results show that the GA method is efficient and able to design DWDM survivable real-world optical mesh networks. Copyright © 2007 John Wiley & Sons, Ltd. [source] THE CONDITIONS FOR SPECIATION THROUGH INTRASPECIFIC COMPETITIONEVOLUTION, Issue 11 2006Reinhard Bürger Abstract It has been shown theoretically that sympatric speciation can occur if intraspecific competition is strong enough to induce disruptive selection. However, the plausibility of the involved processes is under debate, and many questions on the conditions for speciation remain unresolved. For instance, is strong disruptive selection sufficient for speciation? Which roles do genetic architecture and initial composition of the population play? How strong must assortative mating be before a population can split in two? These are some of the issues we address here. We investigate a diploid multilocus model of a quantitative trait that is under frequency-dependent selection caused by a balance of intraspecific competition and frequency-independent stabilizing selection. This trait also acts as mating character for assortment. It has been established previously that speciation can occur only if competition is strong enough to induce disruptive selection. We find that speciation becomes more difficult for very strong competition, because then extremely strong assortment is required. Thus, speciation is most likely for intermediate strengths of competition, where it requires strong, but not extremely strong, assortment. For this range of parameters, however, it is not obvious how assortment can evolve from low to high levels, because with moderately strong assortment less genetic variation is maintained than under weak or strong assortment sometimes none at all. In addition to the strength of frequency-dependent competition and assortative mating, the roles of the number of loci, the distribution of allelic effects, the initial conditions, costs to being choosy, the strength of stabilizing selection, and the particular choice of the fitness function are explored. A multitude of possible evolutionary outcomes is observed, including loss of all genetic variation, splitting in two to five species, as well as very short and extremely long stable limit cycles. On the methodological side, we propose quantitative measures for deciding whether a given distribution reflects two (or more) reproductively isolated clusters. [source] ADAPTIVE CHANGE IN THE RESOURCE-EXPLOITATION TRAITS OF A GENERALIST CONSUMER: THE CEOLUTION AND COEXISTENCE OF GENERALISTS AND SPECIALISTSEVOLUTION, Issue 3 2006Peter A. Abrams Abstract Mathematical models of consumer-resource systems are used to explore the evolution of traits related to resource acquisition in a generalist consumer species that is capable of exploiting two resources. The analysis focuses on whether evolution of traits determining the capture rates of two resources by a consumer species produce one generalist, two specialists, or all three types, when all types are characterized by a common fitness function. In systems with a stable equilibrium, evolution produces one generalist or two specialists, depending on the second derivative of the trade-off relationship. When there are sustained population fluctuations, the nature of the trade-off between the consumer's capture rates of the two resources still plays a key role in determining the evolutionary outcome. If the trade-off is described by a choice variable between zero and one that is raised to a power n, polymorphic states are possible when n > 1, which implies a positive second derivative of the curve. These states are either dimorphism, with two relatively specialized consumer types, or trimorphism, with a single generalist type and two specialists. Both endogenously driven consumer-resource cycles, and fluctuations driven by an environmental variable affecting resource growth are considered. Trimorphic evolutionary outcomes are relatively common in the case of endogenous cycles. In contrast to a previous study, these trimorphisms can often evolve even when new lineages are constrained to have phenotypes very similar to existing lineages. Exogenous cycles driven by environmental variation in resource growth rates appear to be much less likely to produce a mixture of generalists and specialists than are endogenous consumer-resource cycles. [source] THE EVOLUTION OF GENETIC CANALIZATION UNDER FLUCTUATING SELECTIONEVOLUTION, Issue 1 2000Tadeusz J. Kawecki Abstract., If the direction of selection changes from generation to generation, the ability to respond to selection is maladaptive: the response to selection in one generation leads to reduced fitness in the next. Because the response is determined by the amount of genetic variance expressed at the phenotypic level, rapidly fluctuating selection should favor modifier genes that reduce the phenotypic effect of alleles segregating at structural loci underlying the trait. Such reduction in phenotypic expression of genetic variation has been named "genetic canalization." I support this argument with a series of two- and multilocus models with alternating linear selection and Gaussian selection with fluctuating optimum. A canalizing modifier gene affects the fitness of its carriers in three ways: (1) it reduces the phenotypic consequences of genetic response to previous selection; (2) it reduces the genetic response to selection, which is manifested as linkage disequilibrium between the modifier and structural loci; and (3) it reduces the phenotypic variance. The first two effects reduce fitness under directional selection sustained for several generations, but improve fitness when the direction of selection has just been reversed. The net effect tends to favor a canalizing modifier under rapidly fluctuating selection regimes (period of eight generations or less). The third effect improves fitness of the modifier allele if the fitness function is convex and reduces it if the function is concave. Under fluctuating Gaussian selection, the population is more likely to experience the concave portion of the fitness function when selection is stronger. Therefore, only weak to moderately strong fluctuating Gaussian selection favors genetic canalization. This paper considerably broadens the conditions that favor genetic canalization, which so far has only been postulated to evolve under long-term stabilizing selection. [source] A structural damage identification method based on genetic algorithm and vibrational dataINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 13 2007Carlos C. H. Borges Abstract The problem of damage identification in framed structures using vibrational data is considered. The identification problem is modelled as an optimization task and the use of measured natural frequencies as well as modeshape information in the construction of objective functions is discussed. In a first attempt, a standard genetic algorithm is shown to be ineffective in obtaining the correct damage distribution in test problems. Using domain knowledge, modifications are introduced in the coding process, in the initial population generation, in the fitness function, and in the genetic operators, leading to a promising tool to solve this class of problems. Synthetic problems, with the addition of noise in the simulated measured data associated with the damaged structure, are analysed in order to assess the capability of the proposed technique. Copyright © 2006 John Wiley & Sons, Ltd. [source] Video tracking system optimization using evolution strategiesINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 2 2007Jesús García Abstract A video-based tracking system for airport surveillance, composed by modules performing vision tasks at different levels, is adapted for operational conditions by means of Evolution Strategies (ES). An optimization procedure has been carried out considering different scenes composed of representative trajectories, supported by a global evaluation metric proposed to quantify the system performance. The generalization problem (the search of appropriate solutions for general situations, avoiding over-adaptation to particular conditions) is approached considering evaluation of ES-individuals over combinations of trajectories to build the fitness function. In this way, the optimization procedure covers sets of trajectories representing different types of problems. Besides, alternative operators for aggregating partial evaluations have been analysed. Results show how the optimization strategy provides a sensitive tuning of performance related to input parameters at different levels, and how the combination of different situations improves the generalization capability of the trained system. The global performance final system after optimization is also compared with representative algorithms in the state of the art of visual tracking. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 75,90, 2007 [source] An evolutionary algorithm for constructing a decision forest: Combining the classification of disjoints decision treesINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 4 2008Lior Rokach Decision forest is an ensemble classification method that combines multiple decision trees to in a manner that results in more accurate classifications. By combining multiple heterogeneous decision trees, decision forest is effective in mitigating noise that is often prevalent in real-world classification tasks. This paper presents a new genetic algorithm for constructing a decision forest. Each decision tree classifier is trained using a disjoint set of attributes. Moreover, we examine the effectiveness of using a Vapnik,Chervonenkis dimension bound for evaluating the fitness function of decision forest. The new algorithm was tested on various datasets. The obtained results have been compared to other methods, indicating the superiority of the proposed algorithm. © 2008 Wiley Periodicals, Inc. [source] Design of a linear array antenna for shaped beam using genetic algorithmINTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, Issue 5 2008Sona O. Kundukulam Abstract A linear array antenna design with desired radiation pattern has been presented based on genetic algorithm (GA) approach. Examples of cosecant and flat-topped beam patterns are illustrated to show the flexibility of GA to solve complex antenna synthesis problems by suitably selecting the fitness function, even with a simple GA. The results have been validated by IE3D electromagnetic simulation. The antenna arrays with different element geometries can also be implemented using the proposed technique. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008. [source] The importance of growth and mortality costs in the evolution of the optimal life historyJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 6 2006D. A. ROFF Abstract A central assumption of life history theory is that the evolution of the component traits is determined in part by trade-offs between these traits. Whereas the existence of such trade-offs has been well demonstrated, the relative importance of these remains unclear. In this paper we use optimality theory to test the hypothesis that the trade-off between present and future fecundity induced by the costs of continued growth is a sufficient explanation for the optimal age at first reproduction, ,, and the optimal allocation to reproduction, G, in 38 populations of perch and Arctic char. This hypothesis is rejected for both traits and we conclude that this trade-off, by itself, is an insufficient explanation for the observed values of , and G. Similarly, a fitness function that assumes a mortality cost to reproduction but no growth cost cannot account for the observed values of ,. In contrast, under the assumption that fitness is maximized, the observed life histories can be accounted for by the joint action of trade-offs between growth and reproductive allocation and between mortality and reproductive allocation (Individual Juvenile Mortality model). Although the ability of the growth/mortality model to fit the data does not prove that this is the mechanism driving the evolution of the optimal age at first reproduction and allocation to reproduction, the fit does demonstrate that the hypothesis is consistent with the data and hence cannot at this time be rejected. We also examine two simpler versions of this model, one in which adult mortality is a constant proportion of juvenile mortality [Proportional Juvenile Mortality (PJM) model] and one in which the proportionality is constant within but not necessarily between species [Specific Juvenile Mortality (SSJM) model]. We find that the PJM model is unacceptable but that the SSJM model produces fits suggesting that, within the two species studied, juvenile mortality is proportional to adult mortality but the value differs between the two species. [source] Quantitative structure/property relationship analysis of Caco-2 permeability using a genetic algorithm-based partial least squares methodJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 10 2002Fumiyoshi Yamashita Abstract Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure,property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (rpred) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability. © 2002 Wiley-Liss Inc. and the American Pharmaceutical Association J Pharm Sci 91:2230,2239, 2002 [source] Use of Genetic Algorithm to Determine the Kinetic Model of Solid-State ReactionsJOURNAL OF THE AMERICAN CERAMIC SOCIETY, Issue 5 2007S. Maitra Solid-state reactions take place by different rate-controlling heterogeneous processes. To find the appropriate kinetic model for a particular solid-state reaction, a genetic algorithm-based simulation technique was carried out using DTA data with a fitness function, and a computer program was developed for the same. The process was applied to the decomposition reactions of limestone and magnesite samples. It was observed that both the decomposition reactions mostly followed the Avrami,Erofeev kinetics model. [source] Seasonal changes in female size and its relation to reproduction in the parasitoid Asobara tabidaOIKOS, Issue 2 2001Jacintha Ellers The relation between female size and fitness was studied in female Asobara tabida throughout the field season. The size of A. tabida females varied considerably, with average size being smallest in the middle of the season. There was a positive correlation of realized fecundity with size, and the fitness advantage of larger females increased later in the season. A possible explanation for this can be found in the energy expenditure during the season. Regression analysis showed that fat use increases with size of the female, but also with temperature. Temperature was low early and late in the season, but high in the middle. We argue that the high temperatures may constrain fitness advantages of large females because of their increased metabolic needs. Variation in the form of the fitness function within the season may moderate directional selection for larger females. [source] Factors affecting the evolution of development strategies in parasitoid wasps: the importance of functional constraints and incorporating complexityENTOMOLOGIA EXPERIMENTALIS ET APPLICATA, Issue 1 2005Jeffrey A. Harvey Abstract Parasitoid wasps have long been considered as model organisms for examining optimal resource allocation to different fitness functions, such as body size and development time. Unlike insect predators, which may need to consume many prey items to attain maturity, parasitoids generally rely on a limited amount of resources that are obtained from a single source (the host). This review discusses a range of ecophysiological constraints that affect host quality and concomitantly the evolution of development strategies in parasitoids. Two macroevolutionary differences in host usage strategies (idiobiosis, koinobiosis) are initially described. Over many years, particular attention has been paid in examining a range of quantitative host attributes such as size, age, or stage, as these affect idiobiont and koinobiont parasitoid development. Parasitoids and their hosts, however, constitute only a small part of an ecological community. Consequently, host quality may be affected by a broad range of factors that may operate over variable spatial and temporal scales. Intimate factors include aggressive competition with other parasitoids and pathogens for access to host resources, whereas less intimate factors include the effects of toxic plant compounds (allelochemicals) on parasitoid performance as mediated through primary and/or secondary hosts. It is suggested that future experiments should increase the levels of trophic complexity as these influence the evolution of life history and development strategies in parasitoids. This includes integration of a suite of direct and indirect mechanisms, including biological processes occurring in different ecological realms, such as above-ground and below-ground interactions. [source] | |||||||||||||