Search results for "algorithm"
showing 10 items of 4887 documents
On sampling error in evolutionary algorithms
2021
The initial population in evolutionary algorithms (EAs) should form a representative sample of all possible solutions (the search space). While large populations accurately approximate the distribution of possible solutions, small populations tend to incorporate a sampling error. A low sampling error at initialization is necessary (but not sufficient) for a reliable search since a low sampling error reduces the overall random variations in a random sample. For this reason, we have recently presented a model to determine a minimum initial population size so that the sampling error is lower than a threshold, given a confidence level. Our model allows practitioners of, for example, genetic pro…
Sex-Specific Habitat Selection in an Edge Habitat Specialist, the Western Barbastelle Bat
2011
The niche variation hypothesis suggests that a population's ability to react to varying environmental conditions depend on the behavioural variability of its members. However, most studies on bats, including the work on the habitat use of the western barbastelle bat, Barbastella barbastellus, have not considered sex-specific and individual variability. We studied the habitat use of 12 female and five male western barbastelle bats within their home ranges with respect to available habitat types by applying kernel methods and Euclidean distances. Our results indicate individual habitat preferences within and among sexes of this species. Females preferred deciduous forest and linear elements w…
Mate‐Search Efficiency Can Determine the Evolution of Separate Sexes and the Stability of Hermaphroditism in Animals
2002
Limited availability of mating partners has been proposed as an explanation for the occurrence of simultaneous hermaphroditism in animals with pair mating. When low population density or low mobility of a species limits the number of potential mates, simultaneous hermaphrodites may have a selective advantage because, first, they are able to adjust the allocation of resources between male and female functions in order to maximize fitness; second, in a hermaphroditic population the likelihood of meeting a partner is higher because all individuals are potential mates; and, third, in the absence of mating partners, many simultaneously hermaphroditic animals have the option of reproducing throug…
Can adaptation lead to extinction?
2005
Ever since J.B.S. Haldane proposed the idea, evolutionary biologists are aware that individual level adaptations do not necessarily lead to optimal population performance. A few deeply mathematical models, drawing from a diverse range of systems, even predict that individual selection can lead to the extinction of the whole population, a phenomenon which has become known as evolutionary suicide. Due to the complexity of both following adaptation and determining the exact cause of an extinction, evolutionary suicide has remained untested empirically. However, three recent empirical studies suggest that it may occur, and that suicide should be taken seriously as a potentially important evolut…
On the Bias of Syntactic Geometric Recombination in Genetic Programming and Grammatical Evolution
2015
For fixed-length binary representations as used in genetic algorithms, standard recombination operators (e.g.,~one-point crossover) are unbiased. Thus, the application of recombination only reshuffles the alleles and does not change the statistical properties in the population. Using a geometric view on recombination operators, most search operators for fixed-length strings are geometric, which means that the distances between offspring and their parents are less than, or equal to, the distance between their parents. In genetic programming (GP) and grammatical evolution (GE), the situation is different since the recombination operators are applied to variable-length structures. Thus, most r…
Optimizing the Integration Area and Performance of VLIW Architectures by Hardware/Software Co-design
2021
The cost and the performance are major concerns that the designers of embedded processors shall take into account, especially for market considerations. In order to reduce the cost, embedded systems rely on simple hardware architectures like VLIW (Very Long Instruction Word) processors and they look for compiler support. This paper aims at developing a design space explorer of VLIW architectures from different perspectives like processing performance and integration area. A multi-objective Genetic Algorithm (GA) was used to find the optimum hardware configuration of an embedded system and the optimization rules applied by compiler on the benchmarks code. The first step consisted in represen…
An adaption mechanism for the error threshold of XCSF
2020
Learning Classifier System (LCS) is a class of rule-based learning algorithms, which combine reinforcement learning (RL) and genetic algorithm (GA) techniques to evolve a population of classifiers. The most prominent example is XCS, for which many variants have been proposed in the past, including XCSF for function approximation. Although XCSF is a promising candidate for supporting autonomy in computing systems, it still must undergo parameter optimization prior to deployment. However, in case the later deployment environment is unknown, a-priori parameter optimization is not possible, raising the need for XCSF to automatically determine suitable parameter values at run-time. One of the mo…
Multi-modal search for multiobjective optimization: an application to optimal smart grids management
2012
This paper studies the possibility to use efficient multimodal optimizers for multi-objective optimization. In this paper, the application area considered for such new approach is the optimal dispatch of energy sources in smart microgrids. The problem indeed shows a non uniform Pareto front and requires efficient optimal search methods. The idea is to exploit the potential of agents in population-based heuristics to improve diversity in the Pareto front, where solutions show the same rank and are thus equally weighted. Since Pareto dominance is at the basis of the theory of multi-objective optimization, most algorithms show the non dominance ranking as quality indicator, with some problem i…
A hybrid evolution strategy for the open vehicle routing problem
2010
This paper presents a hybrid evolution strategy (ES) for solving the open vehicle routing problem (OVRP), which is a well-known combinatorial optimization problem that addresses the service of a set of customers using a homogeneous fleet of non-depot returning capacitated vehicles. The objective is to minimize the fleet size and the distance traveled. The proposed solution method manipulates a population of @m individuals using a (@m+@l)-ES; at each generation, a new intermediate population of @l offspring is produced via mutation, using arcs extracted from parent individuals. The selection and combination of arcs is dictated by a vector of strategy parameters. A multi-parent recombination …
Scheduling a cellular manufacturing system with GA
2002
The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual…