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Biomedical subjects

H G Beyer

Publications and source records attributed to H G Beyer.

7 recordsLinked to original sources
PubMed2001

Self-adaptive genetic algorithms with simulated binary crossover.

Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored mainly with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the self-adaptive feature of real-parameter genetic algorithms (GAs) using a simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with the SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need for emphasizing further studies on self-adaptive GAs.

Algorithms↗
PubMed2000

Do evolutionary processes minimize expected losses?

Evolution by variation and natural selection is often viewed as an optimization process that favors those organisms which are best adapted to their environment. This leaves open the issue of how to measure adaptation and what criterion is implied for optimization. This problem has been framed and analysed mathematically under the assumption that individuals compete to minimize expected losses across a series of decisions (e.g. choice of behavior), where each decision offers a stochastic payoff. But the fact that a particular analysis is tractable for a specified criterion does not imply the fidelity of that criterion. Computer simulations involving a version of the k -armed bandit problem can address the veracity of the hypothesis that individuals are selected to minimize expected losses. The results offered here do not support this hypothesis.

Adaptation, Physiological↗
PubMed2000

Analysis of the (1, lambda)-ES on the parabolic ridge.

The progress rate of the (1,+ lambda)-ES (Evolution Strategy) is analyzed on the parabolic ridge test function. A different progress behavior is observed for the (1, lambda)-ES than for the sphere model test function. The characteristics of the progress rate picture for the plus strategy differs little from the one obtained for the sphere model, but this strategy has drastically worse progress rate values than those obtained for the comma strategy. The dynamics of the distance to the progress axis is also investigated. A theoretical formula is derived to estimate the change in this distance over generations. This formula is used to derive the expected value of the problem-specific distance to the ridge axis. The correctness of the formulae is supported by simulation results.

Algorithms↗
PubMed2000

Analysis of the (mu/mu, lambda)-ES on the parabolic ridge.

The progress behavior of evolution strategies (ES) using recombination is analyzed in this paper on the parabolic ridge. This test function represents landscapes far from the optimum. The ES algorithms with intermediate and dominant recombination are considered in the analysis. The derivations are presented for intermediate recombination. Thereafter, the formulae for dominant recombination are obtained using the so-called surrogate mutation model. In the analysis, the formulae are derived for the progress rate psi and for the stationary distance R(infinity) to the ridge axis. As a result, it will be shown that the progress rate psi can increase if recombination is applied. Simulations are used to show the appropriateness of the formulae derived.

Algorithms↗
PubMed1997

An alternative explanation for the manner in which genetic algorithms operate.

The common explanation of the manner in which genetic algorithms (GAs) process individuals in a population of contending solutions relies on the 'building block hypothesis'. This suggests that successively better solutions are generated by combining useful parts of extant solutions. An alternative explanation is presented which focuses on the collective phenomena taking place in populations that undergo recombination. The new explanation is derived from investigations in evolution strategies (ESs). The principles studied are general, and hold for all evolutionary algorithms (EAs), including genetic algorithms (GAs). Further, they appear to be somewhat analogous to some theories and observations on the benefits of sex in biota.

Algorithms↗
PubMed1993

The value of follow-up after curative surgery of colorectal carcinoma.

Between 1978 and 1989, 1045 of 1399 patients (580 male and 474 female) had undergone curative surgery for colorectal carcinoma. Of these patients, 350 (33%) had recurrences, another 16 (1.5%) developed a metachronous colorectal cancer, and 23 (2%) had cancers of other organs. An isolated locoregional recurrence was found in 75 of 350 (21%). The remaining 275 of 350 (79%) of the patients showed systemic dissemination of the carcinoma. Reoperations with curative intent were performed on 56 of 350 (16%) of the patients. Only 21 of the 56 resected patients (38%), i.e., 21 of 350 (6%), are without recurrence at the end of the follow-up period on December 31, 1990. Despite a curative reoperation, 62% of the patients again developed recurrent growths. There is an imbalance of the efforts invested in tumor follow-up and the benefits gained. Further follow-up programs should be investigated in a controlled, prospective fashion.

Adult↗