Showing papers on "Crossover published in 1990"

Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems

Abstract: Many seemingly different problems in artificial intelligence, symbolic processing, and machine learning can be viewed as requiring discovery of a computer program that produces some desired output for particular inputs When viewed in this way, the process of solving these problems becomes equivalent to searching a space of possible computer programs for a most fit individual computer program The new "genetic programming" paradigm described herein provides a way to search for this most fit individual computer program In this new "genetic programming" paradigm, populations of computer programs are genetically bred using the Darwinian principle of survival of the fittest and using a genetic crossover (recombination) operator appropriate for genetically mating computer programs In this paper, the process of formulating and solving problems using this new paradigm is illustrated using examples from various areas Examples come from the areas of machine learning of a function; planning; sequence induction; function function identification (including symbolic regression, empirical discovery, "data to function" symbolic integration, "data to function" symbolic differentiation); solving equations, including differential equations, integral equations, and functional equations); concept formation; automatic programming; pattern recognition, time-optimal control; playing differential pursuer-evader games; neural network design; and finding a game-playing strategyfor a discrete game in extensive form

An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms

Abstract: In this paper we present some theoretical and empirical results on the interacting roles of population size and crossover in genetic algorithms. We summarize recent theoretical results on the disruptive effect of two forms of multi-point crossover: n-point crossover and uniform crossover. We then show empirically that disruption analysis alone is not sufficient for selecting appropriate forms of crossover. However, by taking into account the interacting effects of population size and crossover, a general picture begins to emerge. The implications of these results on implementation issues and performance are discussed, and several directions for further research are suggested.

An Analysis of Multi-Point Crossover

Abstract: In this paper we present some theoretical results on two forms of multi-point crossover: n-point crossover and uniform crossover. This analysis extends the work from De Jong's thesis, which dealt with disruption of n-point crossover on 2nd order hyperplanes. We present various extensions to this theory, including 1) an analysis of the disruption of n-point crossover on kth order hyperplanes; 2) the computation of tighter bounds on the disruption caused by n-point crossover, by handling cases where parents share critical allele values; and 3) an analysis of the disruption caused by uniform crossover on kth order hyperplanes. The implications of these results on implementation issues and performance are discussed, and several directions for further research are suggested.

Comparing genetic operators with gaussian mutations in simulated evolutionary processes using linear systems

Abstract: Evolutionary optimization has been proposed as a method to generate machine learning through automated discovery. Specific genetic operations (e.g. crossover and inversion) have been proposed to mutate the structure that encodes expressed behavior. The efficiency of these operations is evaluated in a series of experiments aimed at solving linear systems of equations. The results indicate that these genetic operators do not compare favorably with more simple random mutation.

A genetic approach to standard cell placement using meta-genetic parameter optimization

Abstract: The genetic algorithm applies transformations on the chromosonal representation of the physical layout. The algorithm works on a set of configurations constituting a constant-size population. The transformations are performed through crossover operators that generate a new configuration assimilating the characteristics of a pair of configurations existing in the current population. Mutation and inversion operators are also used to increase the diversity of the population, and to avoid premature convergence at local optima. Due to the simultaneous optimization of a large population of configurations, there is a logical concurrency in the search of the solution space which makes the genetic algorithm an extremely efficient optimizer. Three efficient crossover techniques are compared, and the algorithm parameters are optimized for the cell-placement problem by using a meta-genetic process. The resulting algorithm was tested against TimberWolf 3.3 on five industrial circuits consisting of 100-800 cells. The results indicate that a placement comparable in quality can be obtained in about the same execution time as TimberWolf, but the genetic algorithm needs to explore 20-50 times fewer configurations than does TimberWolf. >

Representational issues in genetic optimization

Abstract: Functions are partially characterized as easy or hard for genetic algorithms to optimize. The failure modes of inappropriate embedding, crossover disruption, and deceptiveness are introduced, analyzed, and resolved in part. Virtually all optimizable (by any method) real valued functions defined on a finite domain are shown to be theoretically easy for genetic algorithms given appropriately chosen representations. Unfortunately, problems that are easy in theory can be difficult in practice because of sampling error. Also, the transformations required to induce favorable representations are generally arbitrary permutations, and the space of permutations is so large that search for good ones is intractable. The space of inversions is amenable to search, but inversions are insufficiently powerful to overcome deceptiveness. On the other hand, affine transformations (over the diadic group) are shown to be sufficiently powerful to transform at least selected deceptive problems into easy ones. These new ...

Crossover from singular critical to regular classical thermodynamic behavior of fluids

Abstract: A procedure is presented for constructing a thermodynamic free energy for fluids in the critical region that incorporates the crossover from Ising-like singular behavior near the critical point to regular classical behavior far away from the critical point. The procedure is based on an approximation of the solution of the renormalization-group theory of critical phenomena, modified to include effects from a cutoff wave number for the crossover to the classical limit. As an illustration we show how the procedure can be applied to a truncated classical Landau expansion. The results are compared with experimental thermodynamic-property data for carbon dioxide, steam, and ethylene in the critical region.

Constraint-based channel routing for analog and mixed analog/digital circuits

Abstract: A well-defined methodology for mapping the constraints on a set of critical coupling capacitances into constraints in the vertical-constraint (VC) graph of a channel is presented. The approach involves directing undirected edges, adding directed edges, and increasing the weights of edges in the VC graph in order to meet crossover constraints between orthogonal segments and adjacency constraints between parallel segments while attempting to cause minimum increase in the channel height due to the constraints. Use is made of shield nets when necessary. A formal description of the conditions under which the crossover and the adjacency constraints are satisfied is provided and used to construct the appropriate mapping algorithms. The problem of imposing matching constraints on the routing parasitics in a channel with lateral symmetry is addressed. It is observed that perfect matching is not possible for a matched pair of nets with intersecting horizontal spans. A technique to achieve almost perfect mirror symmetry is presented for such pairs of nets. >

Genetic Algorithms Applications to Set Covering and Traveling Salesman Problems

Abstract: For set covering problems, genetic algorithms with two types of crossover operators are investigated in conjunction with three penalty function and two multiobjective formulations A Pareto multiobjective formulation and greedy crossover are suggested to work well On the other hand, for traveling salesman problems, the results appear to be discouraging; genetic algorithm performance hardly exceeds that of a simple swapping rule These results suggest that genetic algorithms have their place in optimization of constrained problems However, lack of, or insufficient use of fundamental building blocks seems to keep the tested genetic algorithm variants from being competitive with specialized search algorithms on ordering problems

An analysis of a reordering operator on a GA-hard problem

Abstract: This paper analyzes the performance of a genetic algorithm that combines reproduction, crossover, and a reordering operator. Reordering operators have often been suggested as one way to avoid thecoding traps -- the combinations of loose linkage and deception among important, lower order schemata -- of fixed codings. The analysis confirms this role and suggests directions for further research.

An all-optical implementation of a 3-D crossover switching network

Abstract: One of the more promising interconnection schemes proposed for use in photonic switching networks is the crossover interconnection network; however, reported implementations of the crossover have been limited in size and complexity. A large-scale cascadable implementation of the optical crossover network that capitalizes on planar symmetric self electrooptic effect device (S-SEED) arrays is discussed. A fully functional experimental prototype with 32 inputs and 32 outputs that was operated at a maximum rate of 55.7 kb/s is also discussed. It is also shown that S-SEED arrays can be operated as simple two-input two-output nodes (called 2-modules) within a controllable network. >

Parallel Genetic Packing of Rectangles

Abstract: A parallel, problem-specific genetic algorithm to compute a certain optimization problem, the two-dimensional Bin Packing Problem, is presented. The algorithm includes a new graph-theoretical model to encode the problem and a problem specific mutation and crossover operator. Experimental results indicate that the algorithm is able to solve large Bin Packing Problems in reasonable time and that smaller instances are likely to be solved optimally.

Partitioning a Graph with a Parallel Genetic Algorithm

Abstract: We present a parallel genetic algorithm for the k way graph partitioning problem. The algorithm uses selection in local neighborhood and sophisticated genetic operators. For a sample problem the algorithm has found better solutions than those found by recent GPP algorithms. The success of the parallel genetic algorithm depends on the representation, a suitable crossover operator and an efficient local hill climbing method which is used to restrict the solution space.

Schema survival rates and heuristic search in genetic algorithms

Abstract: Genetic algorithms are a relatively new paradigm for search in artificial intelligence. It is shown that, for certain kinds of search problems, called permutation problems, the ordinary rule for intermixing the genes between two organisms leads to longer search chains than are necessary. A schema is a partially completed organism. Its order is the number of fixed components and its length is the distance between its first and last fixed component. A scheme is compact if its length and order are nearly equal. It is shown that the survival rate of a compact schema is directly proportional to the quality of the solution after a fixed number of iterations. The ordinary gene intermixing method called a crossover rule, separates the parents of a new organism at almost the precise point at which the compact scheme survival rate is at a minimum. A variation of the crossover rule is proposed that takes advantage of the knowledge of survival rates on the quality of the solution. >

Altimeter crossover methods for precision orbit determination and the mapping of geophysical parameters

Abstract: Accurate orbit determination and the recovery of geophysical parameters are presently attempted via methodologies which use differenced height measurements at the points where the ground tracks of the altimetric satellite orbits intersect. Such 'crossover measurements' could significantly improve the earth's gravity field model. Attention is given to a novel technique employing crossover measurements from two satellites carrying altimeter instruments; this method can observe zonal harmonics of the earth's geopotential which are weakly observed through single-satellite crossovers. This dual-satellite crossover technique will be applicable to data from such future oceanographic satellites as ERS-1.

First-order and continuous transitions in confined liquid crystals

Abstract: We propose a mechanism for the crossover between first-order and continuous transitions in confined liquid crystals that is based on a dimensional crossover of both the space and the order-parameter variables. We estimate the relevant parameters by carrying out explicit mean-field calculations of the global phase diagram of an appropriate lattice model. We discuss in some detail the effects on the phase diagram of the fluctuations neglected by the mean-field approximation.

A simple method for the estimation of interaction bias in crossover studies.

Abstract: The crossover trial is considered the most powerful means of determining the efficacy of new drugs. However this study design is frequently invalidated by treatment-by-period interaction. If, for example, the effect of the first treatment period carries on into the next one, then it influences the response to the latter period (carryover effect). A second problem is that there are no reliable statistical methods to test for this potential bias. This article takes issue with these problems and gives an alternative method for the detection of interaction simply by looking at the data. In a crossover without interaction the second period should be a true reflection of the first. If, however, the data of a treatment are better in the second period than in the first, a carryover effect is probable. If worse, a rebound phenomenon or a negative carryover effect is likely. If both treatments are better or worse, a time effect or some other external influence might be present. The authors illustrate this simple method by a summary of a few selected trials that have been published recently. This method enables not only the detection of interaction but also the differentiation between different types of interactions. Therefore, investigators are advised to use it in order to make sure that there are no unexpected problems.

Underestimation of treatment effect in crossover trials.

Abstract: In crossover trials each subject serves as his own control. For the study of cardiovascular diseases such as hypertension and angina pectoria, properly designed crossover studies are preferred to parallel studies. There is a considerable between-subject variability of symptoms in some of these conditions. Bias due to this is eliminated by the use of a crossover design. However, a problem is the so-called treatment-by-period interaction. The present study analyzes the potential influences of this on the outcome of the trial. Physical carryover effect, defined as a physical effect of the first treatment period carrying on into the second, tends to minimize differences between two consecutive treatment periods. So does the frustrating experience of an inactive agent in the first treatment period. Outside influences such as the change of the seasons may affect lengthy crossover trials in a similar way. The author concludes that the treatment effect in a crossover trial tends to be underestimated. The current concept that reports of clinical trials are generally biased toward an exaggeration of treatment effects does not seem to apply to crossover trials.

Point pattern matching by a genetic algorithm

Abstract: The problem of finding a subset of points in a pattern that best match to a subset of points in another pattern through a transformation in an optimal sense is considered. An exhaustive search to find the best assignment mapping one set of points to another set is, if the number of points that are to be matched is large, computationally expensive. A genetic algorithm that searches for the best ('almost the best') assignment efficiently is described. To map the point pattern matching into the framework of a genetic algorithm, a fitness function that is inversely proportional to the match error and a scheme for encoding an assignment between two sets of points into a string are used, along with a genetic operator known as the mixed-type partial matching crossover. Experimental results have demonstrated the robustness and the fast convergence of the algorithm. The algorithm can be applied to n-dimensional point patterns and any transformation. Results are presented for two-dimensional point patterns and a similarity transformation. >

What determines crossover wavelengths of metameric pairs with three crossovers

Abstract: Two matameric stimuli with identical tristimulus values must have spectral radiance distributions that cross at least three times. Many studies have shown that the crossover locations of three-crossover metamers tend to occur in certain defined regions. This finding has led to hypotheses concerning fundamental aspects of the visual system. In the current article, calculations are reported that prove that crossover locations depend on the spectral properties of the metameric stimuli. For object colors, the spectral properties are determined by colorant obsorption bandwidths. Depending on the absorption bandwidth, crossovers can occur in nearly any region of the visible spectrum. Thus any relationship between crossover wavelengths and properties of the visual system such as maximal responsivities appears coincidental.

Full-wave analysis of a strip crossover

Abstract: A full-wave analysis of a strip crossover above a conducting plane is carried out. Higher-order modes are excited in the form of evanescent waves in the vicinity of the discontinuity, while further away only the dominant (TEM) modes exist. The higher-order mode currents are modeled by triangle functions and the dominant modes by outgoing traveling waves. The method of moments is used to reduce the integral equations on the surface of each strip to matrix equations whose solution determines the currents on each strip. The impedance and scattering matrices of the four-port network and the equivalent circuit were determined. At low frequencies, the equivalent circuit agrees very well with that which was obtained previously using a quasi-static analysis. The two approaches begin to disagree when the cross-sectional dimensions of the crossover become comparable to a tenth of the wavelength. At that point the quasi-static analysis becomes inaccurate, while the full-wave analysis presented here remains valid. >

GASP-a genetic algorithm for standard cell placement

Abstract: This paper describes the implementation of the Genetic Algorithm for Standard-cell Placement, GASP-1 As opposed to simulated annealing, which normally uses pairwise interchange for transforming the layout configuration, in a genetic algorithm, the crossover operator is used to combine two current configurations to generate a new configuration (similar to reproduction in living organisms) The traditional genetic crossover operator, as proposed by Holland, cannot be applied to the cell placement problem without modification, because it occasionally results in illegal placement A great deal of effort has there fore been directed towards finding an efficient crossover operator for this problem domain Three powerful crossover operators have been implemented, and their performance in reducing the interconnect length has been compared The results of this comparison were conclusively in favor of Cycle crossover Besides crossover, two other genetic operators --- mutation and inversion --- have been used to improve the efficiency of the search process In order to benchmark the performance of GASP-1, the best possible compromise of the parameters was picked, and the algorithm was run to place five industrial circuits consisting of 100 to 800 cells The results were very encouraging The total number of configurations examined by GASP-1 was 19 to 50 times less than that for Timber Wolf 33 and the run time was marginally better The percentage improvement in the wire length was better in three out of five circuits The overall conclusion from this research is that adaptive search based on the genetic algorithm yields results comparable to simulated annealing, both in the final result quality and computation time required

The Analysis of Data from Crossover Designs: The Efficiency of Ordinary Least Squares

Abstract: SUMMARY Continuous data from crossover trials are usually analysed using a linear model with independent errors. This might be reasonable for observations on different subjects, but it may be more realistic to assume that the errors within a subject are correlated. If this is so, ordinary least squares (OLS) may be an inefficient method of analysis. How inefficient OLS can become is investigated, assuming errors that follow first-order autoregressive and moving average processes; numerical details are given for some two-treatment designs.

Effects of biodynamic coupling on the human operator model

Abstract: Describing function models of the human operator in manual tracking tasks developed so far, have essentially been restricted to a static cockpit environment using fixed based simulators. This paper addresses the problem whether, and how, the response of the human operator and his associated describing function are influenced by cockpit motion induced by his own control commands. It is suggested, that the motion induced biodynamic stick feedthrough affecting the inner kinesthetic control loop, can be interpreted as a modification of the dynamics of the controlled vehicle. By assuming that the crossover model remains valid under conditions of vehicle motion, an extended analytical model of the human operator describing function is derived. Computer simulation of this analytical model provides reference characteristics of the describing function and remnant noise. A validation of this model, accomplished by extensive dynamical tests on a moving base simulator is described. The excellent match of the analytical and experimental characteristics obtained both in magnitude and shape substantiates the notion of the extended human operator model and suggests that it may contribute to improved overall pilot-aircraft system design.

Factorial designs for crossover clinical trials

Abstract: When measuring the joint effect of two factors it is advantageous to use a factorial design If the application is suitable, efficiency may be further improved by using a crossover design This paper presents a flexible method for amalgamating these two devices Designs are constructed from smaller designs, known as bricks, generated cyclically from tabulated initial sequences The bricks have known efficiencies for estimation of direct treatment main effects and interactions; the efficiencies can be simply combined to approximate the efficiencies of the whole design This allows the user to build a design that is tailored to the particular objectives of the experiment Three and four periods, and two factors with up to four levels are considered

A 3D Crossover Switching Network Based on S-SEED Arrays

Abstract: This paper describes a fully-operational prototype of an optical crossover network that was based on S-SEED arrays. The network provided for 32 input ports and 32 output ports, and it was operated at a maximum channel rate of 55.7 kbps. New node-types (2-modules) and 2D to 3D transformations of crossover networks are also discussed.

On-the-fly arrangement for interconnecting leads and connectors

Abstract: An arrangement is provided to correlate random connections made at one end of a multiwire cable with connections that are to made at the opposite end of the cable, in which the different leads of the cable are usually separated, for example, by a distinctive color pattern. The arrangement includes identifying the respective leads by a distinguishing marking, connecting a first end of the leads to a first connector, sensing the distinguishing marking of the lead connected to each contact of the first connector, and, responsive to the first end distinguishing marking, generating a first order identifying signal. The arrangement also includes identifying the respective leads by a distinguishing marking at a second end of the leads, sensing the distinguishing marking of each lead at the second end of the leads, responsive to the second end distinguishing marking, generating a second order identifying signal, responsive to the first and the second order identifying signals, generating a crossover matrix, which correlates the first and the second ends of the leads, responsive to the crossover matrix, generating a crossover network, and inserting the crossover network in a second connector for establishing connectivity between the first and the second connectors. The arrangement may also include generating the crossover network by selecting a crossover network from a plurality of prefabricated crossover networks or, alternatively, fabricating a crossover network.