Genetic algorithms and their use in Geophysical Problems

Parker, Paul Bradley

doi:10.2172/8770

Cited by 14 publications

(20 citation statements)

References 17 publications

(33 reference statements)

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“…These random process, also known as heuristic methods, simulate natural phenomena algorithmically, such as simulated annealing, ant colony optimization, and genetic algorithm. The latter method starts from a random population and progressively modifies the set of estimates by simulating the evolutionary behavior of biological systems, until an acceptable result is achieved (Goldberg and Holland, 1988;Parker, 1999). These algorithms have low dependence on prior parameters, have no matrix operations, and need no information about the curvature of goal functions.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

et al. 2015

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We developed a new strategy, based on graph theory concepts, to invert gravity data using an ensemble of simple point masses. Our method consisted of a genetic algorithm with elitism to generate a set of possible solutions. Each estimate was associated to a graph to solve the minimum spanning tree (MST) problem. To produce unique and stable estimates, we restricted the position of the point masses by minimizing the statistical variance of the distances of an MST jointly with the data-misfit function during the iterations of the genetic algorithm. Hence, the 3D spatial distribution of the point masses identified the skeleton of homogeneous gravity sources. In addition, our method also gave an estimation of the anomalous mass of the source. So, together with the anomalous mass, the skeleton could aid other 3D methods with promising geometric a priori parameters. Several tests with different values of regularizing parameter were made to bespeak this new regularizing strategy. The inversion results applied to noise-corrupted synthetic gravity data revealed that, regardless of promising starting models, the estimated distribution of point masses and the anomalous mass offered valuable information about the homogeneous sources in the subsurface. Tests on real data from a portion of Quadrilátero Ferrífero, Minas Gerais state, Brazil, were performed for complementary analysis of the proposed inversion method.

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Section: Introductionmentioning

confidence: 99%

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

et al. 2015

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“…The population size, crossover rate, and mutation rate are problem dependent and may be varied according to the performance of the genetic algorithm. Numerical experiments by other authors (Goldberg, 1989;Shi, 1992;Parker, 1999) suggest that, for best results, the population size should be between 32 and 128, the crossover rate between 0.8 and 1, and the mutation rate between 0.001 and 0.02.…”

Section: Inverse Modeling With Parallel Genetic Algorithmmentioning

confidence: 99%

“…These models are evaluated according to a set of given constraints and are allowed to evolve by the principle of natural selection through many generations. The method is robust and effective in finding optimal models that satisfy the given constraints, and it provides a global search in the model space for all acceptable models (Goldberg and Richardson, 1987;Goldberg, 1989;Shi, 1992;B. P. Parker, 1999).…”

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confidence: 99%

Three‐dimensional crustal structure in central Taiwan from gravity inversion with a parallel genetic algorithm

et al. 2004

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The genetic algorithm method is combined with the finite‐element method for the first time as an alternative method to invert gravity anomaly data for reconstructing the 3D density structure in the subsurface. The method provides a global search in the model space for all acceptable models. The computational efficiency is significantly improved by storing the coefficient matrix and using it in all forward calculations, then by dividing the region of interest into many subregions and applying parallel processing to the subregions. Central Taiwan, a geologically complex region, is used as an example to demonstrate the utility of the method. A crustal block 120 × 150 km2 in area and 34 km in thickness is represented by a finite‐element model of 76 500 cubic elements, each 2 × 2 × 2 km3 in size. An initial density model is reconstructed from the regional 3D tomographic seismic velocity using an empirical relation between velocity and density. The difference between the calculated and the observed gravity anomaly (i.e., the residual anomaly) shows an elongated minimum of large magnitude that extends along the axis of the Taiwan mountain belt. Among the interpretive models tested, the best model shows a crustal root extending to depths of 50 to 60 km beneath the axis of the Western Central and Eastern Central Ranges with a density contrast of 400 or 500 kg/m3 across the Moho. Both predictions appear to be supported by independent seismological and laboratory evidence.

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“…We adopt roulette wheel selection [13,14] method to select individuals to process crossover and mutation in this paper. The best individual in the generation is protected from crossover and mutation.…”

Section: Selection Operatormentioning

confidence: 99%

A batch splitting job shop scheduling problem with bounded batch sizes under multiple-resource constraints using genetic algorithm

Wang

Zhao

et al. 2008

2008 IEEE Conference on Cybernetics and Intelligent Systems

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Considering alternative resources for operations, requirement of multiple resources to process an operation and a job's batch size greater than one in the real manufacturing environment, a study is made on the batch splitting scheduling problem with bounded batch sizes under multiple-resource constraints, based on the objective to minimize the maximum completion time. A genetic algorithm which is suitable for this problem is proposed, with a new chromosome representation, which takes into account the batch splitting of the original batches of jobs. And a new crossover method and a new mutation method are proposed based on the new chromosome representation. The results of the simulation indicate that the method is feasible and efficient.

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Genetic algorithms and their use in Geophysical Problems

Cited by 14 publications

References 17 publications

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

Three‐dimensional crustal structure in central Taiwan from gravity inversion with a parallel genetic algorithm

A batch splitting job shop scheduling problem with bounded batch sizes under multiple-resource constraints using genetic algorithm

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