Detection of flaws in composites from scattered elastic-wave field using an improved μGA and a local optimizer

Xu, Yuhong; Liu, G.R

doi:10.1016/s0045-7825(02)00340-7

Cited by 24 publications

(12 citation statements)

References 16 publications

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“…In [21] a multi-objective micro-genetic extreme learning machine (G-ELM) is proposed, which provides the appropriate number of hidden nodes in the machine for solving the problem and minimizes the mean square error (MSE) of the training phase. The micro-GA is applied successfully for many applications such as designing wave-guide slot antenna with dielectric lenses [36], detection of flaws in composites [30], and scheduling of a real-world pipeline network [29], where better performances compared to the standard GA are reported.…”

Section: Outline Of the Thesismentioning

confidence: 99%

Micro-differential evolution: Diversity enhancement and a comparative study

Salehinejad

Rahnamayan

Tizhoosh

2017

Applied Soft Computing

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Section: Outline Of the Thesismentioning

confidence: 99%

Micro-differential evolution: Diversity enhancement and a comparative study

Salehinejad

Rahnamayan

Tizhoosh

2017

Applied Soft Computing

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“…Krishnakumar (1989) showed that MGA can avoid trapping in local optimal solutions and performs better than a simple GA in solving multimodal optimization problems. Several successful applications of MGA have appeared in the literature (e.g., Coello and Pulido 2001;Xu and Liu 2002). The MGA used for this study is written using Visual FORTRAN language.…”

Section: Micro Genetic Algorithm (Mga)mentioning

confidence: 99%

Developing environmental penalty functions for river water quality management: application of evolutionary game theory

2014

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In this paper, a new evolutionary game theoretic methodology is proposed to determine penalty functions that an environmental protection agency should impose on dischargers to achieve water quality standards at monitoring points along the river when the monitoring points are limited. In the proposed methodology, the concept of evolutionary stable strategy in asymmetric matrix games is utilized to model the interactions among dischargers more realistically. A heuristic optimization-simulation model is developed for calculating the evolutionary stable treatment strategies of dischargers considering the mass transport equations, main characteristics of river flow and pollution loads. The proposed methodology is applied to the Zarjub River in the northern part of Iran to illustrate its practical utility. The results show that the proposed approach can determine penalty functions which guarantee that the water quality standards are met. The results of the suggested model are compared with those of a traditional optimization waste load allocation model. The comparisons show that the evolutionary game theory-based model provides stable wastewater treatment strategies which would not be violated by dischargers in practice.

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“…In [74], Xu and Liu make use of a micro-GA combined with a local optimizer, detecting defects in laminated structures using fields of scattered elastic waves. Yang and Soh [75] solve the topology optimization also considering types of discrete cross-sections, for MCW problem using genetic programming.…”

Section: The Early Two-thousandsmentioning

confidence: 99%