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Genetic Optimization via Diverse Crossover Intelligence

Journal of Applied Mathematics and Physics 2024年第8期12卷 2885-2903页

作者： david webb Eric Sandgren AdvanSix Inc. Parsippany New Jersey USA Systems Engineering Department Donaghey College of Engineering & Information Technology University of Arkansas at Little Rock Little Rock Arkansas USA

An intelligent crossover methodology within the genetic algorithm (GA) is explored within both mathematical and finite element arenas improving both design and solution convergence time. This improved intelligent crossover outperforms the traditional genetic algorithm combined with a rule-based approach utilizing domain specific knowledge developed by webb, et al. [1]. The encoding of the improved crossover consists of two chromosome strings within the genetic algorithm where the first string represents the design or solution string, and the second string represents chromosome crossover string intelligence. This improved crossover methodology saves the best population members or designs evaluated from each generation and applies crossover chromosome intelligence to the best saved population members paired with globally selected parents. Enhanced features of this crossover methodology employ the random selection of the best designs from the prior generation as a potential parent coupled with alternating intelligence pairing methods. In addition to this approach, two globally selected parents possess the ability to mate utilizing crossover chromosome string intelligence maintaining the integrity of a global GA search. Overall, the final population following crossover employs both global and best generation design chromosome strings to maximize creativity while enhancing the solution search. This is a modification to a conventional GA that can be translated into GA encoding. This technique is explored initially through a Base 10 mathematical application followed by the examination of plate structural optimization considering stress and displacement constraints. Results from crossover intelligence are compared with the conventional genetic algorithm and from webb, et al. [1] which illustrates the outcome of a two phase genetic optimization algorithm.

关键词： Crossover Topological Design Structural Optimization Genetic Optimization Variable Material Design

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Research Activities Arising From the University of Kent

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Photonic Sensors 2011年第2期1卷 140-151页

作者： david J. webb Photonics Research Group Aston University Aston Triangle Birmingham B4 7ET UK

In this paper I describe research activities in the field of optical fiber sensing undertaken by me after leaving the Applied Optics Group at the University of Kent. The main topics covered are long period gratings, neural network based signal processing, plasmonic sensors, and polymer fiber gratings. Ⅰ also give a summary of my two periods of research at the University of Kent, covering 1985-1988 and 1991-2001.

关键词： Optical fiber sensor long period grating neural network plasmon polymer POF

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Sustainable Water Resources Management: River Basin Modelling and Decision Support Framework

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Wuhan University Journal of Natural Sciences 2009年第6期14卷 543-551页

作者： RAO Zhengfu POTTER Bob webb david PARKIN Ralph Halcrow Group Ltd Swindon SN4 0QD United Kingdom Halcrow China Ltd Shanghai 200083 China

Sustainability is a key objective of water resources management and this paper describes a modelling and decision support framework that achieves this, illustrated by applications on the UK Thames and Mekong river basins. The decision support framework contains several modules, including an interactive user＇s interface linked to a GIS, a geo-database, knowledge base, simulation models and optimization procedures. Based on the analysis of scenarios and proposed interventions, efficient modelling and optimization tools form a comprehensive integrated decision support framework for the analysis and operational management of water resources in the river basin, our emphasis has been on a practical implementation through careful screening of alternatives, consideration of the institutional framework and direct involvement of stakeholders in the decision making process. Operating in this environment is transparent, reproducible and auditable, securing the trust of all interested parties. This paper discusses its applications to water utilisation on the Mekong river basin and drought management of the Lower Thames stored reservoir system.

关键词： decision support framework sustainable water resources management mathematical modelling optimization

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Sensing Properties of Femtosecond Laser-Inscribed Long Period Gratings in Photonic Crystal Fiber

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Photonic Sensors 2011年第3期1卷 228-233页

作者： Kyriacos KALLI Tom ALLSOP Kaimin ZHOU Graham SMITH Michael KOMODROMOS david webb Ian BENNION Nanophotonics Research Laboratory Department of Electrical Engineering and Information Technology CyprusUniversity of Technology Limassol 3036 Cyprus photonics Research Group Aston University Birmingham B4 7ET United Kingdom Department of Electrical Engineering Frederick University Filokyprou 7 Nicosia Cyprus

The use of near infrared, high intensity femtosecond laser pulses for the inscription of long period fiber gratings in photonic crystal fiber is reported. The formation of grating structures in photonic crystal fiber is complicated by the fiber structure that allows wave-guidance but that impairs and scatters the femtosecond inscription beam. The effects of symmetric and asymmetric femtosecond laser inscriptions are compared and the polarization characteristics of long period gratings and their responses to external perturbations are reported.

关键词： Fiber gratings femtosecond laser inscription photonic crystal fiber

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Structural Design via Genetic Optimization

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Modern Mechanical Engineering 2017年第3期7卷 73-90页

作者： david webb Wissam Alobaidi Eric Sandgren Axalta Coating Systems Front Royal USA Systems Engineering Department Donaghey College of Engineering & Information Technology University of Arkansas at Little Rock Little Rock USA

Structural designs (i.e. truss structures) are derived by the use of a three phase genetic optimization approach, where the minimization of volume is the objective of each truss structure considered. A genetic algorithm is employed which controls the three phase optimization technique. The first phase utilizes the conventional functionality of the genetic algorithm from an evolutionary perspective, however designer interaction by the use of constant rules is provided to ensure an effective evolutionary search outcome. The second phase enhances the best design constructed from phase one by the use of domain specific knowledge in the form of design rules. Phase three improves the final design assembled within phase two by the reduction of truss element areas. This refinement process ensures that the design constraints provided are active, indicating an optimal search solution. All phases operate from a global perspective;however the phase two optimization methodology operates from a more radical approach which encompasses the concept of designing from a “blank sheet of paper” point of view. Results are provided upon the conclusion of each truss example considered which includes the outcomes of each phase for comparison purposes.

关键词： Structural Optimization Genetic Optimization

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Topological Design via a Rule Based Genetic Optimization Algorithm

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American Journal of Computational Mathematics 2017年第3期7卷 291-320页

作者： david webb Qian Liu Wissam Alobaidi Eric Sandgren Axalta Coating Systems Front Royal USA Systems Engineering Department Donaghey College of Engineering & Information Technology University of Arkansas at Little Rock Little Rock USA

A topological structural design approach is presented which is based upon the implementation of a two phase evolutionary optimization algorithm in conjunction with a finite element analysis code. The first phase utilizes a conventional genetic approach which performs a global search for the optimal design topology. Dual level material properties are specified within the genetic encoding and are applied to each individual element in the design mesh to represent either design material or a void. The second phase introduces a rule based refinement which allows for user design intent to accelerate the solution process and eliminate obvious design discrepancies resulting from the phase one search. A series of plate design problems are presented where the objective is to minimize the overall volume of the structure under predefined loading and constraint conditions. The constraints include both stress and deflection considerations where stress is calculated through the use of a commercial finite element package. The initial plate example incorporates a coarse mesh, but a gradual decrease in element size was employed for the remaining cases examined. Replacement of the phase one search with a set of randomly generated designs is demonstrated in order to form a greatly reduced design space which drastically increases the efficiency of the solution process. Comparison results are drawn between the conventional genetic algorithm and the two phase procedure.

关键词： Topological Design Structural Optimization Genetic Optimization Variable Material Design

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Scope and Application of the FIFRA Treated Articles Exemption

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Journal of Transportation Technologies 2020年第1期10卷 16-20页

作者： Lawrence S. Ebner david A. webb Capital Appellate Advocacy PLLC Washington DC USA Creosote Council Valencia PA USA

This paper discusses the U.S. Environmental Agency’s potential improper expansion of its authority under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), the federal pesticide statute, to regulate not only the registration, labeling, and use of wood preservatives, but also treated wood products. EPA’s oversight of wood preservatives under FIFRA is extensive. In recent years, despite EPA’s own Treated Articles Exemption, 40 C.F.R. § 152.25(a), EPA has moved toward utilizing wood preservative labeling in a way that could impose restrictions on the end use of treated wood. Wood preservative registrant and user groups should be concerned and vigilant about this trend toward regulation of treated wood. At the same time, they should continue to interact with EPA in a constructive manner, in part to ensure that EPA respects its own regulatory boundary between wood preservatives, such as creosote, and treated wood, such as creosote-treated railroad crossties, which are a key component of the nation’s transportation critical infrastructure.

关键词： Creosote Wood Preservative Railroad Crossties Treated Wood Registered FIFRA Treated Article Exemption Critical Infrastructure

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A Rule Based Evolutionary Optimization Approach for the Traveling Salesman Problem

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Intelligent Information Management 2017年第4期9卷 115-132页

作者： Wissam M. Alobaidi david J. webb Eric Sandgren Systems Engineering Department Donaghey College of Engineering & Information Technology University of Arkansas at Little Rock Little Rock AR USA Axalta Coating Systems Front Royal VA USA

The traveling salesman problem has long been regarded as a challenging application for existing optimization methods as well as a benchmark application for the development of new optimization methods. As with many existing algorithms, a traditional genetic algorithm will have limited success with this problem class, particularly as the problem size increases. A rule based genetic algorithm is proposed and demonstrated on sets of traveling salesman problems of increasing size. The solution character as well as the solution efficiency is compared against a simulated annealing technique as well as a standard genetic algorithm. The rule based genetic algorithm is shown to provide superior performance for all problem sizes considered. Furthermore, a post optimal analysis provides insight into which rules were successfully applied during the solution process which allows for rule modification to further enhance performance.

关键词： Traveling Salesman Evolutionary Optimization Rule Based Search Heuristic Optimization Hybrid Genetic Algorithm

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Maze Navigation via Genetic Optimization

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Intelligent Information Management 2018年第1期10卷 1-15页

作者： david J. webb Wissam M. Alobaidi Eric Sandgren Axalta Coating Systems Front Royal Virginia USA Systems Engineering Department Donaghey College of Engineering & Information Technology University of Arkansas at Little Rock Little Rock Arkansas USA

One of the most interesting applications of genetic algorithms falls into the area of decision support. Decision support problems involve a series of decisions, each of which is influenced by all decisions made prior to that point. This class of problems occurs often in enterprise management, particularly in the area of scheduling or resource allocation. In order to demonstrate the formulation of this class of problems, a series of maze problems will be presented. The complexity of the mazes is intensified as each new maze is introduced. Two solving scenarios are introduced and comparison results are provided. The first scenario incorporated the traditional genetic algorithm procedure for the intended purpose of acquiring a solution based upon a purely evolutionary approach. The second scenario utilized the genetic algorithm in conjunction with embedded domain specific knowledge in the form of decision rules. The implementation of domain specific knowledge is intended to enhance solution convergence time and improve the overall quality of offspring produced which significantly increases the probability of acquiring a more accurate and consistent solution. Results are provided below for all mazes considered. These results include the traditional genetic algorithm final result and the genetic algorithm optimization approach with embedded rules result. Both results were incorporated for comparison purposes. Overall, the incorporation of domain specific knowledge outperformed the traditional genetic algorithm in both performance and computation time. Specifically, the traditional genetic algorithm failed to adequately find an acceptable solution for each example presented and prematurely converged on average within 54% of their specified generations. Additionally, the most complex maze generated an optimal path directional sequence (i.e. N, S, E, W) via a traditional genetic algorithm which possessed only 50% of the required allowable path sequences for maze completion.

关键词： Maze Navigation Genetic Optimization

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Photonic gas sensors exploiting directly the optical properties of hybrid carbon nanotube localized surface plasmon structures

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Light(Science & Applications) 2016年第1期5卷 624-631页

作者： Thomas Allsop Raz Arif Ron Neal Kyriacos Kalli Vojtěch Kundrát Aleksey Rozhin Phil Culverhouse david J webb Aston Institute of Photonic Technologies School of Engineering and Applied ScienceAston UniversityAston TriangleBirmingham B47ETUK Nanoscience Research Group School of Engineering and Applied ScienceAston UniversityAston TriangleBirmingham B47ETUK Physics Department Faculty of ScienceUniversity of SulaimaniSulaimaniIraq-Kurdistan Region Faculty of Science and Technology School of MathsComputing and RoboticsUniversity of PlymouthPlymouth PL48AAUK Department of Electrical Engineering Computer Engineering and InformaticsCyprus University of TechnologyLimassol 3036Cyprus

Weinvestigate the modification of the optical properties of carbon nanotubes(CNTs)resulting from a chemical reaction triggered by the presence of a specific compound(gaseous carbon dioxide(CO_(2)))and show this mechanism has important consequences for chemical *** have attracted significant research interest because they can be functionalized for a particular chemical,yielding a specific physical response which suggests many potential applications in the fields of nanotechnology and *** far,however,utilizing their optical properties for this purpose has proven to be *** demonstrate the use of localized surface plasmons generated on a nanostructured thin film,resembling a large array of nano-wires,to detect changes in the optical properties of the *** selectivity is demonstrated using CO_(2) in gaseous form at room *** demonstrated methodology results additionally in a new,electrically passive,optical sensing configuration that opens up the possibilities of using CNTs as sensors in hazardous/explosive environments.

关键词： carbon nanotubes gas sensors localized surface plasmons optical sensing

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