Modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques

2010 ◽  
Author(s):  
Jason P. de Villiers ◽  
F. Wilhelm Leuschner ◽  
Ronelle Geldenhuys
Keyword(s):  
Optimization Techniques ◽  
Lens Distortion ◽  
Radial Asymmetry ◽  
Modern Optimization

scholarly journals Preliminary Sailplane Design Using MDO And Multi-Fidelity Analysis

2021 ◽  
Author(s):  
Chris V. Pilcher
Keyword(s):  
Multidisciplinary Design Optimization ◽  
High Performance ◽  
Vortex Lattice ◽  
Optimization Techniques ◽  
Multidisciplinary Design ◽  
Preliminary Design ◽  
Adaptive Meshing ◽  
Analysis Methods ◽  
And Performance ◽  
Modern Optimization

A multidisciplinary design optimization (MDO) strategy for the preliminary design of a sailplane has been developed. The proposed approach applies MDO techniques and multi-fidelity analysis methods which have seen successful use in many aerospace design applications. A customized genetic algorithm (GA) was developed to control the sailplane optimization that included aerodynamics/stability, structures/weights and balance and, performance/airworthiness disciplinary analysis modules. An adaptive meshing routine was developed to allow for accurate modeling of the aero structural couplinginvolved in wing design, which included a finite element method (FEM) structural solver along with a vortex lattice aerodynamics solver. Empirical equations were used to evaluate basic sailplane performance and airworthiness requirements. This research yielded an optimum design that correlated well with an existing high performance sailplane. The results of this thesis suggest that preliminary sailplane design is a well suited application for modern optimization techniques when coupled with, multi-fidelity analysis methods.

The Application of Genetic Algorithms to the Evaluation of Software Reliability

2010 ◽  
pp. 29-49
Author(s):  
Angel Fernando Kuri-Morales
Keyword(s):  
Genetic Algorithms ◽  
Software Reliability ◽  
Optimization Techniques ◽  
Software System ◽  
Adequate Measure ◽  
Practical Tool ◽  
Definition Of ◽  
Modern Optimization ◽  
The Way

The evaluation of software reliability depends on a) The definition of an adequate measure of correctness and b) A practical tool that allows such measurement. Once the proper metric has been defined it is needed to estimate whether a given software system reaches its optimum value or how far away this software is from it. Typically, the choice of a given metric is limited by the ability to optimize it: mathematical considerations traditionally curtail such choice. However, modern optimization techniques (such as Genetic Algorithms [GAs]) do not exhibit the limitations of classical methods and, therefore, do not limit such choice. In this work the authors describe GAs, the typical limitations for measurement of software reliability (MSR) and the way GAs may help to overcome them.

scholarly journals Review of Modern Optimization Techniques

2015 ◽  
Vol V4 (04) ◽  
Author(s):  
Shahbaz Khan ◽  
Mohammad Asjad ◽  
Akhlas Ahmad ◽  
Keyword(s):  
Optimization Techniques ◽  
Modern Optimization

scholarly journals Optimal invasive species surveillance in the real world: practical advances from research

2020 ◽  
Vol 4 (5) ◽  
pp. 513-520 ◽  
Author(s):  
Frank H. Koch ◽  
Denys Yemshanov ◽  
Robert G. Haight ◽  
Chris J.K. MacQuarrie ◽  
Ning Liu ◽  
...  
Keyword(s):  
Invasive Species ◽  
Real World ◽  
Cost Effective ◽  
Optimization Techniques ◽  
Optimal Routing ◽  
Planning Strategy ◽  
Site Access ◽  
Multiple Scenarios ◽  
Relevant Factors ◽  
Modern Optimization

When alien species make incursions into novel environments, early detection through surveillance is critical to minimizing their impacts and preserving the possibility of timely eradication. However, incipient populations can be difficult to detect, and usually, there are limited resources for surveillance or other response activities. Modern optimization techniques enable surveillance planning that accounts for the biology and expected behavior of an invasive species while exploring multiple scenarios to identify the most cost-effective options. Nevertheless, most optimization models omit some real-world limitations faced by practitioners during multi-day surveillance campaigns, such as daily working time constraints, the time and cost to access survey sites and personnel work schedules. Consequently, surveillance managers must rely on their own judgments to handle these logistical details, and default to their experience during implementation. This is sensible, but their decisions may fail to address all relevant factors and may not be cost-effective. A better planning strategy is to determine optimal routing to survey sites while accounting for common daily logistical constraints. Adding site access and other logistical constraints imposes restrictions on the scope and extent of the surveillance effort, yielding costlier but more realistic expectations of the surveillance outcomes than in a theoretical planning case.

scholarly journals Applying the Decision Support System, TRACER, to Forest Road Design

2005 ◽  
Vol 20 (3) ◽  
pp. 184-191 ◽  
Author(s):  
Abdullah E. Akay ◽  
John Sessions
Keyword(s):  
Three Dimensional ◽  
Design Procedure ◽  
Optimization Techniques ◽  
Forest Road ◽  
The Road ◽  
Road Design ◽  
Road Section ◽  
Environmental Requirements ◽  
Alignment Model ◽  
Modern Optimization

Abstract A three-dimensional forest road alignment model, TRACER, was developed to assist a forest road designer with rapid evaluation of alternative road paths. The objective is to design a route with the lowest total cost considering construction, maintenance, and transportation costs, while conforming to design specifications, environmental requirements, and driver safety. The model integrates two optimization techniques: a linear programming for earthwork allocation and a heuristic approach for vertical alignment selection. The model enhances user efficiency through automated horizontal and vertical curve fitting routines, cross-section generation, and cost routines for construction, maintenance, and vehicle use. The average sediment delivered to a stream from the road section is estimated using the method of a GIS-based road erosion/delivery model. It is anticipated that the development of a design procedure incorporating modern graphics capability, hardware, software languages, modern optimization techniques, and environmental considerations will improve the design process for forest roads. West. J. Appl. For. 20(3):184–191.

scholarly journals Investigation of the iCC Framework Performance for Solving Constrained LSGO Problems

Algorithms ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 108
Author(s):  
Alexey Vakhnin ◽  
Evgenii Sopov
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Optimization Techniques ◽  
Objective Functions ◽  
Parameter Adaptation ◽  
New Approach ◽  
Scientific Papers ◽  
Evolution Algorithms ◽  
Low Dimensional ◽  
Modern Optimization

Many modern real-valued optimization tasks use “black-box” (BB) models for evaluating objective functions and they are high-dimensional and constrained. Using common classifications, we can identify them as constrained large-scale global optimization (cLSGO) tasks. Today, the IEEE Congress of Evolutionary Computation provides a special session and several benchmarks for LSGO. At the same time, cLSGO problems are not well studied yet. The majority of modern optimization techniques demonstrate insufficient performance when confronted with cLSGO tasks. The effectiveness of evolution algorithms (EAs) in solving constrained low-dimensional optimization problems has been proven in many scientific papers and studies. Moreover, the cooperative coevolution (CC) framework has been successfully applied for EA used to solve LSGO problems. In this paper, a new approach for solving cLSGO has been proposed. This approach is based on CC and a method that increases the size of groups of variables at the decomposition stage (iCC) when solving cLSGO tasks. A new algorithm has been proposed, which combined the success-history based parameter adaptation for differential evolution (SHADE) optimizer, iCC, and the ε-constrained method (namely ε-iCC-SHADE). We investigated the performance of the ε-iCC-SHADE and compared it with the previously proposed ε-CC-SHADE algorithm on scalable problems from the IEEE CEC 2017 Competition on constrained real-parameter optimization.

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