The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Kang Hao Cheong - One of the best experts on this subject based on the ideXlab platform.

Li Jiao - One of the best experts on this subject based on the ideXlab platform.

  • an adaptive Fitness Function based on branch hardness for search based testing
    Genetic and Evolutionary Computation Conference, 2017
    Co-Authors: Xiong Xu, Li Jiao
    Abstract:

    Search based software testing has received great attention as a means of automating the test data generation, and the goal is to improve various criteria. There are different types of coverage criteria. In this paper, we deal with the path coverage. Concretely, we focus on the path that is the most difficult to cover. One major limitation of search based testing is the inefficient and insufficiently informed Fitness Function. To address this problem, we propose an adaptive Fitness Function based on branch hardness. The branch hardness is measured by the expected number of visits of each branch in the program, which is modeled by an absorbing discrete time Markov chain. By tuning the parameters of branch hardness heuristically, the search hardness, evaluated by the variation coefficient of the Fitness Function, of generating test data can be minimized. Therefore, this new Fitness Function is more flexible than the traditional counterparts. In addition, we point out that the present definition of branch distance and the use of normalizing Functions are problematic, and propose some improvements. Finally, the empirical study reveals the promising result of our proposal in this paper.

Michael Meyer - One of the best experts on this subject based on the ideXlab platform.

  • design of industrial axial compressor blade sections for optimal range and performance
    Journal of Turbomachinery-transactions of The Asme, 2004
    Co-Authors: Frank Sieverding, Beat Ribi, Michael Casey, Michael Meyer
    Abstract:

    Background: The blade sections of industrial axial flow compressors require a wider range from surge to choke than typical gas turbine compressors in order to meet the high volume flow range requirements of the plant in which they operate. While in the past conventional blade profiles (NACA65 or C4 profiles) at moderate Mach number have mostly been used, recent well-documented experience in axial compressor design for gas turbines suggests that peak efficiency improvements and considerable enlargement of volume flow range can be achieved by the use of so-called prescribed velocity distribution (PVD) or controlled diffusion (CD) airfoils. Method of approach: The method combines a parametric geometry definition method, a powerful blade-to-blade flow solver and an optimization technique (breeder genetic algorithm) with an appropriate Fitness Function. Particular effort has been devoted to the design of the Fitness Function for this application which includes non-dimensional terms related to the required performance at design and off-design operating points. It has been found that essential aspects of the design (such as the required flow turning, or mechanical constraints) should not be part of the Fitness Function, but need to be treated as so-called killer criteria in the genetic algorithm. Finally, it has been found worthwhile to examine the effect of the weighting factors of the Fitness Function to identify how these affect the performance of the sections. Results: The system has been tested on the design of a repeating stage for the middle stages of an industrial axial compressor. The resulting profiles show an increased operating range compared to an earlier design using NACA65 profiles. Conclusions: A design system for the blade sections of industrial axial compressors has been developed. Three-dimensional CFD simulations and experimental measurements demonstrate the effectiveness of the new profiles with respect to the operating range.

  • design of industrial axial compressor blade sections for optimal range and performance
    ASME Turbo Expo 2003 collocated with the 2003 International Joint Power Generation Conference, 2003
    Co-Authors: Frank Sieverding, Beat Ribi, Michael Casey, Michael Meyer
    Abstract:

    A design system for the blade sections of industrial axial compressors has been developed. The method combines a parametric geometry definition method, a powerful blade-to-blade flow solver (MISES) and an optimization technique (breeder genetic algorithm) with an appropriate Fitness Function. Particular effort has been devoted to the design of the Fitness Function for this application which includes non-dimensional terms related to the required performance at design and off-design operating points. It has been found that essential aspects of the design (such as the required flow turning, or mechanical constraints) should not be part of the Fitness Function, but need to be treated as so-called “killer” criteria in the genetic algorithm. Finally, it has been found worthwhile to examine the effect of the weighting factors of the Fitness Function to identify how these affect the performance of the sections. The system has been tested on the design of a repeating stage for the middle stages of an industrial axial compressor. The resulting profiles show an increased operating range compared to an earlier design using NACA65 profiles.Copyright © 2003 by ASME

Xin Yao - One of the best experts on this subject based on the ideXlab platform.

  • analysis of evolutionary algorithms on Fitness Function with time linkage property
    IEEE Transactions on Evolutionary Computation, 2021
    Co-Authors: Weijie Zheng, Huanhuan Chen, Xin Yao
    Abstract:

    In real-world applications, many optimization problems have the time-linkage property, that is, the objective Function value relies on the current solution as well as the historical solutions. Although the rigorous theoretical analysis on evolutionary algorithms (EAs) has rapidly developed in recent two decades, it remains an open problem to theoretically understand the behaviors of EAs on time-linkage problems. This article takes the first step to rigorously analyze EAs for time-linkage Functions. Based on the basic OneMax Function, we propose a time-linkage Function where the first bit value of the last time step is integrated but has a different preference from the current first bit. We prove that with probability $1-o(1)$ , randomized local search and (1 + 1) EA cannot find the optimum, and with probability $1-o(1)$ , $(\mu +1)$ EA is able to reach the optimum.

  • analysis of evolutionary algorithms on Fitness Function with time linkage property
    arXiv: Neural and Evolutionary Computing, 2020
    Co-Authors: Weijie Zheng, Huanhuan Chen, Xin Yao
    Abstract:

    In real-world applications, many optimization problems have the time-linkage property, that is, the objective Function value relies on the current solution as well as the historical solutions. Although the rigorous theoretical analysis on evolutionary algorithms has rapidly developed in recent two decades, it remains an open problem to theoretically understand the behaviors of evolutionary algorithms on time-linkage problems. This paper takes the first step to rigorously analyze evolutionary algorithms for time-linkage Functions. Based on the basic OneMax Function, we propose a time-linkage Function where the first bit value of the last time step is integrated but has a different preference from the current first bit. We prove that with probability $1-o(1)$, randomized local search and $(1+1)$ EA cannot find the optimum, and with probability $1-o(1)$, $(\mu+1)$ EA is able to reach the optimum.

David B Saakian - One of the best experts on this subject based on the ideXlab platform.

  • solution of the crow kimura model with a periodically changing two season Fitness Function
    Physical Review E, 2019
    Co-Authors: David B Saakian, Kang Hao Cheong
    Abstract:

    Since the origin of life, both evolutionary dynamics and rhythms have played a key role in the Functioning of living systems. The Crow-Kimura model of periodically changing Fitness Function has been solved exactly, using integral equation with time-ordered exponent. We also found a simple approximate solution for the two-season case. The evolutionary dynamics accompanied by the rhythms provide important insights into the properties of certain biological systems and processes.

  • dynamics of the eigen and the crow kimura models for molecular evolution
    Physical Review E, 2008
    Co-Authors: David B Saakian, Olga Rozanova, Andrei Akmetzhanov
    Abstract:

    We introduce an alternative way to study molecular evolution within well-established Hamilton-Jacobi formalism, showing that for a broad class of Fitness landscapes it is possible to derive dynamics analytically within the 1N accuracy, where N is the genome length. For a smooth and monotonic Fitness Function this approach gives two dynamical phases: smooth dynamics and discontinuous dynamics. The latter phase arises naturally with no explicite singular Fitness Function, counterintuitively. The Hamilton-Jacobi method yields straightforward analytical results for the models that utilize Fitness as a Function of Hamming distance from a reference genome sequence. We also show the way in which this method gives dynamical phase structure for multipeak Fitness.