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Implementation of the design structure matrix method in engineering development projects

Implementing an ANN model optimized by genetic algorithm for estimating cohesion of limestone samples

  • Authors: Khandelwal, Manoj , Marto, Aminaton , Fatemi, Seyed , Ghoroqi, Mahyar , Armaghani, Danial , Singh, Trilok , Tabrizi, Omid
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Engineering with Computers Vol. 34, no. 2 (2018), p. 307-317
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  • Description: Shear strength parameters such as cohesion are the most significant rock parameters which can be utilized for initial design of some geotechnical engineering applications. In this study, evaluation and prediction of rock material cohesion is presented using different approaches i.e., simple and multiple regression, artificial neural network (ANN) and genetic algorithm (GA)-ANN. For this purpose, a database including three model inputs i.e., p-wave velocity, uniaxial compressive strength and Brazilian tensile strength and one output which is cohesion of limestone samples was prepared. A meaningful relationship was found for all of the model inputs with suitable performance capacity for prediction of rock cohesion. Additionally, a high level of accuracy (coefficient of determination, R2 of 0.925) was observed developing multiple regression equation. To obtain higher performance capacity, a series of ANN and GA-ANN models were built. As a result, hybrid GA-ANN network provides higher performance for prediction of rock cohesion compared to ANN technique. GA-ANN model results (R2 = 0.976 and 0.967 for train and test) were better compared to ANN model results (R2 = 0.949 and 0.948 for train and test). Therefore, this technique is introduced as a new one in estimating cohesion of limestone samples. © 2017, Springer-Verlag London Ltd., part of Springer Nature.

Increasing quasiconcave co-radiant functions with applications in mathematical economics

  • Authors: Martinez-Legaz, Juan , Rubinov, Alex , Schaible, Siegfried
  • Date: 2005
  • Type: Text , Journal article
  • Relation: Mathematical Methods of Operations Research Vol. 61, no. 2 (2005), p. 261-280
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  • Description: We study increasing quasiconcave functions which are co-radiant. Such functions have frequently been employed in microeconomic analysis. The study is carried out in the contemporary framework of abstract convexity and abstract concavity. Various properties of these functions are derived. In particular we identify a small "natural" infimal generator of the set of all coradiant quasiconcave increasing functions. We use this generator to examine two duality schemes for these functions: classical duality often used in microeconomic analysis and a more recent duality concept. Some possible applications to the theory of production functions and utility functions are discussed. © Springer-Verlag 2005.
  • Description: C1
  • Description: 2003001423

Internet security applications of Grobner-Shirvov bases

Limited memory discrete gradient bundle method for nonsmooth derivative-free optimization

  • Authors: Karmitsa, Napsu , Bagirov, Adil
  • Date: 2012
  • Type: Text , Journal article
  • Relation: Optimization Vol. 61, no. 12 (2012), p. 1491-1509
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  • Description: Typically, practical nonsmooth optimization problems involve functions with hundreds of variables. Moreover, there are many practical problems where the computation of even one subgradient is either a difficult or an impossible task. In such cases derivative-free methods are the better (or only) choice since they do not use explicit computation of subgradients. However, these methods require a large number of function evaluations even for moderately large problems. In this article, we propose an efficient derivative-free limited memory discrete gradient bundle method for nonsmooth, possibly nonconvex optimization. The convergence of the proposed method is proved for locally Lipschitz continuous functions and the numerical experiments to be presented confirm the usability of the method especially for medium size and large-scale problems. © 2012 Copyright Taylor and Francis Group, LLC.
  • Description: 2003010398

Managing complex engineering projects with design structure matrix methods

  • Authors: Gunawan, Indra
  • Date: 2010
  • Type: Text , Conference proceedings
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  • Description: In this paper, ways of improving planning, execution and management of complex engineering projects using design structure matrix (DSM) methods: path searching, powers of the adjacency matrix, and reachability matrix are presented. This is done by identifying loops or circuits in the project. The application of the DSM methods to minimize loops or circuits is discussed. As a case study, these methods are implemented to reduce design iterations or rework in a complex engineering project. By applying the DSM methods, the project duration can be minimized and hence the total cost of the project is reduced significantly.

Marginal longitudinal semiparametric regression via penalized splines

  • Authors: Ali-Alkadiri, Mohammad , Carroll, R.J. , Wand, M.P.
  • Date: 2011
  • Type: Text , Journal article
  • Relation: Statistics and Probablitity Letters Vol. 80, no. 15-16 (2011), p. 1242-1252
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  • Description: We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

Metric projection onto a closed set : Necessary and sufficient conditions for the global minimum

  • Authors: Mohebi, Hossein , Rubinov, Alex
  • Date: 2006
  • Type: Text , Journal article
  • Relation: Mathematics of Operations Research Vol. 31, no. 1 (2006), p. 124-132
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  • Description: Necessary and sufficient conditions for a local minimum form a well-developed chapter of optimization theory. Determination of such conditions for the global minimum is a challenging problem. Useful conditions are currently known only for a few classes of nonconvex optimization problems. It is important to find different classes of problems for which the required conditions can be obtained. In this paper we examine one of these classes: the minimization of the distance to an arbitrary closed set in a class of ordered normed spaces. We use the structure of the objective function in order to present necessary and sufficient conditions that give a clear understanding of the structure of a global minimizer and can be easily verified for some problems under consideration. © 2006 INFORMS.
  • Description: C1
  • Description: 2003001835

Metric Regularity of the Sum of Multifunctions and Applications

  • Authors: Van Ngai, Huynh , Tron, Nguyen Tron , Thera, Michel
  • Date: 2014
  • Type: Text , Journal article
  • Relation: Journal of Optimization Theory and Applications Vol. 160, no. 2 (2014), p. 355-390
  • Relation: http://purl.org/au-research/grants/arc/DP110102011
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  • Description: The metric regularity of multifunctions plays a crucial role in modern variational analysis and optimization. This property is a key to study the stability of solutions of generalized equations. Many practical problems lead to generalized equations associated to the sum of multifunctions. This paper is devoted to study the metric regularity of the sum of multifunctions. As the sum of closed multifunctions is not necessarily closed, almost all known results in the literature on the metric regularity for one multifunction (which is assumed usually to be closed) fail to imply regularity properties of the sum of multifunctions. To avoid this difficulty, we use an approach based on the metric regularity of so-called epigraphical multifunctions and the theory of error bounds to study the metric regularity of the sum of two multifunctions, as well as some related important properties of variational systems. Firstly, we establish the metric regularity of the sum of a regular multifunction and a pseudo-Lipschitz multifunction with a suitable Lipschitz modulus. These results subsume some recent results by Durea and Strugariu. Secondly, we derive coderivative characterizations of the metric regularity of epigraphical multifunctions associated with the sum of multifunctions. Applications to the study of the behavior of solutions of variational systems are reported. © 2013 Springer Science+Business Media New York.

Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations

  • Authors: Gaudioso, Manlio , Giallombardo, Giovanni , Miglionico, Giovanna , Bagirov, Adil
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Journal of Global Optimization Vol. 71, no. 1 (2018), p. 37-55
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  • Description: We introduce a proximal bundle method for the numerical minimization of a nonsmooth difference-of-convex (DC) function. Exploiting some classic ideas coming from cutting-plane approaches for the convex case, we iteratively build two separate piecewise-affine approximations of the component functions, grouping the corresponding information in two separate bundles. In the bundle of the first component, only information related to points close to the current iterate are maintained, while the second bundle only refers to a global model of the corresponding component function. We combine the two convex piecewise-affine approximations, and generate a DC piecewise-affine model, which can also be seen as the pointwise maximum of several concave piecewise-affine functions. Such a nonconvex model is locally approximated by means of an auxiliary quadratic program, whose solution is used to certify approximate criticality or to generate a descent search-direction, along with a predicted reduction, that is next explored in a line-search setting. To improve the approximation properties at points that are far from the current iterate a supplementary quadratic program is also introduced to generate an alternative more promising search-direction. We discuss the main convergence issues of the line-search based proximal bundle method, and provide computational results on a set of academic benchmark test problems. © 2017, Springer Science+Business Media, LLC.

Mixed finite element solutions to contact problems of nonlinear Gao beam on elastic foundation

  • Authors: Gao, David , Machalova, Jitka , Netuka, Horymir
  • Date: 2015
  • Type: Text , Journal article
  • Relation: Nonlinear Analysis: Real World Applications Vol. 22, no. (2015), p. 537-550
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  • Description: This paper analyzes nonlinear contact problems of a large deformed beam on an elastic foundation. The beam model is governed by a nonlinear fourth-order differential equation developed by Gao (1996); while the elastic foundation model is assumed as Winkler's type. Based on a decomposition method, the nonlinear variational inequality problem is able to be reformed as a min-max problem of a saddle Lagrangian. Therefore, by using mixed finite element method with independent discretization-interpolations for foundation and beam elements, the nonlinear contact problem in continuous space is eventually converted as a nonlinear mixed complementarity problem, which can be solved by combination of interior-point and Newton methods. Applications are illustrated by different boundary conditions. Results show that the nonlinear Gao beam is more stiffer than the Euler-Bernoulli beam.

New Farkas-type results for vector-valued functions : A non-abstract approach

  • Authors: Dinh, Nguyen , Goberna, Miguel , Long, Dang , Lopez-Cerda, Marco
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Journal of Optimization Theory and Applications Vol. 182, no. 1 (2019), p. 4-29
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  • Description: This paper provides new Farkas-type results characterizing the inclusion of a given set, called contained set, into a second given set, called container set, both of them are subsets of some locally convex space, called decision space. The contained and the container sets are described here by means of vector functions from the decision space to other two locally convex spaces which are equipped with the partial ordering associated with given convex cones. These new Farkas lemmas are obtained via the complete characterization of the conic epigraphs of certain conjugate mappings which constitute the core of our approach. In contrast with a previous paper of three of the authors (Dinh et al. in J Optim Theory Appl 173:357-390, 2017), the aimed characterizations of the containment are expressed here in terms of the data.

New largest known graphs of diameter 6

Nonlinear metric subregularity

  • Authors: Kruger, Alexander
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Journal of Optimization Theory and Applications Vol. 171, no. 3 (2016), p. 820-855
  • Relation: http://purl.org/au-research/grants/arc/DP110102011
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  • Description: In this article, we investigate nonlinear metric subregularity properties of set-valued mappings between general metric or Banach spaces. We demonstrate that these properties can be treated in the framework of the theory of (linear) error bounds for extended real-valued functions of two variables developed in Kruger (Error bounds and metric subregularity. Optimization 64(1):49-79, 2015). Several primal and dual space local quantitative and qualitative criteria of nonlinear metric subregularity are formulated. The relationships between the criteria are established and illustrated.

Nonsmooth DC programming approach to clusterwise linear regression : Optimality conditions and algorithms

  • Authors: Bagirov, Adil , Ugon, Julien
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Optimization Methods and Software Vol. 33, no. 1 (2018), p. 194-219
  • Relation: http://purl.org/au-research/grants/arc/DP140103213
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  • Description: The clusterwise linear regression problem is formulated as a nonsmooth nonconvex optimization problem using the squared regression error function. The objective function in this problem is represented as a difference of convex functions. Optimality conditions are derived, and an algorithm is designed based on such a representation. An incremental approach is proposed to generate starting solutions. The algorithm is tested on small to large data sets. © 2017 Informa UK Limited, trading as Taylor & Francis Group.

Nonsmooth DC programming approach to clusterwise linear regression : Optimality conditions and algorithms

  • Authors: Bagirov, Adil , Ugon, Julien
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Optimization Methods and Software Vol. 33, no. 1 (2018), p. 194-219
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  • Description: The clusterwise linear regression problem is formulated as a nonsmooth nonconvex optimization problem using the squared regression error function. The objective function in this problem is represented as a difference of convex functions. Optimality conditions are derived, and an algorithm is designed based on such a representation. An incremental approach is proposed to generate starting solutions. The algorithm is tested on small to large data sets.

Nonsmooth Lyapunov pairs for differential inclusions governed by operators with nonempty interior domain

  • Authors: Adly, Samir , Hantoute, Abderrahim , Thera, Michel
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Mathematical Programming Vol. 157, no. 2 (2016), p. 349-374
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  • Description: The general theory of Lyapunov stability of first-order differential inclusions in Hilbert spaces has been studied by the authors in the previous paper (Adly et al. in Nonlinear Anal 75(3): 985–1008, 2012). This new contribution focuses on the case when the interior of the domain of the maximally monotone operator governing the given differential inclusion is nonempty; this includes in a natural way the finite-dimensional case. The current setting leads to simplified, more explicit criteria and permits some flexibility in the choice of the generalized subdifferentials. Some consequences of the viability of closed sets are given. Our analysis makes use of standard tools from convex and variational analysis. © 2015, Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society.

Nonsmooth Lyapunov pairs for infinite-dimensional first-order differential inclusions

  • Authors: Adly, Samir , Hantoute, Abderrahim , Théra, Michel
  • Date: 2012
  • Type: Text , Journal article
  • Relation: Nonlinear Analysis: Theory, Methods & Applications Vol. 75, no. 3 (February, 2012), p. 985-1008
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  • Description: The main objective of this paper is to provide new explicit criteria to characterize weak lower semicontinuous Lyapunov pairs or functions associated to first-order differential inclusions in Hilbert spaces. These inclusions are governed by a Lipschitzian perturbation of a maximally monotone operator. The dual criteria we give are expressed by means of the proximal and basic subdifferentials of the nominal functions while primal conditions are described in terms of the contingent directional derivative. We also propose a unifying review of many other criteria given in the literature. Our approach is based on advanced tools of variational analysis and generalized differentiation.

Nonsmooth optimization algorithm for solving clusterwise linear regression problems

  • Authors: Bagirov, Adil , Ugon, Julien , Mirzayeva, Hijran
  • Date: 2015
  • Type: Text , Journal article
  • Relation: Journal of Optimization Theory and Applications Vol. 164, no. 3 (2015), p. 755-780
  • Relation: http://purl.org/au-research/grants/arc/DP140103213
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  • Description: Clusterwise linear regression consists of finding a number of linear regression functions each approximating a subset of the data. In this paper, the clusterwise linear regression problem is formulated as a nonsmooth nonconvex optimization problem and an algorithm based on an incremental approach and on the discrete gradient method of nonsmooth optimization is designed to solve it. This algorithm incrementally divides the whole dataset into groups which can be easily approximated by one linear regression function. A special procedure is introduced to generate good starting points for solving global optimization problems at each iteration of the incremental algorithm. The algorithm is compared with the multi-start Spath and the incremental algorithms on several publicly available datasets for regression analysis.

Numerical investigation of the meshless radial basis integral equation method for solving 2D anisotropic potential problems

  • Authors: Ooi, Ean Hin , Ooi, Ean Tat , Ang, Whye Teong
  • Date: 2015
  • Type: Text , Journal article
  • Relation: Engineering Analysis with Boundary Elements Vol. 53, no. (2015), p. 27-39
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  • Description: The radial basis integral equation (RBIE) method is derived for the first time to solve potential problems involving material anisotropy. The coefficients of the anisotropic conductivity require the gradient term to be modified accordingly when deriving the boundary integral equation so that the flux expression can be properly accounted. Analyses of the behavior of the anisotropic fundamental solution and its spatial gradients showed that their variations along the subdomain boundaries may be large and they increase as the diagonal components of the material anisotropy become larger. The accuracy of the anisotropic RBIE was found to depend primarily on the accuracy of the influence coefficients evaluations and this precedes the number of nodes used. Root mean squared errors of less than 10(-4)% can be obtained if evaluations of the influence coefficients are sufficiently accurate. An alternative formulation of the anisotropic RBIE was derived. The levels of accuracy obtained were not significantly different from the standard formulation. (C) 2014 Elsevier Ltd. All rights reserved.