Description:
Purpose – One of the significant underlying principles of nanorobotic systems deals with the understanding and conceptualization of their respective complex nanocomponents. This paper introduces a new methodology to compute a set of optimal electronic and mathematical properties of Buckyball nanoparticle using graph algorithms based on dynamic programming and greedy algorithm. Design/methodology/approach – Buckyball, C60, is composed of sixty equivalent carbon atoms arranged as a highly symmetric hollow spherical cage in the form of a soccer ball. At first, Wiener, hyper-Wiener, Harary and reciprocal Wiener indices were computed using dynamic programming and presented them as: W(Buckyball)=11870.4, WW(Buckyball)=52570.9, Ha(Buckyball)=102.2 and RW(Buckyball)=346.9. The polynomials of Buckyball, Hosoya and hyper-Hosoya, which are in relationship with Buckyball's indices, have also been computed. The relationships between Buckyball's indices and polynomials were then computed and demonstrated a good agreement with their mathematical equations. Also, a graph algorithm based on greedy algorithms was used to find some optimal electronic aspects of Buckyball's structure by computing the Minimum Weight Spanning Tree (MWST) of Buckyball. Findings – The computed MWST was indicated that for connecting sixty carbon atoms of Buckyball together: the minimum numbers of double bonds were 30; the minimum numbers of single bonds were 29; and the minimum numbers of electrons were 178. These results also had good agreement with the principles of the authors' used greedy algorithm. Originality/value – This paper has used the graph algorithms for computing the optimal electronic and mathematical properties of BB. It has focused on mathematical properties of BB including Wiener, hyper-Wiener, Harary and reciprocal Wiener indices as well as Hosoya and Hyper-Hosoya polynomials and computerized them with dynamic programming graph algorithms.
Description:
We consider parametric equilibrium problems in metric spaces. Sufficient conditions for the Hölder calmness of solutions are established. We also study the Hölder well-posedness for equilibrium problems in metric spaces.
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We consider parametric equilibrium problems in metric spaces. Sufficient conditions for the Hölder calmness of solutions are established. We also study the Hölder well-posedness for equilibrium problems in metric spaces.
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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.
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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.
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This paper studies stability of error bounds for convex constraints in Banach spaces. We show that certain known sufficient conditions for local and global error bounds actually ensure error bounds for the family of functions being in a sense small perturbations of the given one. A single inequality as well as semi-infinite constraint systems are considered.
Description:
This paper studies stability of error bounds for convex constraints in Banach spaces. We show that certain known sufficient conditions for local and global error bounds actually ensure error bounds for the family of functions being in a sense small perturbations of the given one. A single inequality as well as semi-infinite constraint systems are considered.
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New algorithms for solving unconstrained optimization problems are presented based on the idea of combining two types of descent directions: the direction of anti-gradient and either the Newton or quasi-Newton directions. The use of latter directions allows one to improve the convergence rate. Global and superlinear convergence properties of these algorithms are established. Numerical experiments using some unconstrained test problems are reported. Also, the proposed algorithms are compared with some existing similar methods using results of experiments. This comparison demonstrates the efficiency of the proposed combined methods.
Description:
New algorithms for solving unconstrained optimization problems are presented based on the idea of combining two types of descent directions: the direction of anti-gradient and either the Newton or quasi-Newton directions. The use of latter directions allows one to improve the convergence rate. Global and superlinear convergence properties of these algorithms are established. Numerical experiments using some unconstrained test problems are reported. Also, the proposed algorithms are compared with some existing similar methods using results of experiments. This comparison demonstrates the efficiency of the proposed combined methods.
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In this paper, we study global concave optimization by the canonical dual function. A differential flow on the dual feasible space is introduced. We show that the flow reaches a global minimizer of the concave function over a box. An example is illustrated.
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In this paper, we present a new global optimization method to solve nonlinear systems of equations. We reformulate given system of nonlinear equations as a global optimization problem and then give a new auxiliary function method to solve the reformulated global optimization problem. The new auxiliary function proposed in this paper can be a filled function, a quasifilled function or a strict filled function with appropriately chosen parameters. Several numerical examples are presented to illustrate the effciency of the present approach.
Description:
In this paper, an implementation of lean manufacturing through learning curve modelling for labour forecast is discussed. First, various learning curve models are presented. Then the models are analyzed in terms of their advantages and limitations. As a case study, the learning curve modelling is presented with the data derived from a production company. With the application of the learning curve, labour need can be more accurately predicted and scheduled on time.
Description:
In this paper, an implementation of lean manufacturing through learning curve modelling for labour forecast is discussed. First, various learning curve models are presented. Then the models are analyzed in terms of their advantages and limitations. As a case study, the learning curve modelling is presented with the data derived from a production company. With the application of the learning curve, labour need can be more accurately predicted and scheduled on time.