On the Local Uniqueness of Solutions of Variational Inequalities Under H-Differentiability

In this paper, we give some sufficient conditions for the local uniqueness of solutions to nonsmooth variational inequalities where the underlying functions are H-differentiable and the underlying set is a closed convex set/polyhedral set/box/polyhedral cone. We show how the solution of a linearized variational inequality is related to the solution of the variational inequality. These results extend/unify various similar results proved for C ¹ and locally Lipschitzian variational inequality problems. When specialized to the nonlinear complementarity problem, our results extend/unify those of C ² and C ¹ nonlinear complementarity problems.     

Existence and Limiting Behavior of Trajectories Associated with P0-equations

Given a continuous P₀-function F : Rⁿ Rⁿ, we describe a method of constructing trajectories associated with the P₀-equation F(x) = 0. Various well known equation-based reformulations of the nonlinear complementarity problem and the box variational inequality problem corresponding to a continuous P₀-function lead to P₀-equations. In particular, reformulations via (a) the Fischer function for the NCP, (b) the min function for the NCP, (c) the fixed point map for a BVI, and (d) the normal map for a BVI give raise to P₀-equations when the underlying function is P₀. To generate the trajectories, we perturb the given P₀-function F to a P-function F(x, ); unique solutions of F(x, ) = 0 as varies over an interval in (0, ) then define the trajectory. We prove general results on the existence and limiting behavior of such trajectories. As special cases we study the interior point trajectory, trajectories based on the fixed point map of a BVI, trajectories based on the normal map of a BVI, and a trajectory based on the aggregate function of a vertical nonlinear complementarity problem.     

On Minimizing Some Merit Functions for Nonlinear Complementarity Problems under <Emphasis Type="Italic">H</Emphasis>-Differentiability

In this paper, we describe the H-differentials of some well known NCP functions and their merit functions. We show how, under appropriate conditions on an H-differential of f, minimizing a merit function corresponding to f leads to a solution of the nonlinear complementarity problem. Our results give a unified treatment of such results for C ¹-functions, semismooth-functions, and locally Lipschitzian functions. Illustrations are given to show the usefulness of our results. We present also a result on the global convergence of a derivative-free descent algorithm for solving the nonlinear complementarity problem. The first author is deeply indebted to Professor M. Seetharama Gowda for his numerous helpful suggestions and encouragement. Special thanks to Professor J.-P. Crouzeix and an anonymous referees for their constructive suggestions which led to numerous improvements in the paper. The research of the first author was supported in part by the Natural Sciences and Engineering Research Council of Canada and Scholar Activity Grant of Thompson Rivers University. The research of the second author was supported by the Natural Sciences and Engineering Research Council of Canada.     

A Hybrid grey wolf optimizer and genetic algorithm for minimizing potential energy function

In this paper, we propose a new hybrid algorithm between the grey wolf optimizer algorithm and the genetic algorithm in order to minimize a simplified model of the energy function of the molecule. We call the proposed algorithm by Hybrid Grey Wolf Optimizer and Genetic Algorithm (HGWOGA). We employ three procedures in the HGWOGA. In the first procedure, we apply the grey wolf optimizer algorithm to balance between the exploration and the exploitation process in the proposed algorithm. In the second procedure, we utilize the dimensionality reduction and the population partitioning processes by dividing the population into sub-populations and using the arithmetical crossover operator in each sub-population in order to increase the diversity of the search in the algorithm. In the last procedure, we apply the genetic mutation operator in the whole population in order to refrain from the premature convergence and trapping in local minima. We implement the proposed algorithm with various molecule size with up to 200 dimensions and compare the proposed algorithm with 8 benchmark algorithms in order to validate its efficiency for solving molecular potential energy function. The numerical experiment results show that the proposed algorithm is a promising, competent, and capable of finding the global minimum or near global minimum of the molecular energy function faster than the other comparative algorithms.     

Complementarity problems over a hypermatrix (tensor) set

A hypermatrix (tensor) complementarity problem \(\textit{HMCP}(q,\mathcal {A})\) is to find a vector \(x\in \mathbb {R}^n\) such that \(x\ge 0,~\mathcal {A}x+q\ge 0,~x^T(\mathcal {A}x+q)=0,\) for every \(q\in \mathbb {R}^n\), where \(\mathcal {A}\) is an mth order hypermatrix (tensor) (Song and Qi in J Optim Theory Appl 165(3): 854–873, 2015). Uniqueness, feasibility, and strict feasibility of the solution of a complementarity problem induced by a (compact) set of hypermatrices are characterized in terms of the hypermatrices involved.     

Energy barriers associated with slip–twin interactions

The energetics of slip–coherent twin boundary (CTB) interactions are established under tensile deformation in face centered cubic (fcc) copper with molecular dynamics simulations, exploring the entire stereographic triangle. The CTBs serve as effective barriers in some crystal orientations more than others, consistent with experimental observations. The resulting dislocation structures upon slip–twin reactions are identified in terms of Burgers vector analysis. Visualization of the dislocation transmission, lock formation, dislocation incorporation to twin boundaries, dislocation multiplication at the matrix–twin interface and twin translation, growth, and contraction behaviors cover the most significant reactions that can physically occur providing a deeper understanding of the mechanical behavior of fcc alloys in the presence of twin boundaries. The results make a distinction between deformation and annealing twins interacting with incident dislocations and point to the considerable role both types of twins can play in strengthening of fcc metals.     

Detail review on chemical,physical and green synthesis,classification, characterizations and applications of nanoparticles

ABSTRACT

Nanotechnology is an emerging field of science. The base of nanotechnology is nanoparticles. The size of nanoparticles ranges from 1 to 100?nm. The nanoparticles are classified into different classes such as inorganic nanoparticles, organic nanoparticles, ceramic nanoparticles and carbon base nanoparticles. The inorganic nanoparticles are further classified into metal nanoparticles and metal oxide nanoparticles.similarly carbon base nanoparticles classified into Fullerene, Carbon nanotubes, Graphene, Carbon nanofiber and carbon black Nanoparticles are also classified on the basis of dimension such as one dimension nanoparticles, two-dimension nanoparticles and three-dimension nanoparticles. The nanoparticles are synthesized by using two approaches like top-down approach and bottom-up approach. In this review chemical, physical and green synthesis of nanoparticles is reported. The synthesized nanoparticles are synthesized using different qualitative and quantitative techniques. The Qualitative techniques include Fourier Transform Infrared Spectroscopy (FT-IR), UV-Vis spectrophotometry, Scanning electron microscope (SEM), X.ray diffraction (XRD) and Atomic Force Microscopy (AFM). The Quantitative techniques include Transmission Electron Microscopy (TEM), Annular Dark-Field Imaging (HAADF) and Intracranial pressure (ICP). The nanoparticles have different application which is reported in this review.     

A simplex social spider algorithm for solving integer programming and minimax problems

In this paper, we propose a new hybrid social spider algorithm with simplex Nelder-Mead method in order to solve integer programming and minimax problems. We call the proposed algorithm a Simplex Social Spider optimization (SSSO) algorithm. In the the proposed SSSO algorithm, we combine the social spider algorithm with its powerful capability of performing exploration, exploitation, and the Nelder-Mead method in order to refine the best obtained solution from the standard social spider algorithm. In order to investigate the general performance of the proposed SSSO algorithm, we test it on 7 integer programming problems and 10 minimax problems and compare against 10 algorithms for solving integer programming problems and 9 algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time.