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 Subjects -> ENGINEERING (Total: 2054 journals)     - CHEMICAL ENGINEERING (169 journals)    - CIVIL ENGINEERING (160 journals)    - ELECTRICAL ENGINEERING (87 journals)    - ENGINEERING (1142 journals)    - ENGINEERING MECHANICS AND MATERIALS (318 journals)    - HYDRAULIC ENGINEERING (50 journals)    - INDUSTRIAL ENGINEERING (52 journals)    - MECHANICAL ENGINEERING (76 journals) ENGINEERING (1142 journals)            First | 2 3 4 5 6 7 8 9 | Last
 International Journal of Innovation Science       (Followers: 6) International Journal of Integrated Engineering       (Followers: 1) International Journal of Intelligent Engineering Informatics International Journal of Intelligent Systems and Applications in Engineering       (Followers: 1) International Journal of Lifecycle Performance Engineering International Journal of Machine Tools and Manufacture       (Followers: 4) International Journal of Manufacturing Research       (Followers: 5) International Journal of Manufacturing Technology and Management       (Followers: 7) International Journal of Materials and Product Technology       (Followers: 4) International Journal of Mathematical Education in Science and Technology       (Followers: 7) International Journal of Mathematics in Operational Research       (Followers: 1) International Journal of Medical Engineering and Informatics       (Followers: 5) International Journal of Micro Air Vehicles       (Followers: 4) International Journal of Microwave and Wireless Technologies       (Followers: 1) International Journal of Microwave Science and Technology       (Followers: 2) International Journal of Mobile Network Design and Innovation       (Followers: 3) International Journal of Multiphase Flow       (Followers: 2) International Journal of Nanomanufacturing       (Followers: 1) International Journal of Nanoscience       (Followers: 1) International Journal of Nanotechnology       (Followers: 5) International Journal of Nanotechnology and Molecular Computation       (Followers: 3) International Journal of Navigation and Observation       (Followers: 6) International Journal of Network Management International Journal of Nonlinear Sciences and Numerical Simulation International Journal of Numerical Methods for Heat & Fluid Flow       (Followers: 7) International Journal of Optics       (Followers: 1) International Journal of Organisational Design and Engineering       (Followers: 9) International Journal of Pattern Recognition and Artificial Intelligence       (Followers: 6) International Journal of Pavement Engineering       (Followers: 2) International Journal of Physical Modelling in Geotechnics       (Followers: 3) International Journal of Plasticity       (Followers: 6) International Journal of Plastics Technology International Journal of Polymer Analysis and Characterization       (Followers: 5) International Journal of Polymer Science       (Followers: 16) International Journal of Precision Engineering and Manufacturing       (Followers: 5) International Journal of Precision Technology International Journal of Pressure Vessels and Piping       (Followers: 3) International Journal of Production Economics       (Followers: 13) International Journal of Quality and Innovation       (Followers: 4) International Journal of Quality Assurance in Engineering and Technology Education       (Followers: 2) International Journal of Quality Engineering and Technology       (Followers: 2) International Journal of Quantum Information International Journal of Rapid Manufacturing       (Followers: 1) International Journal of Reliability, Quality and Safety Engineering       (Followers: 6) International Journal of Renewable Energy Technology       (Followers: 8) International Journal of Robust and Nonlinear Control       (Followers: 2) International Journal of Science Engineering and Advance Technology International Journal of Sediment Research       (Followers: 1) International Journal of Self-Propagating High-Temperature Synthesis       (Followers: 2) International Journal of Signal and Imaging Systems Engineering International Journal of Six Sigma and Competitive Advantage International Journal of Social Robotics       (Followers: 2) International Journal of Software Engineering and Knowledge Engineering       (Followers: 1) International Journal of Space Science and Engineering       (Followers: 2) International Journal of Speech Technology       (Followers: 4) International Journal of Spray and Combustion Dynamics       (Followers: 6) International Journal of Surface Engineering and Interdisciplinary Materials Science       (Followers: 1) International Journal of Surface Science and Engineering       (Followers: 7) International Journal of Sustainable Engineering       (Followers: 7) International Journal of Sustainable Manufacturing       (Followers: 4) International Journal of Systems and Service-Oriented Engineering International Journal of Systems Assurance Engineering and Management International Journal of Systems, Control and Communications       (Followers: 2) International Journal of Technoethics International Journal of Technology Management and Sustainable Development       (Followers: 1) International Journal of Technology Policy and Law       (Followers: 4) International Journal of Telemedicine and Applications       (Followers: 2) International Journal of Thermal Sciences       (Followers: 7) International Journal of Thermodynamics       (Followers: 2) International Journal of Turbo & Jet-Engines International Journal of Ultra Wideband Communications and Systems International Journal of Vehicle Autonomous Systems       (Followers: 1) International Journal of Vehicle Design       (Followers: 6) International Journal of Vehicle Information and Communication Systems       (Followers: 2) International Journal of Vehicle Noise and Vibration       (Followers: 3) International Journal of Vehicle Safety       (Followers: 5) International Journal of Vehicular Technology       (Followers: 2) International Journal of Virtual Technology and Multimedia       (Followers: 4) International Journal of Wavelets, Multiresolution and Information Processing International Journal on Artificial Intelligence Tools       (Followers: 4) International Nano Letters       (Followers: 9) International Review of Applied Sciences and Engineering Inverse Problems in Science and Engineering       (Followers: 2) Ionics IPTEK The Journal for Technology and Science IRBM News Irrigation and Drainage Systems ISA Transactions       (Followers: 1) ISRN - International Scholarly Research Notices       (Followers: 68) ISRN Nanotechnology ISRN Signal Processing ISRN Thermodynamics IT Professional       (Followers: 3) Journal of Biosensors & Bioelectronics       (Followers: 2) Journal of Advanced Manufacturing Systems       (Followers: 6) Journal of Aerosol Science       (Followers: 1) Journal of Aerospace Engineering       (Followers: 186) Journal of Alloys and Compounds       (Followers: 8) Journal of Analytical and Applied Pyrolysis       (Followers: 3) Journal of Analytical Science & Technology       (Followers: 4)
 Journal of Global Optimization     [SJR: 1.149]   [H-I: 46]    [6 followers]  Follow        Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1573-2916 - ISSN (Online) 0925-5001    Published by Springer-Verlag  [2210 journals]
• Higher-order metric subregularity and its applications
• Abstract: Abstract This paper is devoted to the study of metric subregularity and strong subregularity of any positive order $$q$$ for set-valued mappings in finite and infinite dimensions. While these notions have been studied and applied earlier for $$q=1$$ and—to a much lesser extent—for $$q\in (0,1)$$ , no results are available for the case $$q>1$$ . We derive characterizations of these notions for subgradient mappings, develop their sensitivity analysis under small perturbations, and provide applications to the convergence rate of Newton-type methods for solving generalized equations.
PubDate: 2015-01-29

• Maximizing and minimizing quasiconvex functions: related properties,
existence and optimality conditions via radial epiderivatives
• Abstract: Abstract This paper deals with maximization and minimization of quasiconvex functions in a finite dimensional setting. Firstly, some existence results on closed convex sets, possibly containing lines, are presented. This is given via a careful study of reduction to the boundary and/or extremality of the feasible set. Necessary or sufficient optimality conditions are derived in terms of radial epiderivatives. Then, the problem of minimizing quasiconvex functions are analyzed via asymptotic analysis. Finally, some attempts to define asymptotic functions under quasiconvexity are also outlined. Several examples illustrating the applicability of our results are shown.
PubDate: 2015-01-21

• A new alternating direction method for linearly constrained nonconvex
optimization problems
• Abstract: Abstract In this paper, we study the classical nonconvex linearly constrained optimization problem. Under some mild conditions, we obtain that the penalization sequence is nonincreasing and the sequence generated by our algorithm has finite length. Based on the assumption that the objective functions have Kurdyka–Lojasiewicz property, we prove the convergence of the algorithm. We also show the numerical efficiency of our method by the concrete applications in the areas of image processing and statistics.
PubDate: 2015-01-20

• Analysis of copositive optimization based linear programming bounds on
• Abstract: Abstract The problem of minimizing a quadratic form over the unit simplex, referred to as a standard quadratic optimization problem, admits an exact reformulation as a linear optimization problem over the convex cone of completely positive matrices. This computationally intractable cone can be approximated in various ways from the inside and from the outside by two sequences of nested tractable convex cones of increasing accuracy. In this paper, we focus on the inner polyhedral approximations due to Yıldırım (Optim Methods Softw 27(1):155–173, 2012) and the outer polyhedral approximations due to de Klerk and Pasechnik (SIAM J Optim 12(4):875–892, 2002). We investigate the sequences of upper and lower bounds on the optimal value of a standard quadratic optimization problem arising from these two hierarchies of inner and outer polyhedral approximations. We give complete algebraic descriptions of the sets of instances on which upper and lower bounds are exact at any given finite level of the hierarchy. We identify the structural properties of the sets of instances on which upper and lower bounds converge to the optimal value only in the limit. We present several geometric and topological properties of these sets. Our results shed light on the strengths and limitations of these inner and outer polyhedral approximations in the context of standard quadratic optimization.
PubDate: 2015-01-20

• A polynomial case of convex integer quadratic programming problems with
box integer constraints
• Abstract: Abstract In this paper, we study a special class of convex quadratic integer programming problem with box constraints. By using the decomposition approach, we propose a fixed parameter polynomial time algorithm for such a class of problems. Given a problem with size $$n$$ being the number of decision variables and $$m$$ being the possible integer values of each decision variable, if the $$n-k$$ largest eigenvalues of the quadratic coefficient matrix in the objective function are identical for some $$k$$ $$(0<k<n)$$ , we can construct a solution algorithm with a computational complexity of $${\mathcal {O}}((mn)^k)$$ . To achieve such complexity, we decompose the original problem into several convex quadratic programming problems, where the total number of the subproblems is bounded by the number of cells generated by a set of hyperplane arrangements in $$\mathbb {R}^k$$ space, which can be efficiently identified by cell enumeration algorithm.
PubDate: 2015-01-07

• Existence results for vector equilibrium problems given by a sum of two
functions
• Abstract: Abstract We obtain existence results for the weak vector equilibrium problem where the function involved is a sum of two functions, and the assumptions are required separately on each of these functions. We show that some earlier results of this type contain too demanding assumptions. We relax several of these assumption without loosing the results. The special case of reflexive Banach spaces is also studied, where we make use of the fact that closed balls are weakly compact.
PubDate: 2015-01-03

• Scalarization and pointwise well-posedness for set optimization problems
• Abstract: Abstract In this paper, we consider three kinds of pointwise well-posedness for set optimization problems. We establish some relations among the three kinds of pointwise well-posedness. By virtue of a generalized nonlinear scalarization function, we obtain the equivalence relations between the three kinds of pointwise well-posedness for set optimization problems and the well-posedness of three kinds of scalar optimization problems, respectively.
PubDate: 2015-01-03

• Inverse Max + Sum spanning tree problem by modifying the
sum-cost vector under weighted $$l_\infty$$ l ∞ Norm
• Abstract: Abstract The inverse max + sum spanning tree (IMSST) problem is studied, which is the first inverse problem on optimization problems with combined minmax–minsum objective functions. Given an edge-weighted undirected network $$G(V,E,c,w)$$ , the MSST problem is to find a spanning tree $$T$$ which minimizes the combined weight $$\max _{e\in T}w(e)+\sum _{e\in T}c(e)$$ , which can be solved in $$O(m\log n)$$ time, where $$m:= E$$ and $$n:= V$$ . Whereas, in an IMSST problem, a spanning tree $$T_0$$ of $$G$$ is given, which is not an optimal MSST. A new sum-cost vector $$\bar{c}$$ is to be identified so that $$T_0$$ becomes an optimal MSST of the network $$G(V,E,\bar{c},w)$$ , where $$0\le c-l\le \bar{c} \le c+u$$ and $$l,u\ge 0$$ . The objective is to minimize the cost $$\max _{e\in E}q(e) \bar{c}(e)-c(e)$$ incurred by modifying the sum-cost vector $$c$$ under weighted $$l_\infty$$ norm, where $$q(e)\ge 1$$ . We show that the unbounded IMSST problem is a linear fractional combinatorial optimization (LFCO) problem and develop a discrete type Newton method to solve it. Furthermore, we prove an $$O(m)$$ bound on the number of iterations, although most LFCO problems can be solved in $$O(m^2 \log m)$$ iterations. Therefore, both the unbounded and bounded IMSST problems can be solved by solving $$O(m)$$ MSST problems. Computational results show that the algorithms can efficiently solve the problems.
PubDate: 2015-01-01

• Global optimization by multilevel partition
• Abstract: Abstract Partition-based algorithms, such as the DIRECT algorithm, are popular algorithms for solving global optimization problems. However, these algorithms often have an eventually inefficient behavior due to much more costs requirement to obtain a solution with higher accuracy. In this paper, we present an algorithm framework for bound constrained global optimization problems based on a multilevel partition strategy. This multilevel partition strategy can be regarded as a combination of the basic partition strategy and the multigrid algorithm, which is one of the best algorithms to solve partial differential equation. Our basic idea is to combine the multigrid algorithm with the partition-based algorithm to improve the eventually inefficient behavior of the partition-based algorithm. First, we provide a general framework of the partition-based algorithms which include the DIRECT algorithm as a special case. Then we present a strategy to build the subproblem at the coarse level. This strategy is easy to implement and brings no more computational costs. Under mild conditions, we show that the sequence generated by the proposed global optimization algorithm framework converges to the global optimum. Finally, we employ the original DIRECT algorithm to build a specific global optimization algorithm based on multilevel partition and compare it with the original DIRECT algorithm. Our numerical results show that obtained algorithm improves significantly the eventually inefficient behavior of the original DIRECT algorithm when the required accuracy is high.
PubDate: 2015-01-01

• Truss topology optimization with discrete design variables by outer
approximation
• Abstract: Abstract Several variants of an outer approximation method are proposed to solve truss topology optimization problems with discrete design variables to proven global optimality. The objective is to minimize the volume of the structure while satisfying constraints on the global stiffness of the structure under the applied loads. We extend the natural problem formulation by adding redundant force variables and force equilibrium constraints. This guarantees that the designs suggested by the relaxed master problems are capable of carrying the applied loads, a property which is generally not satisfied for classical outer approximation approaches applied to optimal design problems. A set of two- and three-dimensional benchmark problems are solved and the numerical results suggest that the proposed approaches are competitive with other special-purpose global optimization methods for the considered class of problems. Numerical comparisons indicate that the suggested outer approximation algorithms can outperform standard approaches suggested in the literature, especially on difficult problem instances.
PubDate: 2015-01-01

• Global optimization of generalized semi-infinite programs via restriction
of the right hand side
• Abstract: Abstract The algorithm proposed in Mitsos (Optimization 60(10–11):1291–1308, 2011) for the global optimization of semi-infinite programs is extended to the global optimization of generalized semi-infinite programs. No convexity or concavity assumptions are made. The algorithm employs convergent lower and upper bounds which are based on regular (in general nonconvex) nonlinear programs (NLP) solved by a (black-box) deterministic global NLP solver. The lower bounding procedure is based on a discretization of the lower-level host set; the set is populated with Slater points of the lower-level program that result in constraint violations of prior upper-level points visited by the lower bounding procedure. The purpose of the lower bounding procedure is only to generate a certificate of optimality; in trivial cases it can also generate a global solution point. The upper bounding procedure generates candidate optimal points; it is based on an approximation of the feasible set using a discrete restriction of the lower-level feasible set and a restriction of the right-hand side constraints (both lower and upper level). Under relatively mild assumptions, the algorithm is shown to converge finitely to a truly feasible point which is approximately optimal as established from the lower bound. Test cases from the literature are solved and the algorithm is shown to be computationally efficient.
PubDate: 2015-01-01

• Matrix-power energy-landscape transformation for finding NP-hard
spin-glass ground states
• Abstract: Abstract A method for solving binary optimization problems was proposed by Karandashev and Kryzhanovsky that can be used for finding ground states of spin glass models. By taking a power of the bond matrix the energy landscape of the system is transformed in such a way, that the global minimum should become easier to find. In this paper we test the combination of the new approach with various algorithms, namely simple random search, a cluster algorithm by Houdayer and Martin, and the common approach of parallel tempering. We apply these approaches to find ground states of the three-dimensional Edwards–Anderson model, which is an NP-hard problem, hence computationally challenging. To investigate whether the power-matrix approach is useful for such hard problems, we use previously computed ground states of this model for systems of size $$10^3$$ spins. In particular we try to estimate the difference in needed computation time compared to plain parallel tempering.
PubDate: 2015-01-01

• Analytical characterizations of some classes of optimal strongly
attack-tolerant networks and their Laplacian spectra
• Abstract: Abstract This paper analytically characterizes certain classes of low-diameter strongly attack-tolerant networks of arbitrary size, which are globally optimal in the sense that they contain the minimum possible number of edges. Strong attack tolerance property of level $$R$$ implies that a network preserves connectivity and diameter after the deletion of up to $$R-1$$ network elements (vertices and/or edges). In addition to identifying such optimal network configurations, we explicitly derive their entire Laplacian spectra, that is, all eigenvalues and eigenvectors of the graph Laplacian matrix. Each of these eigenvalues is by itself a solution to a global optimization problem; thus, the results of this study show that these optimization problems yield analytical solutions for the considered classes of networks. As an important special case, we show that the algebraic connectivity (i.e., the second-smallest eigenvalue of the Laplacian) considered as a function on all networks with fixed vertex connectivity $$R$$ reaches its maximum on the optimal $$R$$ -robust 2-club, which has diameter 2 and strong attack tolerance of level $$R$$ . We also demonstrate that the obtained results have direct implications on the exact calculation of convergence speed of consensus algorithms utilizing the entire Laplacian spectrum, which is in contrast to traditionally used simulation-based estimates through just the algebraic connectivity.
PubDate: 2015-01-01

• Solving DC programs using the cutting angle method
• Abstract: Abstract In this paper, we propose a new algorithm for global minimization of functions represented as a difference of two convex functions. The proposed method is a derivative free method and it is designed by adapting the extended cutting angle method. We present preliminary results of numerical experiments using test problems with difference of convex objective functions and box-constraints. We also compare the proposed algorithm with a classical one that uses prismatical subdivisions.
PubDate: 2015-01-01

• A hybrid method without extrapolation step for solving variational
inequality problems
• Abstract: Abstract In this paper, we introduce a new method for solving variational inequality problems with monotone and Lipschitz-continuous mapping in Hilbert space. The iterative process is based on well-known projection method and the hybrid (or outer approximation) method. However we do not use an extrapolation step in the projection method. The absence of one projection in our method is explained by slightly different choice of sets in the hybrid method. We prove a strong convergence of the sequences generated by our method.
PubDate: 2015-01-01

• Pareto-optimal front of cell formation problem in group technology
• Abstract: Abstract The earliest approaches to the cell formation problem in group technology, dealing with a binary machine-part incidence matrix, were aimed only at minimizing the number of intercell moves (exceptional elements in the block-diagonalized matrix). Later on this goal was extended to simultaneous minimization of the numbers of exceptions and voids, and minimization of intercell moves and within-cell load variation, respectively. In this paper we design the first exact branch-and-bound algorithm to create a Pareto-optimal front for the bi-criterion cell formation problem.
PubDate: 2015-01-01

• Efficient random coordinate descent algorithms for large-scale structured
nonconvex optimization
• Abstract: Abstract In this paper we analyze several new methods for solving nonconvex optimization problems with the objective function consisting of a sum of two terms: one is nonconvex and smooth, and another is convex but simple and its structure is known. Further, we consider both cases: unconstrained and linearly constrained nonconvex problems. For optimization problems of the above structure, we propose random coordinate descent algorithms and analyze their convergence properties. For the general case, when the objective function is nonconvex and composite we prove asymptotic convergence for the sequences generated by our algorithms to stationary points and sublinear rate of convergence in expectation for some optimality measure. Additionally, if the objective function satisfies an error bound condition we derive a local linear rate of convergence for the expected values of the objective function. We also present extensive numerical experiments for evaluating the performance of our algorithms in comparison with state-of-the-art methods.
PubDate: 2015-01-01

• Projective dualities for quasiconvex problems
• Abstract: Abstract We study two dualities that can be applied to quasiconvex problems. They are conjugacies deduced from polarities. They are characterized by the polar sets of sublevel sets. We give some calculus rules for the associated subdifferentials and we relate the subdifferentials to known subdifferentials. We adapt the general duality schemes in terms of Lagrangians or in terms of perturbations to two specific problems. First a general mathematical programming problem and then a programming problem with linear constraints.
PubDate: 2014-12-23

• Characterizations of the solution set for quasiconvex programming in terms
of Greenberg–Pierskalla subdifferential
• Abstract: Abstract In convex programming, characterizations of the solution set in terms of the subdifferential have been investigated by Mangasarian. An invariance property of the subdifferential of the objective function is studied, and as a consequence, characterizations of the solution set by any solution point and any point in the relative interior of the solution set are given. In quasiconvex programming, however, characterizations of the solution set by any solution point and an invariance property of Greenberg–Pierskalla subdifferential, which is one of the well known subdifferential for quasiconvex functions, have not been studied yet as far as we know. In this paper, we study characterizations of the solution set for quasiconvex programming in terms of Greenberg–Pierskalla subdifferential. To the purpose, we show an invariance property of Greenberg–Pierskalla subdifferential, and we introduce a necessary and sufficient optimality condition by Greenberg–Pierskalla subdifferential. Also, we compare our results with previous ones. Especially, we prove some of Mangasarian’s characterizations as corollaries of our results.
PubDate: 2014-12-21

• A penalty approach to a discretized double obstacle problem with
derivative constraints
• Abstract: Abstract This work presents a penalty approach to a nonlinear optimization problem with linear box constraints arising from the discretization of an infinite-dimensional differential obstacle problem with bound constraints on derivatives. In this approach, we first propose a penalty equation approximating the mixed nonlinear complementarity problem representing the Karush–Kuhn–Tucker conditions of the optimization problem. We then show that the solution to the penalty equation converges to that of the complementarity problem with an exponential convergence rate depending on the parameters used in the equation. Numerical experiments, carried out on a non-trivial test problem to verify the theoretical finding, show that the computed rates of convergence match the theoretical ones well.
PubDate: 2014-12-19

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