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 Subjects -> ENGINEERING (Total: 1948 journals)     - CHEMICAL ENGINEERING (149 journals)    - CIVIL ENGINEERING (146 journals)    - ELECTRICAL ENGINEERING (83 journals)    - ENGINEERING (1123 journals)    - ENGINEERING MECHANICS AND MATERIALS (278 journals)    - HYDRAULIC ENGINEERING (43 journals)    - INDUSTRIAL ENGINEERING (53 journals)    - MECHANICAL ENGINEERING (73 journals) ENGINEERING (1123 journals)            First | 2 3 4 5 6 7 8 9 | Last
 International Journal of Integrated Engineering       (1 follower) International Journal of Intelligent Engineering Informatics International Journal of Intelligent Systems and Applications in Engineering       (1 follower) International Journal of Lifecycle Performance Engineering International Journal of Machine Tools and Manufacture       (4 followers) International Journal of Manufacturing Research       (7 followers) International Journal of Manufacturing Technology and Management       (10 followers) International Journal of Materials and Product Technology       (4 followers) International Journal of Mathematical Education in Science and Technology       (6 followers) International Journal of Mathematics in Operational Research       (1 follower) International Journal of Medical Engineering and Informatics       (4 followers) International Journal of Micro Air Vehicles       (2 followers) International Journal of Microwave and Wireless Technologies       (1 follower) 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Journal of Physical Modelling in Geotechnics       (2 followers) International Journal of Plasticity       (6 followers) International Journal of Plastics Technology International Journal of Polymer Analysis and Characterization       (2 followers) International Journal of Polymer Science       (15 followers) International Journal of Precision Engineering and Manufacturing       (8 followers) International Journal of Precision Technology International Journal of Pressure Vessels and Piping       (2 followers) International Journal of Production Economics       (10 followers) International Journal of Quality and Innovation       (2 followers) International Journal of Quality Engineering and Technology       (2 followers) International Journal of Quantum Information International Journal of Rapid Manufacturing       (4 followers) International Journal of Reliability, Quality and Safety Engineering       (4 followers) International Journal of Renewable Energy Technology       (7 followers) International Journal of Robust and Nonlinear Control       (2 followers) International Journal of Science Engineering and Advance Technology International Journal of Sediment Research       (1 follower) International Journal of Self-Propagating High-Temperature Synthesis       (2 followers) International Journal of Signal and Imaging Systems Engineering International Journal of Six Sigma and Competitive Advantage International Journal of Social Robotics       (1 follower) International Journal of Software Engineering and Knowledge Engineering       (1 follower) International Journal of Space Science and Engineering       (2 followers) International Journal of Speech Technology       (2 followers) International Journal of Spray and Combustion Dynamics       (5 followers) International Journal of Surface Engineering and Interdisciplinary Materials Science       (1 follower) International Journal of Surface Science and Engineering       (7 followers) International Journal of 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Aerosol Science       (2 followers) Journal of Aerospace Engineering       (64 followers) Journal of Alloys and Compounds       (6 followers) Journal of Analytical and Applied Pyrolysis       (3 followers) Journal of Analytical Science & Technology       (4 followers) Journal of Analytical Sciences, Methods and Instrumentation       (1 follower) Journal of Applied Analysis Journal of Applied and Industrial Sciences
Journal of Global Optimization    [6 followers]  Follow
Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-2916 - ISSN (Online) 0925-5001
Published by Springer-Verlag  [2185 journals]   [SJR: 1.149]   [H-I: 46]
• Equilibrium problems involving the Lorentz cone
• Abstract: Abstract We study a general equilibrium model formulated as a smooth system of equations coupled with complementarity conditions relative to the $n$ -dimensional Lorentz cone. For the purpose of analysis, as well as for the design of algorithms, we exploit the fact that the Lorentz cone is representable as a cone of squares in a suitable Euclidean Jordan algebra.
PubDate: 2014-02-01

• Minimizing rational functions by exact Jacobian SDP relaxation applicable to finite singularities
• Abstract: Abstract This paper considers the optimization problem of minimizing a rational function. We reformulate this problem as a polynomial optimization problem by the technique of homogenization. These two problems are shown to be equivalent under some generic conditions. The exact Jacobian SDP relaxation method proposed by Nie is used to solve the resulting polynomial optimization problem. We also prove that the assumption of nonsingularity in Nie’s method can be weakened to the finiteness of singularities. Some numerical examples are given in the end.
PubDate: 2014-02-01

• Modified projection method for strongly pseudomonotone variational inequalities
• Abstract: Abstract A modified projection method for strongly pseudomonotone variational inequalities is considered. Strong convergence and error estimates for the sequences generated by this method are studied in two versions of the method: the stepsizes are chosen arbitrarily from a given fixed closed interval and the stepsizes form a non-summable decreasing sequence of positive real numbers. We also propose some interesting examples to analyze the obtained results.
PubDate: 2014-02-01

• Online pricing for bundles of multiple items
• Abstract: Abstract Given a seller with $k$ types of items, $m$ of each, a sequence of users $\{u_1, u_2,\ldots \}$ arrive one by one. Each user is single-minded, i.e., each user is interested only in a particular bundle of items. The seller must set the price and assign some amount of bundles to each user upon his/her arrival. Bundles can be sold fractionally. Each $u_i$ has his/her value function $v_i(\cdot )$ such that $v_i(x)$ is the highest unit price $u_i$ is willing to pay for $x$ bundles. The objective is to maximize the revenue of the seller by setting the price and amount of bundles for each user. In this paper, we first show that a lower bound of the competitive ratio for this problem is $\Omega (\log h+\log k)$ , where $h$ is the highest unit price to be paid among all users. We then give a deterministic online algorithm, Pricing, whose competitive ratio is $O(\sqrt{k}\cdot \log h\log k)$ . When $k=1$ the lower and upper bounds asymptotically match the optimal result $O(\log h)$ .
PubDate: 2014-02-01

• Construction of error-tolerance pooling designs in symplectic spaces
• Abstract: Abstract The paper provides the construction of error-correcting pooling designs with the incidence matrix of two types of subspaces of symplectic spaces over finite fields. As a generalization of Guo et al.’s matrix, we use the general subspaces of type $(m,s)$ to substitute special subspaces of type $(2s,s)$ . If $\nu$ is big enough, we can get the higher degree of error-tolerant property.
PubDate: 2014-02-01

• Generalized second-order contingent epiderivatives in parametric vector optimization problems
• Abstract: Abstract This paper is concerned with generalized second-order contingent epiderivatives of frontier and solution maps in parametric vector optimization problems. Under some mild conditions, we obtain some formulas for computing generalized second-order contingent epiderivatives of frontier and solution maps, respectively. We also give some examples to illustrate the corresponding results.
PubDate: 2014-02-01

• Abstract convexity of topical functions
• Abstract: In this paper, we examine properties of topical (increasing and plus-homogeneous) functions defined on a normed linear space ${X}$ . We also study many results of abstract convexity such as support set, polarity and subdifferential set of these functions. Finally, we give a characterization for topical functions with respect to closed downward sets.
PubDate: 2014-02-01

• Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework
• Abstract: Abstract We review algorithms developed for nonnegative matrix factorization (NMF) and nonnegative tensor factorization (NTF) from a unified view based on the block coordinate descent (BCD) framework. NMF and NTF are low-rank approximation methods for matrices and tensors in which the low-rank factors are constrained to have only nonnegative elements. The nonnegativity constraints have been shown to enable natural interpretations and allow better solutions in numerous applications including text analysis, computer vision, and bioinformatics. However, the computation of NMF and NTF remains challenging and expensive due the constraints. Numerous algorithmic approaches have been proposed to efficiently compute NMF and NTF. The BCD framework in constrained non-linear optimization readily explains the theoretical convergence properties of several efficient NMF and NTF algorithms, which are consistent with experimental observations reported in literature. In addition, we discuss algorithms that do not fit in the BCD framework contrasting them from those based on the BCD framework. With insights acquired from the unified perspective, we also propose efficient algorithms for updating NMF when there is a small change in the reduced dimension or in the data. The effectiveness of the proposed updating algorithms are validated experimentally with synthetic and real-world data sets.
PubDate: 2014-02-01

• High-order moments conservation in thermostatted kinetic models
• Abstract: Abstract Recently the thermostatted kinetic framework has been proposed as mathematical model for studying nonequilibrium complex systems constrained to keep constant the total energy. The time evolution of the distribution function of the system is described by a nonlinear partial integro-differential equation with quadratic type nonlinearity coupled with the Gaussian isokinetic thermostat. This paper is concerned with further developments of this thermostatted framework. Specifically the term related to the Gaussian thermostat is adjusted in order to ensure the conservation of even high-order moments of the distribution function. The derived framework that constitutes a new paradigm for the derivation of specific models in the applied sciences, is analytically investigated. The global in time existence and uniqueness of the solution to the relative Cauchy problem is proved. Existence and moments conservation of stationary solutions are also performed. Suitable applications and research perspectives are outlined in the last section of the paper.
PubDate: 2014-02-01

• Augmented Lagrangians with possible infeasibility and finite termination for global nonlinear programming
• Abstract: Abstract In a recent paper, Birgin, Floudas and Martínez introduced an augmented Lagrangian method for global optimization. In their approach, augmented Lagrangian subproblems are solved using the $\alpha$ BB method and convergence to global minimizers was obtained assuming feasibility of the original problem. In the present research, the algorithm mentioned above will be improved in several crucial aspects. On the one hand, feasibility of the problem will not be required. Possible infeasibility will be detected in finite time by the new algorithms and optimal infeasibility results will be proved. On the other hand, finite termination results that guarantee optimality and/or feasibility up to any required precision will be provided. An adaptive modification in which subproblem tolerances depend on current feasibility and complementarity will also be given. The adaptive algorithm allows the augmented Lagrangian subproblems to be solved without requiring unnecessary potentially high precisions in the intermediate steps of the method, which improves the overall efficiency. Experiments showing how the new algorithms and results are related to practical computations will be given.
PubDate: 2014-02-01

• Existence of augmented Lagrange multipliers for cone constrained optimization problems
• Abstract: Abstract In this paper, by using an augmented Lagrangian approach, we obtain several sufficient conditions for the existence of augmented Lagrange multipliers of a cone constrained optimization problem in Banach spaces, where the corresponding augmenting function is assumed to have a valley at zero. Furthermore, we deal with the relationship of saddle points, augmented Lagrange multipliers, and zero duality gap property between the cone constrained optimization problem and its augmented Lagrangian dual problem.
PubDate: 2014-02-01

• 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: 2014-01-23

• 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: 2014-01-19

• Turning restriction design in traffic networks with a budget constraint
• Abstract: Abstract The restriction (prohibition) of certain turns at intersections is a very common task employed by the managers of urban traffic networks. Surprisingly, this approach has received little attention in the research literature. The turning restriction design problem (TRDP) involves finding a set of turning restrictions at intersections to promote flow in a congested urban traffic network. This article uses a successive linear approximation (SLA) method for identifying approximate solutions to a nonlinear model of the TRDP. It aims to adjust the current turning restriction regime in a given network in order to minimize total user travel cost when route choice is driven by user equilibrium principles. Novel features of the method include the facts that it is based on link capacity-based arc travel costs and there is a budget constraint on the total cost of all turning restriction alterations. It has been tested using standard network examples from the literature. One of the tests utilized a multi-start approach which improved the solutions produced by the SLA method. The method was also employed to identify turning restrictions for an actual medium-sized urban traffic network in Brazil. Computational experience with the proposed method is promising.
PubDate: 2014-01-18

• A branch and bound method for the solution of multiparametric mixed integer linear programming problems
• Abstract: Abstract In this paper, we present a novel algorithm for the solution of multiparametric mixed integer linear programming (mp-MILP) problems that exhibit uncertain objective function coefficients and uncertain entries in the right-hand side constraint vector. The algorithmic procedure employs a branch and bound strategy that involves the solution of a multiparametric linear programming sub-problem at leaf nodes and appropriate comparison procedures to update the tree. McCormick relaxation procedures are employed to overcome the presence of bilinear terms in the model. The algorithm generates an envelope of parametric profiles, containing the optimal solution of the mp-MILP problem. The parameter space is partitioned into polyhedral convex critical regions. Two examples are presented to illustrate the steps of the proposed algorithm.
PubDate: 2014-01-18

• Bound constrained interval global optimization in the COCONUT Environment
• Abstract: Abstract We introduce a new interval global optimization method for solving bound constrained problems. The method originates from a small standalone software and is implemented in the COCONUT Environment, a framework designed for the development of complex algorithms, containing numerous state-of-the-art methods in a common software platform. The original algorithm is enhanced by various new methods implemented in COCONUT, regarding both interval function evaluations (such as first and second order derivatives with backward automatic differentiation, slopes, slopes of derivatives, bicentered forms, evaluations on the Karush–John conditions, etc.) and algorithmic elements (inclusion/exclusion boxes, local search, constraint propagation). This resulted in a substantial performance increase as compared to the original code. During the selection of the best combination of options, we performed comparison tests that gave empirical answers to long-lasting algorithmic questions (such as whether to use interval gradients or use slopes instead), that have never been studied numerically in such detail before. The new algorithm, called coco_gop_ex, was tested against the prestigious BARON software on an extensive set of bound constrained problems. We found that in addition to accepting a wider class of bound constrained problems and providing more output information (by locating all global minimizers), coco_gop_ex is competitive with BARON in terms of the solution success rates (with the exception of a set of nonlinear least squares problems), and it often outperforms BARON in running time. In particular, coco_gop_ex was around 21 % faster on average over the set of problems solved by both software systems.
PubDate: 2014-01-17

• Exclusion regions for optimization problems
• Abstract: Abstract Branch and bound methods for finding all solutions of a global optimization problem in a box frequently have the difficulty that subboxes containing no solution cannot be easily eliminated if they are close to the global minimum. This has the effect that near each global minimum, and in the process of solving the problem also near the currently best found local minimum, many small boxes are created by repeated splitting, whose processing often dominates the total work spent on the global search. This paper discusses the reasons for the occurrence of this so-called cluster effect, and how to reduce the cluster effect by defining exclusion regions around each local minimum found, that are guaranteed to contain no other local minimum and hence can safely be discarded. In addition, we will introduce a method for verifying the existence of a feasible point close to an approximate local minimum. These exclusion regions are constructed using uniqueness tests based on the Krawczyk operator and make use of first, second and third order information on the objective and constraint functions.
PubDate: 2014-01-14

• Inverse Max + Sum spanning tree problem by modifying the sum-cost vector under weighted $l_\infty$ 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: 2014-01-14

• Primal and dual approximation algorithms for convex vector optimization problems
• Abstract: Abstract Two approximation algorithms for solving convex vector optimization problems (CVOPs) are provided. Both algorithms solve the CVOP and its geometric dual problem simultaneously. The first algorithm is an extension of Benson’s outer approximation algorithm, and the second one is a dual variant of it. Both algorithms provide an inner as well as an outer approximation of the (upper and lower) images. Only one scalar convex program has to be solved in each iteration. We allow objective and constraint functions that are not necessarily differentiable, allow solid pointed polyhedral ordering cones, and relate the approximations to an appropriate $\epsilon$ -solution concept. Numerical examples are provided.
PubDate: 2014-01-12

• Journal of Global Optimization Best Paper Award for a paper published in 2012
• PubDate: 2014-01-04

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