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  Subjects -> ENGINEERING (Total: 1971 journals)
    - CHEMICAL ENGINEERING (154 journals)
    - CIVIL ENGINEERING (150 journals)
    - ELECTRICAL ENGINEERING (83 journals)
    - ENGINEERING (1117 journals)
    - ENGINEERING MECHANICS AND MATERIALS (294 journals)
    - HYDRAULIC ENGINEERING (46 journals)
    - INDUSTRIAL ENGINEERING (52 journals)
    - MECHANICAL ENGINEERING (75 journals)

ENGINEERING (1117 journals)            First | 2 3 4 5 6 7 8 9 | Last

International Journal of Manufacturing Research     Hybrid Journal   (Followers: 6)
International Journal of Manufacturing Technology and Management     Hybrid Journal   (Followers: 8)
International Journal of Materials and Product Technology     Hybrid Journal   (Followers: 4)
International Journal of Mathematical Education in Science and Technology     Hybrid Journal   (Followers: 7)
International Journal of Mathematics in Operational Research     Hybrid Journal   (Followers: 1)
International Journal of Medical Engineering and Informatics     Hybrid Journal   (Followers: 5)
International Journal of Micro Air Vehicles     Full-text available via subscription   (Followers: 4)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 1)
International Journal of Microwave Science and Technology     Open Access   (Followers: 2)
International Journal of Mobile Network Design and Innovation     Hybrid Journal   (Followers: 3)
International Journal of Multiphase Flow     Hybrid Journal   (Followers: 2)
International Journal of Nanomanufacturing     Hybrid Journal   (Followers: 1)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Nanotechnology     Hybrid Journal   (Followers: 5)
International Journal of Navigation and Observation     Open Access   (Followers: 6)
International Journal of Network Management     Hybrid Journal  
International Journal of Nonlinear Sciences and Numerical Simulation     Full-text available via subscription   (Followers: 1)
International Journal of Numerical Methods for Heat & Fluid Flow     Hybrid Journal   (Followers: 7)
International Journal of Optics     Open Access   (Followers: 1)
International Journal of Organisational Design and Engineering     Hybrid Journal   (Followers: 9)
International Journal of Pattern Recognition and Artificial Intelligence     Hybrid Journal   (Followers: 6)
International Journal of Pavement Engineering     Hybrid Journal   (Followers: 2)
International Journal of Physical Modelling in Geotechnics     Hybrid Journal   (Followers: 3)
International Journal of Plasticity     Hybrid Journal   (Followers: 6)
International Journal of Plastics Technology     Hybrid Journal  
International Journal of Polymer Analysis and Characterization     Hybrid Journal   (Followers: 4)
International Journal of Polymer Science     Open Access   (Followers: 16)
International Journal of Precision Engineering and Manufacturing     Hybrid Journal   (Followers: 6)
International Journal of Precision Technology     Hybrid Journal  
International Journal of Pressure Vessels and Piping     Hybrid Journal   (Followers: 2)
International Journal of Production Economics     Hybrid Journal   (Followers: 10)
International Journal of Quality and Innovation     Hybrid Journal   (Followers: 4)
International Journal of Quality Engineering and Technology     Hybrid Journal   (Followers: 2)
International Journal of Quantum Information     Hybrid Journal  
International Journal of Rapid Manufacturing     Hybrid Journal   (Followers: 2)
International Journal of Reliability, Quality and Safety Engineering     Hybrid Journal   (Followers: 5)
International Journal of Renewable Energy Technology     Hybrid Journal   (Followers: 8)
International Journal of Robust and Nonlinear Control     Hybrid Journal   (Followers: 2)
International Journal of Science Engineering and Advance Technology     Open Access  
International Journal of Sediment Research     Full-text available via subscription   (Followers: 1)
International Journal of Self-Propagating High-Temperature Synthesis     Hybrid Journal   (Followers: 2)
International Journal of Signal and Imaging Systems Engineering     Hybrid Journal  
International Journal of Six Sigma and Competitive Advantage     Hybrid Journal  
International Journal of Social Robotics     Hybrid Journal   (Followers: 1)
International Journal of Software Engineering and Knowledge Engineering     Hybrid Journal   (Followers: 1)
International Journal of Space Science and Engineering     Hybrid Journal   (Followers: 2)
International Journal of Speech Technology     Hybrid Journal   (Followers: 3)
International Journal of Spray and Combustion Dynamics     Full-text available via subscription   (Followers: 6)
International Journal of Surface Engineering and Interdisciplinary Materials Science     Full-text available via subscription   (Followers: 1)
International Journal of Surface Science and Engineering     Hybrid Journal   (Followers: 7)
International Journal of Sustainable Engineering     Hybrid Journal   (Followers: 7)
International Journal of Sustainable Manufacturing     Hybrid Journal   (Followers: 4)
International Journal of Systems Assurance Engineering and Management     Hybrid Journal  
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 2)
International Journal of Technology Management and Sustainable Development     Hybrid Journal   (Followers: 1)
International Journal of Technology Policy and Law     Hybrid Journal   (Followers: 4)
International Journal of Telemedicine and Applications     Open Access   (Followers: 2)
International Journal of Thermal Sciences     Hybrid Journal   (Followers: 5)
International Journal of Thermodynamics     Open Access   (Followers: 2)
International Journal of Turbo & Jet-Engines     Full-text available via subscription  
International Journal of Ultra Wideband Communications and Systems     Hybrid Journal  
International Journal of Vehicle Autonomous Systems     Hybrid Journal   (Followers: 1)
International Journal of Vehicle Design     Hybrid Journal   (Followers: 6)
International Journal of Vehicle Information and Communication Systems     Hybrid Journal   (Followers: 2)
International Journal of Vehicle Noise and Vibration     Hybrid Journal   (Followers: 3)
International Journal of Vehicle Safety     Hybrid Journal   (Followers: 4)
International Journal of Vehicular Technology     Open Access   (Followers: 2)
International Journal of Virtual Technology and Multimedia     Hybrid Journal   (Followers: 4)
International Journal of Wavelets, Multiresolution and Information Processing     Hybrid Journal  
International Journal on Artificial Intelligence Tools     Hybrid Journal   (Followers: 4)
International Nano Letters     Open Access   (Followers: 6)
International Review of Applied Sciences and Engineering     Full-text available via subscription  
Inverse Problems in Science and Engineering     Hybrid Journal   (Followers: 2)
Ionics     Hybrid Journal  
IPTEK The Journal for Technology and Science     Open Access  
IRBM News     Full-text available via subscription  
Irrigation and Drainage Systems     Hybrid Journal  
ISA Transactions     Full-text available via subscription   (Followers: 1)
ISRN - International Scholarly Research Notices     Open Access   (Followers: 69)
ISRN Nanotechnology     Open Access  
ISRN Signal Processing     Open Access  
ISRN Thermodynamics     Open Access  
IT Professional     Full-text available via subscription   (Followers: 3)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 1)
Journal of Advanced Manufacturing Systems     Hybrid Journal   (Followers: 7)
Journal of Aerosol Science     Hybrid Journal   (Followers: 2)
Journal of Aerospace Engineering     Full-text available via subscription   (Followers: 146)
Journal of Alloys and Compounds     Hybrid Journal   (Followers: 7)
Journal of Analytical and Applied Pyrolysis     Hybrid Journal   (Followers: 3)
Journal of Analytical Science & Technology     Open Access   (Followers: 4)
Journal of Analytical Sciences, Methods and Instrumentation     Open Access   (Followers: 1)
Journal of Applied Analysis     Full-text available via subscription  
Journal of Applied and Industrial Sciences     Open Access  
Journal of Applied Logic     Full-text available via subscription  
Journal of Applied Physics     Hybrid Journal   (Followers: 170)
Journal of Applied Probability     Full-text available via subscription   (Followers: 6)
Journal of Applied Research and Technology     Open Access  
Journal of Applied Science and Technology     Full-text available via subscription  
Journal of Applied Sciences     Open Access   (Followers: 5)
Journal of Architectural Engineering     Full-text available via subscription   (Followers: 6)

  First | 2 3 4 5 6 7 8 9 | Last

Journal Cover Journal of Global Optimization
   Journal TOC RSS feeds Export to Zotero [6 followers]  Follow    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
     ISSN (Print) 1573-2916 - ISSN (Online) 0925-5001
     Published by Springer-Verlag Homepage  [2209 journals]   [SJR: 1.149]   [H-I: 46]
  • A modified DIRECT algorithm with bilevel partition
    • Abstract: Abstract It has been pointed out by Jones D. R. that the DIRECT global optimization algorithm can quickly get close to the basin of the optimum but takes longer to achieve a high degree of accuracy. In this paper, we introduce a bilevel strategy into a modifed DIRECT algorithm to overcome this shortcoming. The proposed algorithm is proved to be convergent globally. Numerical results show that the proposed algorithm is very promising.
      PubDate: 2014-11-01
       
  • Branch-and-Sandwich: a deterministic global optimization algorithm for
           optimistic bilevel programming problems. Part II: Convergence analysis and
           numerical results
    • Abstract: Abstract In the first part of this work, we presented a global optimization algorithm, Branch-and-Sandwich, for optimistic bilevel programming problems that satisfy a regularity condition in the inner problem (Kleniati and Adjiman in J Glob Optim, 2014). The proposed approach can be interpreted as the exploration of two solution spaces (corresponding to the inner and the outer problems) using a single branch-and-bound tree, where two pairs of lower and upper bounds are computed: one for the outer optimal objective value and the other for the inner value function. In the present paper, the theoretical properties of the proposed algorithm are investigated and finite \(\varepsilon \) -convergence to a global solution of the bilevel problem is proved. Thirty-four problems from the literature are tackled successfully.
      PubDate: 2014-11-01
       
  • Handelman’s hierarchy for the maximum stable set problem
    • Abstract: Abstract The maximum stable set problem is a well-known NP-hard problem in combinatorial optimization, which can be formulated as the maximization of a quadratic square-free polynomial over the (Boolean) hypercube. We investigate a hierarchy of linear programming relaxations for this problem, based on a result of Handelman showing that a positive polynomial over a polytope with non-empty interior can be represented as conic combination of products of the linear constraints defining the polytope. We relate the rank of Handelman’s hierarchy with structural properties of graphs. In particular we show a relation to fractional clique covers which we use to upper bound the Handelman rank for perfect graphs and determine its exact value in the vertex-transitive case. Moreover we show two upper bounds on the Handelman rank in terms of the (fractional) stability number of the graph and compute the Handelman rank for several classes of graphs including odd cycles and wheels and their complements. We also point out links to several other linear and semidefinite programming hierarchies.
      PubDate: 2014-11-01
       
  • A penalty approximation method for a semilinear parabolic double obstacle
           problem
    • Abstract: Abstract In this work, we present a novel power penalty method for the approximation of a global solution to a double obstacle complementarity problem involving a semilinear parabolic differential operator and a bounded feasible solution set. We first rewrite the double obstacle complementarity problem as a double obstacle variational inequality problem. Then, we construct a semilinear parabolic partial differential equation (penalized equation) for approximating the variational inequality problem. We prove that the solution to the penalized equation converges to that of the variational inequality problem and obtain a convergence rate that is corresponding to the power used in the formulation of the penalized equation. Numerical results are presented to demonstrate the theoretical findings.
      PubDate: 2014-11-01
       
  • Fast calculation of multiobjective probability of improvement and expected
           improvement criteria for Pareto optimization
    • Abstract: Abstract The use of surrogate based optimization (SBO) is widely spread in engineering design to reduce the number of computational expensive simulations. However, “real-world” problems often consist of multiple, conflicting objectives leading to a set of competitive solutions (the Pareto front). The objectives are often aggregated into a single cost function to reduce the computational cost, though a better approach is to use multiobjective optimization methods to directly identify a set of Pareto-optimal solutions, which can be used by the designer to make more efficient design decisions (instead of weighting and aggregating the costs upfront). Most of the work in multiobjective optimization is focused on multiobjective evolutionary algorithms (MOEAs). While MOEAs are well-suited to handle large, intractable design spaces, they typically require thousands of expensive simulations, which is prohibitively expensive for the problems under study. Therefore, the use of surrogate models in multiobjective optimization, denoted as multiobjective surrogate-based optimization, may prove to be even more worthwhile than SBO methods to expedite the optimization of computational expensive systems. In this paper, the authors propose the efficient multiobjective optimization (EMO) algorithm which uses Kriging models and multiobjective versions of the probability of improvement and expected improvement criteria to identify the Pareto front with a minimal number of expensive simulations. The EMO algorithm is applied on multiple standard benchmark problems and compared against the well-known NSGA-II, SPEA2 and SMS-EMOA multiobjective optimization methods.
      PubDate: 2014-11-01
       
  • Interior Epigraph Directions method for nonsmooth and nonconvex
           optimization via generalized augmented Lagrangian duality
    • Abstract: Abstract We propose and study a new method, called the Interior Epigraph Directions (IED) method, for solving constrained nonsmooth and nonconvex optimization. The IED method considers the dual problem induced by a generalized augmented Lagrangian duality scheme, and obtains the primal solution by generating a sequence of iterates in the interior of the dual epigraph. First, a deflected subgradient (DSG) direction is used to generate a linear approximation to the dual problem. Second, this linear approximation is solved using a Newton-like step. This Newton-like step is inspired by the Nonsmooth Feasible Directions Algorithm (NFDA), recently proposed by Freire and co-workers for solving unconstrained, nonsmooth convex problems. We have modified the NFDA so that it takes advantage of the special structure of the epigraph of the dual function. We prove that all the accumulation points of the primal sequence generated by the IED method are solutions of the original problem. We carry out numerical experiments by using test problems from the literature. In particular, we study several instances of the Kissing Number Problem, previously solved by various approaches such as an augmented penalty method, the DSG method, as well as several popular differentiable solvers. Our experiments show that the quality of the solutions obtained by the IED method is comparable with (and sometimes favourable over) those obtained by the differentiable solvers.
      PubDate: 2014-11-01
       
  • A study of singular spectrum analysis with global optimization techniques
    • Abstract: Abstract Singular spectrum analysis has recently become an attractive tool in a broad range of applications. Its main mechanism of alternating between rank reduction and Hankel projection to produce an approximation to a particular component of the original time series, however, deserves further mathematical justification. One paramount question to ask is how good an approximation that such a straightforward apparatus can provide when comparing to the absolute optimal solution. This paper reexamines this issue by exploiting a natural parametrization of a general Hankel matrix via its Vandermonde factorization. Such a formulation makes it possible to recast the notion of singular spectrum analysis as a semi-linear least squares problem over a compact feasible set, whence global optimization techniques can be employed to find the absolute best approximation. This framework might not be immediately suitable for practical application because global optimization is expectedly more expensive, but it does provide a theoretical baseline for comparison. As such, our empirical results indicate that the simpler SSA algorithm usually is amazingly sufficient as a handy tool for constructing exploratory model. The more complicated global methods could be used as an alternative of rigorous affirmative procedure for verifying or assessing the quality of approximation.
      PubDate: 2014-11-01
       
  • Vladimir Fedorovich Demyanov (18.08.1938–18.04.2014)
    • PubDate: 2014-11-01
       
  • Ya. D. Sergeyev, R. G. Strongin and D. Lera: Introduction to global
           optimization exploiting space-filling curves
    • PubDate: 2014-11-01
       
  • Branch-and-Sandwich: a deterministic global optimization algorithm for
           optimistic bilevel programming problems. Part I: Theoretical development
    • Abstract: Abstract We present a global optimization algorithm, Branch-and-Sandwich, for optimistic bilevel programming problems that satisfy a regularity condition in the inner problem. The functions involved are assumed to be nonconvex and twice continuously differentiable. The proposed approach can be interpreted as the exploration of two solution spaces (corresponding to the inner and the outer problems) using a single branch-and-bound tree. A novel branching scheme is developed such that classical branch-and-bound is applied to both spaces without violating the hierarchy in the decisions and the requirement for (global) optimality in the inner problem. To achieve this, the well-known features of branch-and-bound algorithms are customized appropriately. For instance, two pairs of lower and upper bounds are computed: one for the outer optimal objective value and the other for the inner value function. The proposed bounding problems do not grow in size during the algorithm and are obtained from the corresponding problems at the parent node.
      PubDate: 2014-11-01
       
  • R. Paulavičius and J. Žilinskas: Simplicial global optimization
    • PubDate: 2014-10-30
       
  • Journal of Global Optimization Best Paper Award for a paper published in
           2013
    • PubDate: 2014-10-30
       
  • Some observations on exclusion regions in branch and bound algorithms
    • Abstract: Abstract In branch and bound algorithms for constrained global optimization, an acceleration technique is to construct regions \({\varvec{x}}^{*}\) around local optimizing points \(\check{x}\) , then delete these regions from further search. The result of the algorithm is then a list of those small regions in which all globally optimizing points must lie. If the constructed regions are too small, the algorithm will not be able to easily reject adjacent regions in the search, while, if the constructed regions are too large, the set of optimizing points is not known accurately. We briefly review previous methods of constructing boxes about approximate optimizing points. We then derive a formula for determining the size of a constructed solution-containing region, depending on a small radius \(\epsilon \) , and of constructing a containing box \({\varvec{X}}^{*}\supset {\varvec{x}}^{*}\) such that all points in \({\varvec{X}}^{*}\setminus {\varvec{x}}^{*}\) are proven to be infeasible, without the need to actually process them in the branch and bound algorithm. The construction differs in its motivation and concept from previous methods of constructing such boxes \({\varvec{X}}^{*}\) . It may be possible to use this technique to reduce the large amount of processing branch and bound algorithms typically require to fathom regions adjacent to optimizing points, and to obtain more accurate bounds on solution sets.
      PubDate: 2014-10-29
       
  • Maximizing the net present value of a Steiner tree
    • Abstract: Abstract The theory of Steiner trees has been extensively applied in physical network design problems to locate a Steiner point that minimizes the total length of a tree. However, maximizing the total generated cash flows of a tree has not been investigated. Such a tree has costs associated with its edges and values associated with nodes. In order to reach the nodes in the tree, the edges need to be constructed. The edges are constructed in a particular order and the costs of constructing the edges and the values at the nodes are discounted over time. These discounted costs and values generate cash flows. In this paper, we study the problem of optimally locating a single Steiner point so as to maximize the sum of all the discounted cash flows, known as the net present value (NPV). An application of this problem occurs in underground mining where, we want to optimally locate a junction point in the underground access network to maximize the NPV. We propose an efficient iterative algorithm to optimally locate a single degree-3 Steiner point. We show this algorithm converges quickly and the Steiner point is unique subject to realistic design parameters.
      PubDate: 2014-10-22
       
  • Parameter identification for a nonlinear enzyme-catalytic dynamic system
           with time-delays
    • Abstract: Abstract In this paper, we consider a nonlinear enzyme-catalytic dynamical system with uncertain system parameters and state-delays for describing the process of batch culture. Some important properties of the time-delay system are discussed. Taking account of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium points for the time-delay system, we define quantitatively biological robustness of the intracellular substance concentrations for the entire process of batch culture to identify the uncertain system parameters and state-delays. Taking the defined biological robustness as a cost function, we establish an identification model subject to the time-delay system, continuous state inequality constraints and parameter constraints. By a penalty approach, this model can be converted into a sequence of nonlinear programming submodels. In consideration of both the difficulty in finding analytical solutions and the complexity of numerical solution to the nonlinear system, based on an improved simulated annealing, we develop a parallelized synchronous algorithm to solve these nonlinear programming submodels. An illustrative numerical example shows the appropriateness of the optimal system parameters and state-delays as well as the validity of the parallel algorithm.
      PubDate: 2014-10-19
       
  • Optimal curvature and gradient-constrained directional cost paths in
           3-space
    • Abstract: Abstract In the design of underground tunnel layout, the development cost is often dependent on the direction of the tunnel at each point due to directional ground fracturing. This paper considers the problem of finding a minimum cost curvature-constrained path between two directed points in 3-space, where the cost at every point along the path depends on the instantaneous direction. This anisotropic behaviour of the cost models the development cost of a tunnel in ground with faulting planes that are almost vertical. The main result we prove in this paper is that there exists an optimal path of the form \(\mathcal {C}\mathcal {S}\mathcal {C}\mathcal {S}\mathcal {C}\mathcal {S}\mathcal {C}\) (or a degeneracy), where \(\mathcal {C}\) represents a segment of a helix with unit radius and \(\mathcal {S}\) represents a straight line segment. This generalises a previous result that in the restriction of the problem to the horizontal plane there always exists a path of the form \(\mathcal {C}\mathcal {S}\mathcal {C}\mathcal {S}\mathcal {C}\) or a degeneracy which is optimal. We also prove some key structural results which are necessary for creating an algorithm which can construct an optimal path between a given pair of directed points in 3-space with a prescribed directional cost function.
      PubDate: 2014-10-15
       
  • Global solutions to nonconvex optimization of 4th-order polynomial and
           log-sum-exp functions
    • Abstract: Abstract This paper presents a canonical dual approach for solving a nonconvex global optimization problem governed by a sum of 4th-order polynomial and a log-sum-exp function. Such a problem arises extensively in engineering and sciences. Based on the canonical duality–triality theory, this nonconvex problem is transformed to an equivalent dual problem, which can be solved easily under certain conditions. We proved that both global minimizer and the biggest local extrema of the primal problem can be obtained analytically from the canonical dual solutions. As two special cases, a quartic polynomial minimization and a minimax problem are discussed. Existence conditions are derived, which can be used to classify easy and relative hard instances. Applications are illustrated by several nonconvex and nonsmooth examples.
      PubDate: 2014-10-10
       
  • Smoothing augmented Lagrangian method for nonsmooth constrained
           optimization problems
    • Abstract: Abstract In this paper, we propose a smoothing augmented Lagrangian method for finding a stationary point of a nonsmooth and nonconvex optimization problem. We show that any accumulation point of the iteration sequence generated by the algorithm is a stationary point provided that the penalty parameters are bounded. Furthermore, we show that a weak version of the generalized Mangasarian Fromovitz constraint qualification (GMFCQ) at the accumulation point is a sufficient condition for the boundedness of the penalty parameters. Since the weak GMFCQ may be strictly weaker than the GMFCQ, our algorithm is applicable for an optimization problem for which the GMFCQ does not hold. Numerical experiments show that the algorithm is efficient for finding stationary points of general nonsmooth and nonconvex optimization problems, including the bilevel program which will never satisfy the GMFCQ.
      PubDate: 2014-10-08
       
  • On the integration of row and column uncertainty in robust linear
           programming
    • Abstract: Abstract The usual formulation of a linear program is max \(c\cdot x{:}Ax \le b, x \ge 0\) . The core part of this linear program is the \(A\) matrix since the columns define the variables and the rows define the constraints. The \(A\) matrix is constructed by populating columns or populating rows, or some of both, depending on the nature of the data and how it is collected. This paper addresses the construction of the \(A\) matrix and solution procedures when there are separate data sources for the columns and for the rows and, moreover, the data is uncertain. The \(A\) matrices which are “realizable” are only those which are considered possible from both sources. These realizable matrices then form an uncertainty set \(U\) for a robust linear program. We show how to formulate and solve linear programs which provide lower and upper bounds to the robust linear program defined by \(U\) . We also show how to use ordinary linear programming duality to share and divide the “credit/responsibility” of the optimal value of the robust linear program between the two alternative data sources.
      PubDate: 2014-10-08
       
  • Optimal rank-sparsity decomposition
    • Abstract: Abstract We describe a branch-and-bound (b&b) method aimed at searching for an exact solution of the fundamental problem of decomposing a matrix into the sum of a sparse matrix and a low-rank matrix. Previous heuristic techniques employed convex and nonconvex optimization. We leverage and extend those ideas, within a spatial b&b framework, aimed at exact global optimization. Our work may serve to (i) gather evidence to assess the true quality of the previous heuristic techniques, and (ii) provide software to routinely calculate global optima or at least better solutions for moderate-sized instances coming from applications.
      PubDate: 2014-10-01
       
 
 
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