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 Subjects -> ENGINEERING (Total: 1963 journals)     - CHEMICAL ENGINEERING (151 journals)    - CIVIL ENGINEERING (149 journals)    - ELECTRICAL ENGINEERING (82 journals)    - ENGINEERING (1120 journals)    - ENGINEERING MECHANICS AND MATERIALS (290 journals)    - HYDRAULIC ENGINEERING (45 journals)    - INDUSTRIAL ENGINEERING (52 journals)    - MECHANICAL ENGINEERING (74 journals) ENGINEERING (1120 journals)            First | 2 3 4 5 6 7 8 9 | Last
 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: 7) International Journal of Manufacturing Technology and Management       (Followers: 9) International Journal of Materials and Product Technology       (Followers: 4) International Journal of Mathematical Education in Science and Technology       (Followers: 6) 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: 3) 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: 4) International Journal of Navigation and Observation       (Followers: 5) International Journal of Network Management International Journal of Nonlinear Sciences and Numerical Simulation       (Followers: 1) 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: 8) 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: 3) International Journal of Polymer Science       (Followers: 16) International Journal of Precision Engineering and Manufacturing       (Followers: 7) International Journal of Precision Technology International Journal of Pressure Vessels and Piping       (Followers: 2) International Journal of Production Economics       (Followers: 10) International Journal of Quality and Innovation       (Followers: 2) International Journal of Quality Engineering and Technology       (Followers: 2) International Journal of Quantum Information International Journal of Rapid Manufacturing       (Followers: 3) International Journal of Reliability, Quality and Safety Engineering       (Followers: 4) International Journal of Renewable Energy Technology       (Followers: 7) 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: 1) 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: 2) International Journal of Spray and Combustion Dynamics       (Followers: 5) 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 Assurance Engineering and Management International Journal of Systems, Control and Communications       (Followers: 2) 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: 4) International Journal of Thermodynamics       (Followers: 1) 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: 4) International Journal of Vehicular Technology       (Followers: 1) 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: 5) 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 Ironmaking & Steelmaking       (Followers: 2) Irrigation and Drainage Systems ISA Transactions       (Followers: 1) ISRN - International Scholarly Research Notices       (Followers: 69) ISRN Nanotechnology ISRN Signal Processing ISRN Thermodynamics IT Professional       (Followers: 2) Journal of Biosensors & Bioelectronics       (Followers: 1) Journal of Advanced Manufacturing Systems       (Followers: 8) Journal of Aerosol Science       (Followers: 2) Journal of Aerospace Engineering       (Followers: 112) Journal of Alloys and Compounds       (Followers: 6) Journal of Analytical and Applied Pyrolysis       (Followers: 3) Journal of Analytical Science & Technology       (Followers: 4) Journal of Analytical Sciences, Methods and Instrumentation       (Followers: 1) Journal of Applied Analysis Journal of Applied and Industrial Sciences Journal of Applied Logic Journal of Applied Physics       (Followers: 139)
 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  [2208 journals]   [SJR: 1.149]   [H-I: 46]
• A solution method for linear variational relation problems
• Abstract: Abstract In this paper, we consider a particular class of variational relation problem namely linear variational relation problem wherein the sets are defined by linear inequalities. The purpose is to study the existence of the solution set and its nature for this class of problem. Using these results, we provide algorithms to obtain the solutions of the problem based on which we present some numerical illustrations.
PubDate: 2014-08-01

• Benson type algorithms for linear vector optimization and applications
• Abstract: Abstract New versions and extensions of Benson’s outer approximation algorithm for solving linear vector optimization problems are presented. Primal and dual variants are provided in which only one scalar linear program has to be solved in each iteration rather than two or three as in previous versions. Extensions are given to problems with arbitrary pointed solid polyhedral ordering cones. Numerical examples are provided, one of them involving a new set-valued risk measure for multivariate positions.
PubDate: 2014-08-01

• Nonlinear separation approach for the augmented Lagrangian in nonlinear
semidefinite programming
• Abstract: Abstract This paper aims at showing that the class of augmented Lagrangian functions for nonlinear semidefinite programming problems can be derived, as a particular case, from a nonlinear separation scheme in the image space associated with the given problem. By means of the image space analysis, a global saddle point condition for the augmented Lagrangian function is investigated. It is shown that the existence of a saddle point is equivalent to a regular nonlinear separation of two suitable subsets of the image space. Without requiring the strict complementarity, it is proved that, under second order sufficiency conditions, the augmented Lagrangian function admits a local saddle point. The existence of global saddle points is then obtained under additional assumptions that do not require the compactness of the feasible set. Motivated by the result on global saddle points, we propose two modified primal-dual methods based on the augmented Lagrangian using different strategies and prove their convergence to a global solution and the optimal value of the original problem without requiring the boundedness condition of the multiplier sequence.
PubDate: 2014-08-01

• Functional inequalities and theorems of the alternative involving
composite functions
• Abstract: Abstract We propose variants of non-asymptotic dual transcriptions for the functional inequality of the form $$f + g + k\circ H \ge h$$ . The main tool we used consists in purely algebraic formulas on the epigraph of the Legendre-Fenchel transform of the function $$f + g + k\circ H$$ that are satisfied in various favorable circumstances. The results are then applied to the contexts of alternative type theorems involving composite and DC functions. The results cover several Farkas-type results for convex or DC systems and are general enough to face with unpublished situations. As applications of these results, nonconvex optimization problems with composite functions, convex composite problems with conic constraints are examined at the end of the paper. There, strong duality, stable strong duality results for these classes of problems are established. Farkas-type results and stable form of these results for the corresponding systems involving composite functions are derived as well.
PubDate: 2014-08-01

• Level bundle-like algorithms for convex optimization
• Abstract: Abstract We propose two restricted memory level bundle-like algorithms for minimizing a convex function over a convex set. If the memory is restricted to one linearization of the objective function, then both algorithms are variations of the projected subgradient method. The first algorithm, proposed in Hilbert space, is a conceptual one. It is shown to be strongly convergent to the solution that lies closest to the initial iterate. Furthermore, the entire sequence of iterates generated by the algorithm is contained in a ball with diameter equal to the distance between the initial point and the solution set. The second algorithm is an implementable version. It mimics as much as possible the conceptual one in order to resemble convergence properties. The implementable algorithm is validated by numerical results on several two-stage stochastic linear programs.
PubDate: 2014-08-01

• On efficiency and mixed duality for a new class of nonconvex
multiobjective variational control problems
• Abstract: Abstract In this paper, we extend the notions of $$(\Phi ,\rho )$$ -invexity and generalized $$(\Phi ,\rho )$$ -invexity to the continuous case and we use these concepts to establish sufficient optimality conditions for the considered class of nonconvex multiobjective variational control problems. Further, multiobjective variational control mixed dual problem is given for the considered multiobjective variational control problem and several mixed duality results are established under $$(\Phi ,\rho )$$ -invexity.
PubDate: 2014-08-01

• SO-I: a surrogate model algorithm for expensive nonlinear integer
programming problems including global optimization applications
• Abstract: Abstract This paper presents the surrogate model based algorithm SO-I for solving purely integer optimization problems that have computationally expensive black-box objective functions and that may have computationally expensive constraints. The algorithm was developed for solving global optimization problems, meaning that the relaxed optimization problems have many local optima. However, the method is also shown to perform well on many local optimization problems, and problems with linear objective functions. The performance of SO-I, a genetic algorithm, Nonsmooth Optimization by Mesh Adaptive Direct Search (NOMAD), SO-MI (Müller et al. in Comput Oper Res 40(5):1383–1400, 2013), variable neighborhood search, and a version of SO-I that only uses a local search has been compared on 17 test problems from the literature, and on eight realizations of two application problems. One application problem relates to hydropower generation, and the other one to throughput maximization. The numerical results show that SO-I finds good solutions most efficiently. Moreover, as opposed to SO-MI, SO-I is able to find feasible points by employing a first optimization phase that aims at minimizing a constraint violation function. A feasible user-supplied point is not necessary.
PubDate: 2014-08-01

• Global optimization workshop 2012
• PubDate: 2014-07-24

• Note on coloring of double disk graphs
• Abstract: Abstract The coloring of disk graphs is motivated by the frequency assignment problem. In 1998, Malesińska et al. introduced double disk graphs as their generalization. They showed that the chromatic number of a double disk graph $$G$$ is at most $$33\,\omega (G) - 35$$ , where $$\omega (G)$$ denotes the size of a maximum clique in $$G$$ . Du et al. improved the upper bound to $$31\,\omega (G) - 1$$ . In this paper we decrease the bound substantially; namely we show that the chromatic number of $$G$$ is at most $$15\,\omega (G) - 14$$ .
PubDate: 2014-07-19

• Reduction of state dependent sweeping process to unconstrained
differential inclusion
• Abstract: Abstract In this article we discuss the differential inclusion known as state dependent sweeping process for a class of prox-regular non-convex sets. We associate with any state dependent sweeping process with such sets an unconstraint differential inclusion whose any solution is a solution of the state sweeping process too. We prove a theorem on the existence of a global solution of nonconvex state dependent sweeping process with unbounded perturbations. The perturbations are not required to be convex valued.
PubDate: 2014-07-18

• Efficient adaptive regression spline algorithms based on mapping approach
with a case study on finance
• Abstract: Abstract Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies have been conducted on improving its performance. For this purpose, an alternative backward stepwise algorithm is proposed through Conic-MARS (CMARS) method which uses a penalized residual sum of squares for MARS as a Tikhonov regularization problem. Additionally, by modifying the forward step of MARS via mapping approach, a time efficient procedure has been introduced by S-FMARS. Inspiring from the advantages of MARS, CMARS and S-FMARS, two hybrid methods are proposed in this study, aiming to produce time efficient DM tools without degrading their performances especially for large datasets. The resulting methods, called SMARS and SCMARS, are tested in terms of several performance criteria such as accuracy, complexity, stability and robustness via simulated and real life datasets. As a DM application, the hybrid methods are also applied to an important field of finance for predicting interest rates offered by a Turkish bank to its customers. The results show that the proposed hybrid methods, being the most time efficient with competing performances, can be considered as powerful choices particularly for large datasets.
PubDate: 2014-07-15

• Norm descent conjugate gradient methods for solving symmetric nonlinear
equations
• Abstract: Abstract Nonlinear conjugate gradient method is very popular in solving large-scale unconstrained minimization problems due to its simple iterative form and lower storage requirement. In the recent years, it was successfully extended to solve higher-dimension monotone nonlinear equations. Nevertheless, the research activities on conjugate gradient method in symmetric equations are just beginning. This study aims to developing, analyzing, and validating a family of nonlinear conjugate gradient methods for symmetric equations. The proposed algorithms are based on the latest, and state-of-the-art descent conjugate gradient methods for unconstrained minimization. The series of proposed methods are derivative-free, where the Jacobian information is needless at the full iteration process. We prove that the proposed methods converge globally under some appropriate conditions. Numerical results with differentiable parameter’s values and performance comparisons with another solver CGD to demonstrate the superiority and effectiveness of the proposed algorithms are reported.
PubDate: 2014-07-11

• Integrating nonlinear branch-and-bound and outer approximation for convex
Mixed Integer Nonlinear Programming
• Abstract: Abstract In this paper, we present a new hybrid algorithm for convex Mixed Integer Nonlinear Programming (MINLP). The proposed hybrid algorithm is an improved version of the classical nonlinear branch-and-bound (BB) procedure, where the enhancements are obtained with the application of the outer approximation algorithm on some nodes of the enumeration tree. The two methods are combined in such a way that each one collaborates to the convergence of the other. Computational experiments with benchmark instances of the MINLP problem show the good performance of the proposed algorithm, which is compared to the outer approximation algorithm, the nonlinear BB algorithm and the hybrid algorithm implemented in the solver Bonmin.
PubDate: 2014-07-06

• A preference-based evolutionary algorithm for multiobjective optimization:
the weighting achievement scalarizing function genetic algorithm
• Abstract: Abstract When solving multiobjective optimization problems, preference-based evolutionary multiobjective optimization (EMO) algorithms introduce preference information into an evolutionary algorithm in order to focus the search for objective vectors towards the region of interest of the Pareto optimal front. In this paper, we suggest a preference-based EMO algorithm called weighting achievement scalarizing function genetic algorithm (WASF-GA), which considers the preferences of the decision maker (DM) expressed by means of a reference point. The main purpose of WASF-GA is to approximate the region of interest of the Pareto optimal front determined by the reference point, which contains the Pareto optimal objective vectors that obey the preferences expressed by the DM in the best possible way. The proposed approach is based on the use of an achievement scalarizing function (ASF) and on the classification of the individuals into several fronts. At each generation of WASF-GA, this classification is done according to the values that each solution takes on the ASF for the reference point and using different weight vectors. These vectors of weights are selected so that the vectors formed by their inverse components constitute a well-distributed representation of the weight vectors space. The efficiency and usefulness of WASF-GA is shown in several test problems in comparison to other preference-based EMO algorithms. Regarding a metric based on the hypervolume, we can say that WASF-GA has outperformed the other algorithms considered in most of the problems.
PubDate: 2014-07-02

• PAVER 2.0: an open source environment for automated performance analysis
of benchmarking data
• Abstract: Abstract In this paper we describe PAVER 2.0, an environment (i.e. a process and a suite of tools supporting that process) for the automated performance analysis of benchmarking data. This new environment improves on its predecessor by addressing some of the shortcomings of the original PAVER (Bussieck et al. in Global optimization and constraint satisfaction, lecture notes in computer science, vol 2861, pp 223–238. Springer, Berlin, 2003. doi:10.1007/978-3-540-39901-8_17) and extending its capabilities. The changes serve to further the original goals of PAVER (automation of the visualization and summarization of benchmarking data) while making the environment more accessible for the use of and modification by the entire community of potential users. In particular, we have targeted the end-users of optimization software, as they are best able to make the many subjective choices necessary to produce impactful results when benchmarking optimization software. We illustrate with some sample analyses conducted via PAVER 2.0.
PubDate: 2014-07-01

• ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of
Nonlinear Equations
• Abstract: Abstract This manuscript introduces ANTIGONE, Algorithms for coNTinuous/Integer Global Optimization of Nonlinear Equations, a general mixed-integer nonlinear global optimization framework. ANTIGONE is the evolution of the Global Mixed-Integer Quadratic Optimizer, GloMIQO, to general nonconvex terms. The purpose of this paper is to show how the extensible structure of ANTIGONE realizes our previously-proposed mixed-integer quadratically-constrained quadratic program and mixed-integer signomial optimization computational frameworks. To demonstrate the capacity of ANTIGONE, this paper presents computational results on a test suite of $$2{,}571$$ problems from standard libraries and the open literature; we compare ANTIGONE to other state-of-the-art global optimization solvers.
PubDate: 2014-07-01

• A fully general, exact algorithm for nesting irregular shapes
• Abstract: Abstract This paper introduces a fully general, exact algorithm for nesting irregular shapes. Both the shapes and material resource can be arbitrary nonconvex polygons. Moreover, the shapes can have holes and the material can have defective areas. Finally, the shapes can be arranged using both translations and arbitrary rotations (as opposed to a finite set of rotation angles, such as 0 $$^\circ$$ and 180 $$^\circ$$ ). The insight that has made all this possible is a novel way to relax the constraint that the shapes not overlap. The key idea is to inscribe a few circles in each irregular shape and then relax the non-overlap constraints for the shapes by replacing them with non-overlap constraints for the inscribed circles. These relaxed problems have the form of quadratic programming problems (QPs) and can be solved to optimality to provide valid lower bounds. Valid upper bounds can be found via local search with strict non-overlap constraints. If the shapes overlap in the solution to the relaxed problem, new circles are inscribed in the shapes to prevent this overlapping configuration from recurring, and the QP is then resolved to obtain improved lower bounds. Convergence to any fixed tolerance is guaranteed in a finite number of iterations. A specialized branch-and-bound algorithm, together with some heuristics, are introduced to find the initial inscribed circles that approximate the shapes. The new approach, called “QP-Nest,” is applied to three problems as proof of concept. The most complicated of these is a problem due to Milenkovic that has four nonconvex polygons with 94, 72, 84, and 74 vertices, respectively. QP-Nest is able prove global optimality when nesting the first two or the first three of these shapes. When all four shapes are considered, QP-Nest finds the best known solution, but cannot prove optimality.
PubDate: 2014-07-01

• Globally convergent DC trust-region methods
• Abstract: Abstract In this paper, we investigate the use of DC (Difference of Convex functions) models and algorithms in the application of trust-region methods to the solution of a class of nonlinear optimization problems where the constrained set is closed and convex (and, from a practical point of view, where projecting onto the feasible region is computationally affordable). We consider DC local models for the quadratic model of the objective function used to compute the trust-region step, and apply a primal-dual subgradient method to the solution of the corresponding trust-region subproblems. One is able to prove that the resulting scheme is globally convergent to first-order stationary points. The theory requires the use of exact second-order derivatives but, in turn, the computation of the trust-region step asks only for one projection onto the feasible region (in comparison to the calculation of the generalized Cauchy point which may require more). The numerical efficiency and robustness of the proposed new scheme when applied to bound-constrained problems is measured by comparing its performance against some of the current state-of-the-art nonlinear programming solvers on a vast collection of test problems.
PubDate: 2014-07-01

• Ya. D. Sergeyev, R. G. Strongin and D. Lera: Introduction to global
optimization exploiting space-filling curves
• PubDate: 2014-07-01

• Preface: Honoring the 60th birthday of Panos M. Pardalos
• PubDate: 2014-05-04

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