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ENGINEERING (1110 journals)            First | 2 3 4 5 6 7 8 9 | Last

International Journal of Mathematical Education in Science and Technology     Hybrid Journal   (Followers: 6)
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: 3)
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: 5)
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: 8)
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: 3)
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: 2)
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: 4)
International Journal of Renewable Energy Technology     Hybrid Journal   (Followers: 7)
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: 5)
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: 4)
International Journal of Thermodynamics     Open Access   (Followers: 1)
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: 2)
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: 124)
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: 151)
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: 5)
Journal of ASTM International     Full-text available via subscription   (Followers: 3)
Journal of Aviation Technology and Engineering     Open Access   (Followers: 6)
Journal of Biological Dynamics     Open Access   (Followers: 1)

  First | 2 3 4 5 6 7 8 9 | Last

Journal Cover Journal of Global Optimization
   [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  [2210 journals]   [SJR: 1.149]   [H-I: 46]
  • A hyperbolic smoothing approach to the Multisource Weber problem
    • Abstract: Abstract The Multisource Weber problem, also known as the continuous location-allocation problem, or as the Fermat-Weber problem, is considered here. A particular case of the Multisource Weber problem is the minimum sum-of-distances clustering problem, also known as the continuous \(p\) -median problem. The mathematical modelling of this problem leads to a \(min-sum-min\) formulation which, in addition to its intrinsic bi-level nature, is strongly nondifferentiable. Moreover, it has a large number of local minimizers, so it is a typical global optimization problem. In order to overcome the intrinsic difficulties of the problem, the so called Hyperbolic Smoothing methodology, which follows a smoothing strategy using a special \( \, C^{\infty } \, \) differentiable class function, is adopted. The final solution is obtained by solving a sequence of low dimension \( \, C^{\infty } \, \) differentiable unconstrained optimization sub-problems which gradually approaches the original problem. For the purpose of illustrating both the reliability and the efficiency of the method, a set of computational experiments making use of traditional test problems described in the literature was performed. Apart from consistently presenting better results when compared to related approaches, the novel technique introduced here was able to deal with instances never tackled before in the context of the Multisource Weber problem.
      PubDate: 2014-09-01
  • A numerical method for pricing European options with proportional
           transaction costs
    • Abstract: Abstract In the paper, we propose a numerical technique based on a finite difference scheme in space and an implicit time-stepping scheme for solving the Hamilton–Jacobi–Bellman (HJB) equation arising from the penalty formulation of the valuation of European options with proportional transaction costs. We show that the approximate solution from the numerical scheme converges to the viscosity solution of the HJB equation as the mesh sizes in space and time approach zero. We also propose an iterative scheme for solving the nonlinear algebraic system arising from the discretization and establish a convergence theory for the iterative scheme. Numerical experiments are presented to demonstrate the robustness and accuracy of the method.
      PubDate: 2014-09-01
  • Restructuring forward step of MARS algorithm using a new knot selection
           procedure based on a mapping approach
    • Abstract: Abstract In high dimensional data modeling, Multivariate Adaptive Regression Splines (MARS) is a popular nonparametric regression technique used to define the nonlinear relationship between a response variable and the predictors with the help of splines. MARS uses piecewise linear functions for local fit and apply an adaptive procedure to select the number and location of breaking points (called knots). The function estimation is basically generated via a two-stepwise procedure: forward selection and backward elimination. In the first step, a large number of local fits is obtained by selecting large number of knots via a lack-of-fit criteria; and in the latter one, the least contributing local fits or knots are removed. In conventional adaptive spline procedure, knots are selected from a set of all distinct data points that makes the forward selection procedure computationally expensive and leads to high local variance. To avoid this drawback, it is possible to restrict the knot points to a subset of data points. In this context, a new method is proposed for knot selection which bases on a mapping approach like self organizing maps. By this method, less but more representative data points are become eligible to be used as knots for function estimation in forward step of MARS. The proposed method is applied to many simulated and real datasets, and the results show that it proposes a time efficient forward step for the knot selection and model estimation without degrading the model accuracy and prediction performance.
      PubDate: 2014-09-01
  • Local reduction based SQP-type method for semi-infinite programs with an
           infinite number of second-order cone constraints
    • Abstract: Abstract The second-order cone program (SOCP) is an optimization problem with second-order cone (SOC) constraints and has achieved notable developments in the last decade. The classical semi-infinite program (SIP) is represented with infinitely many inequality constraints, and has been studied extensively so far. In this paper, we consider the SIP with infinitely many SOC constraints, called the SISOCP for short. Compared with the standard SIP and SOCP, the studies on the SISOCP are scarce, even though it has important applications such as Chebychev approximation for vector-valued functions. For solving the SISOCP, we develop an algorithm that combines a local reduction method with an SQP-type method. In this method, we reduce the SISOCP to an SOCP with finitely many SOC constraints by means of implicit functions and apply an SQP-type method to the latter problem. We study the global and local convergence properties of the proposed algorithm. Finally, we observe the effectiveness of the algorithm through some numerical experiments.
      PubDate: 2014-09-01
  • Preface of the special issue OR: connecting sciences supported by global
           optimization related to the 25th European conference on operational
           research (EURO XXV 2012)
    • PubDate: 2014-09-01
  • New and efficient algorithms for transfer prices and inventory holding
           policies in two-enterprise supply chains
    • Abstract: Abstract We consider a multi-period problem of fair transfer prices and inventory holding policies in two enterprise supply chains. This problem was formulated as a mixed integer non-linear program by Gjerdrum et al. (Eur J Oper Res 143:582–599, 2002). Existing global optimization methods to solve this problem are computationally expensive. We propose a continuous approach based on difference of convex functions (DC) programming and DC Algorithms (DCA) for solving this combinatorial optimization problem. The problem is first reformulated as a DC program via an exact penalty technique. Afterward, DCA, an efficient local approach in non-convex programming framework, is investigated to solve the resulting problem. For globally solving this problem, we investigate a combined DCA-Branch and Bound algorithm. DCA is applied to get lower bounds while upper bounds are computed from a relaxation problem. The numerical results on several test problems show that the proposed algorithms are efficient: DCA provides a good integer solution in a short CPU time although it works on a continuous domain, and the combined DCA-Branch and Bound finds an \(\epsilon \) -optimal solution for large-scale problems in a reasonable time.
      PubDate: 2014-09-01
  • On optimal low rank Tucker approximation for tensors: the case for an
           adjustable core size
    • Abstract: Abstract Approximating high order tensors by low Tucker-rank tensors have applications in psychometrics, chemometrics, computer vision, biomedical informatics, among others. Traditionally, solution methods for finding a low Tucker-rank approximation presume that the size of the core tensor is specified in advance, which may not be a realistic assumption in many applications. In this paper we propose a new computational model where the configuration and the size of the core become a part of the decisions to be optimized. Our approach is based on the so-called maximum block improvement method for non-convex block optimization. Numerical tests on various real data sets from gene expression analysis and image compression are reported, which show promising performances of the proposed algorithms.
      PubDate: 2014-08-17
  • GLODS: Global and Local Optimization using Direct Search
    • Abstract: Abstract Locating and identifying points as global minimizers is, in general, a hard and time-consuming task. Difficulties increase in the impossibility of using the derivatives of the functions defining the problem. In this work, we propose a new class of methods suited for global derivative-free constrained optimization. Using direct search of directional type, the algorithm alternates between a search step, where potentially good regions are located, and a poll step where the previously located promising regions are explored. This exploitation is made through the launching of several instances of directional direct searches, one in each of the regions of interest. Differently from a simple multistart strategy, direct searches will merge when sufficiently close. The goal is to end with as many direct searches as the number of local minimizers, which would easily allow locating the global extreme value. We describe the algorithmic structure considered, present the corresponding convergence analysis and report numerical results, showing that the proposed method is competitive with currently commonly used global derivative-free optimization solvers.
      PubDate: 2014-08-13
  • An information guided framework for simulated annealing
    • Abstract: Abstract This paper presents an information guided framework for stochastic optimization with simulated annealing. Information gathered during randomized exploration of the search domain is used as feedback with progressively increasing gain to drive the optimization procedure, potentially causing the annealing temperature to rise during the algorithm’s execution. The benefits of reheating during the annealing process are shown in terms of significant improvement in the algorithm’s performance, while also staying within bounds for its convergence. A guided-annealing temperature is defined that incorporates information into the annealing schedule. The resulting algorithm has two phases: phase I performs nearly unrestricted exploration as a reconnaissance of the optimization domain and phase II “re-heats” the annealing procedure and exploits information gathered during phase I. Phase I flows seamlessly into phase II via an information effectiveness parameter without need for user input. Conditions are derived to prevent excessive reheating that may jeopardize convergence characteristics. Several examples are presented to test the new algorithm.
      PubDate: 2014-08-08
  • Computing the nadir point for multiobjective discrete optimization
    • Abstract: Abstract We investigate the problem of finding the nadir point for multiobjective discrete optimization problems (MODO). The nadir point is constructed from the worst objective values over the efficient set of a multiobjective optimization problem. We present a new algorithm to compute nadir values for MODO with \(p\) objective functions. The proposed algorithm is based on an exhaustive search of the \((p-2)\) -dimensional space for each component of the nadir point. We compare our algorithm with two earlier studies from the literature. We give numerical results for all algorithms on multiobjective knapsack, assignment and integer linear programming problems. Our algorithm is able to obtain the nadir point for relatively large problem instances with up to five-objectives.
      PubDate: 2014-08-07
  • D-gap functions and descent techniques for solving equilibrium problems
    • Abstract: Abstract A new algorithm for solving equilibrium problems with differentiable bifunctions is provided. The algorithm is based on descent directions of a suitable family of D-gap functions. Its convergence is proved under assumptions which do not guarantee the equivalence between the stationary points of the D-gap functions and the solutions of the equilibrium problem. Moreover, the algorithm does not require to set parameters according to thresholds which depend on regularity properties of the equilibrium bifunction. The results of preliminary numerical tests on Nash equilibrium problems with quadratic payoffs are reported. Finally, some numerical comparisons with other D-gap algorithms are drawn relying on some further tests on linear equilibrium problems.
      PubDate: 2014-08-04
  • Vladimir Fedorovich Demyanov (18.08.1938–18.04.2014)
    • PubDate: 2014-08-03
  • 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
  • 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
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