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 Subjects -> ENGINEERING (Total: 2167 journals)     - CHEMICAL ENGINEERING (184 journals)    - CIVIL ENGINEERING (168 journals)    - ELECTRICAL ENGINEERING (94 journals)    - ENGINEERING (1173 journals)    - ENGINEERING MECHANICS AND MATERIALS (355 journals)    - HYDRAULIC ENGINEERING (55 journals)    - INDUSTRIAL ENGINEERING (57 journals)    - MECHANICAL ENGINEERING (81 journals) ENGINEERING (1173 journals)            First | 2 3 4 5 6 7 8 9 | Last
 International Journal of Grid and Utility Computing International Journal of Heat and Fluid Flow       (Followers: 19) International Journal of Heat and Mass Transfer       (Followers: 130) International Journal of Heavy Vehicle Systems       (Followers: 8) International Journal of Hypersonics       (Followers: 3) International Journal of Imaging Systems and Technology       (Followers: 2) International Journal of Impact Engineering       (Followers: 8) International Journal of Information Acquisition       (Followers: 1) International Journal of Innovation and Applied Studies       (Followers: 4) International Journal of Innovation Science       (Followers: 7) International Journal of Innovative Technology and Research       (Followers: 1) International Journal of Integrated Engineering International Journal of Intelligent Engineering Informatics International Journal of Intelligent Systems and Applications in Engineering International Journal of Lifecycle Performance Engineering       (Followers: 1) International Journal of Machine Tools and Manufacture       (Followers: 5) International Journal of Manufacturing Research       (Followers: 5) International Journal of Manufacturing Technology and Management       (Followers: 7) International Journal of Materials and Product Technology       (Followers: 3) International Journal of Mathematical Education in Science and Technology       (Followers: 8) International Journal of Mathematics in Operational Research       (Followers: 1) International Journal of Medical Engineering and Informatics       (Followers: 5) International Journal of Micro Air Vehicles       (Followers: 4) International Journal of Microwave and Wireless Technologies       (Followers: 1) International Journal of Microwave Science and Technology       (Followers: 2) International Journal of Mobile Network Design and Innovation       (Followers: 3) International Journal of Multiphase Flow       (Followers: 3) International Journal of Nanomanufacturing International Journal of Nanoscience International Journal of Nanotechnology       (Followers: 6) International Journal of Nanotechnology and Molecular Computation       (Followers: 3) International Journal of Navigation and Observation       (Followers: 11) International Journal of Network Management International Journal of Nonlinear Sciences and Numerical Simulation International Journal of Numerical Methods for Heat & Fluid Flow       (Followers: 8) International Journal of Optics       (Followers: 1) International Journal of Organisational Design and Engineering       (Followers: 10) International Journal of Pattern Recognition and Artificial Intelligence       (Followers: 6) International Journal of Pavement Engineering       (Followers: 3) International Journal of Physical Modelling in Geotechnics       (Followers: 3) International Journal of Plasticity       (Followers: 6) International Journal of Plastics Technology       (Followers: 1) International Journal of Polymer Analysis and Characterization       (Followers: 5) International Journal of Polymer Science       (Followers: 20) International Journal of Precision Engineering and Manufacturing       (Followers: 5) International Journal of Precision Engineering and Manufacturing-Green Technology International Journal of Precision Technology International Journal of Pressure Vessels and Piping       (Followers: 4) International Journal of Production Economics       (Followers: 14) International Journal of Quality and Innovation       (Followers: 5) International Journal of Quality Assurance in Engineering and Technology Education       (Followers: 2) International Journal of Quality Engineering and Technology       (Followers: 2) International Journal of Quantum Information International Journal of Rapid Manufacturing       (Followers: 4) International Journal of Reliability, Quality and Safety Engineering       (Followers: 8) International Journal of Renewable Energy Technology       (Followers: 9) International Journal of Robust and Nonlinear Control       (Followers: 3) International Journal of Science Engineering and Advance Technology International Journal of Sediment Research       (Followers: 1) International Journal of Self-Propagating High-Temperature Synthesis       (Followers: 2) International Journal of Signal and Imaging Systems Engineering International Journal of Six Sigma and Competitive Advantage International Journal of Social Robotics       (Followers: 2) International Journal of Software Engineering and Knowledge Engineering       (Followers: 2) International Journal of Space Science and Engineering       (Followers: 2) International Journal of Speech Technology       (Followers: 5) International Journal of Spray and Combustion Dynamics       (Followers: 7) International Journal of Superconductivity International Journal of Surface Engineering and Interdisciplinary Materials Science       (Followers: 1) International Journal of Surface Science and Engineering       (Followers: 8) International Journal of Sustainable Engineering       (Followers: 7) International Journal of Sustainable Manufacturing       (Followers: 5) International Journal of Systems and Service-Oriented Engineering International Journal of Systems Assurance Engineering and Management International Journal of Systems, Control and Communications       (Followers: 2) International Journal of Technoethics       (Followers: 1) International Journal of Technology Management and Sustainable Development       (Followers: 1) International Journal of Technology Policy and Law       (Followers: 6) International Journal of Telemedicine and Applications       (Followers: 2) International Journal of Thermal Sciences       (Followers: 8) International Journal of Thermodynamics       (Followers: 3) International Journal of Turbo & Jet-Engines       (Followers: 1) International Journal of Ultra Wideband Communications and Systems International Journal of Vehicle Autonomous Systems       (Followers: 1) International Journal of Vehicle Design       (Followers: 8) International Journal of Vehicle Information and Communication Systems       (Followers: 2) International Journal of Vehicle Noise and Vibration       (Followers: 3) International Journal of Vehicle Safety       (Followers: 5) International Journal of Vehicular Technology       (Followers: 3) 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: 7) International Review of Applied Sciences and Engineering International Scholarly Research Notices       (Followers: 235) Inverse Problems in Science and Engineering       (Followers: 2) Ionics IPTEK The Journal for Technology and Science IRBM News Ironmaking & Steelmaking       (Followers: 2)
 Journal of Global Optimization   [SJR: 0.919]   [H-I: 51]   [4 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1573-2916 - ISSN (Online) 0925-5001    Published by Springer-Verlag  [2281 journals]
• Irregular polyomino tiling via integer programming with application in
phased array antenna design
• Abstract: Abstract A polyomino is a generalization of the domino and is created by connecting a fixed number of unit squares along edges. Tiling a region with a given set of polyominoes is a hard combinatorial optimization problem. This paper is motivated by a recent application of irregular polyomino tilings in the design of phased array antennas. Specifically, we formulate the irregular polyomino tiling problem as a nonlinear exact set covering model, where irregularity is incorporated into the objective function using the information-theoretic entropy concept. An exact solution method based on a branch-and-price framework along with novel branching and lower-bounding schemes is proposed. The developed method is shown to be effective for small- and medium-size instances of the problem. For large-size instances, efficient heuristics and approximation algorithms are provided. Encouraging computational results including phased array antenna simulations are reported.
PubDate: 2015-09-01

• Nonemptiness and boundedness of solution sets for vector variational
inequalities via topological method
• Abstract: Abstract In this paper, some characterizations of nonemptiness and boundedness of solution sets for vector variational inequalities are studied in finite and infinite dimensional spaces, respectively. By using a new proof method which is different from the one used in Huang et al. (J Optim Theory Appl 162:548–558 2014), a sufficient and necessary condition for the nonemptiness and boundedness of solution sets is established. Basing on this result, some new characterizations of nonemptiness and boundedness of solution sets for vector variational inequalities are proved. Compared with the known results in Huang et al. (2014), the key assumption that $$K_\infty \cap (F(K))^{w\circ }_C=\{0\}$$ is not required in finite dimensional spaces. Furthermore, the corresponding result of Huang et al. (2014) is extended to the case of infinite dimensional spaces. Some examples are also given to illustrated the main results.
PubDate: 2015-09-01

• Existence results for vector equilibrium problems given by a sum of two
functions
• Abstract: Abstract We obtain existence results for the weak vector equilibrium problem where the function involved is a sum of two functions, and the assumptions are required separately on each of these functions. We show that some earlier results of this type contain too demanding assumptions. We relax several of these assumption without loosing the results. The special case of reflexive Banach spaces is also studied, where we make use of the fact that closed balls are weakly compact.
PubDate: 2015-09-01

• Maximizing and minimizing quasiconvex functions: related properties,
existence and optimality conditions via radial epiderivatives
• Abstract: Abstract This paper deals with maximization and minimization of quasiconvex functions in a finite dimensional setting. Firstly, some existence results on closed convex sets, possibly containing lines, are presented. This is given via a careful study of reduction to the boundary and/or extremality of the feasible set. Necessary or sufficient optimality conditions are derived in terms of radial epiderivatives. Then, the problem of minimizing quasiconvex functions are analyzed via asymptotic analysis. Finally, some attempts to define asymptotic functions under quasiconvexity are also outlined. Several examples illustrating the applicability of our results are shown.
PubDate: 2015-09-01

• On power penalty methods for linear complementarity problems arising from
American option pricing
• Abstract: Abstract Power penalty methods for solving a linear parabolic complementarity problem arising from American option pricing have attracted much attention. These methods require us to solve a series of systems of nonlinear equations (called penalized equations). In this paper, we first study the relationships among the solutions of penalized equations under appropriate conditions. Additionally, since these penalized equations are neither smooth nor convex, some existing algorithms, such as Newton method, cannot be applied directly to solve them. We shall apply the nonlinear Jacobian method to solve penalized equations and verify that the iteration sequence generated by the method converges monotonically to the solution of the penalized equation. Some numerical results confirm the theoretical results and the efficiency of the proposed algorithm.
PubDate: 2015-09-01

• A homotopy method based on penalty function for nonlinear semidefinite
programming
• Abstract: Abstract This paper proposes a homotopy method based on a penalty function for solving nonlinear semidefinite programming problems. The penalty function is the composite function of an exponential penalty function, the eigenvalue function and a nonlinear operator mapping. Representations of its first and second order derivatives are given. Using the penalty function, a new homotopy is constructed. Global convergence of a smooth curve determined by the homotopy is proven under mild conditions. In the process of numerically tracing the curve, the method requires just the solution of a linear system of dimension $$n+2$$ , whereas a homotopy method proposed by Yang and Yu (Comput Optim Appl 56(1):81–96, 2013) requires a system of dimension $$n+m(m+1)/2+1$$ to be solved, where $$n$$ is the number of variables while $$m$$ is the order of constraint matrix. So, it is expected that the proposed method can improve the efficiency of the method proposed by Yang and Yu. Preliminary numerical experiments are presented and show that the considered algorithm is efficient for some nonlinear semidefinite programming problems.
PubDate: 2015-09-01

• Reverse propagation of McCormick relaxations
• Abstract: Abstract Constraint propagation techniques have heavily utilized interval arithmetic while the application of convex and concave relaxations has been mostly restricted to the domain of global optimization. Here, reverse McCormick propagation, a method to construct and improve McCormick relaxations using a directed acyclic graph representation of the constraints, is proposed. In particular, this allows the interpretation of constraints as implicitly defining set-valued mappings between variables, and allows the construction and improvement of relaxations of these mappings. Reverse McCormick propagation yields potentially tighter enclosures of the solutions of constraint satisfaction problems than reverse interval propagation. Ultimately, the relaxations of the objective of a non-convex program can be improved by incorporating information about the constraints.
PubDate: 2015-09-01

• Constrained shortest path with uncertain transit times
• Abstract: Abstract This paper is concerned with the constrained shortest path (CSP) problem, where in addition to the arc cost, a transit time is associated to each arc. The presence of uncertainty in transit times is a critical issue in a wide variety of world applications, such as telecommunication, traffic, and transportation. To capture this issue, we present tractable approaches for solving the CSP problem with uncertain transit times from the viewpoint of robust and stochastic optimization. To study robust CSP problem, two different uncertainty sets, $${\varGamma }$$ -scenario and ellipsoidal, are considered. We show that the robust counterpart of the CSP problem under both uncertainty sets, can be efficiently solved. We further consider the CSP problem with random transit times and show that the problem can be solved by solving robust constrained shortest path problem under ellipsoidal uncertainty set. We present extensive computational results on a set of randomly generated networks. Our results demonstrate that with a reasonable extra cost, the robust optimal path preserves feasibility, in almost all scenarios under $${\varGamma }$$ -scenario uncertainty set. The results also show that, in the most cases, the robust CSP problem under ellipsoidal uncertainty set is feasible.
PubDate: 2015-09-01

• Population model-based optimization
• Abstract: Abstract Model-based optimization methods are a class of stochastic search methods that iteratively find candidate solutions by generating samples from a parameterized probabilistic model on the solution space. In order to better capture the multi-modality of the objective functions than the traditional model-based methods which use only a single model, we propose a framework of using a population of models at every iteration with an adaptive mechanism to propagate the population over iterations. The adaptive mechanism is derived from estimating the optimal parameter of the probabilistic model in a Bayesian manner, and thus provides a proper way to determine the diversity in the population of the models. We provide theoretical justification on the convergence of this framework by showing that the posterior distribution of the parameter asymptotically converges to a degenerate distribution concentrating on the optimal parameter. Under this framework, we develop two practical algorithms by incorporating sequential Monte Carlo methods, and carry out numerical experiments to illustrate their performance.
PubDate: 2015-09-01

• Second-order conditions for existence of augmented Lagrange multipliers
for eigenvalue composite optimization problems
• Abstract: Abstract In this paper, we mainly consider the augmented Lagrangian duality theory and explore second-order conditions for the existence of augmented Lagrange multipliers for eigenvalue composite optimization problems. In the approach, we reformulate the augmented Lagrangian introduced by Rockafellar into a new form in terms of the Moreau envelope function and characterize second-order conditions via the epi-derivatives of the augmented Lagrangian.
PubDate: 2015-09-01

• Analysis of copositive optimization based linear programming bounds on
• Abstract: Abstract The problem of minimizing a quadratic form over the unit simplex, referred to as a standard quadratic optimization problem, admits an exact reformulation as a linear optimization problem over the convex cone of completely positive matrices. This computationally intractable cone can be approximated in various ways from the inside and from the outside by two sequences of nested tractable convex cones of increasing accuracy. In this paper, we focus on the inner polyhedral approximations due to Yıldırım (Optim Methods Softw 27(1):155–173, 2012) and the outer polyhedral approximations due to de Klerk and Pasechnik (SIAM J Optim 12(4):875–892, 2002). We investigate the sequences of upper and lower bounds on the optimal value of a standard quadratic optimization problem arising from these two hierarchies of inner and outer polyhedral approximations. We give complete algebraic descriptions of the sets of instances on which upper and lower bounds are exact at any given finite level of the hierarchy. We identify the structural properties of the sets of instances on which upper and lower bounds converge to the optimal value only in the limit. We present several geometric and topological properties of these sets. Our results shed light on the strengths and limitations of these inner and outer polyhedral approximations in the context of standard quadratic optimization.
PubDate: 2015-09-01

• Numerical approximation of the solution in infinite dimensional global
optimization using a representation formula
• Abstract: Abstract A non convex optimization problem, involving a regular functional J, on a closed and bounded subset S of a separable Hilbert space V is here considered. No convexity assumption is introduced. The solutions are represented by using a closed formula involving means of convenient random variables, analogous to Pincus (Oper Res 16(3):690–694, 1968). The representation suggests a numerical method based on the generation of samples in order to estimate the means. Three strategies for the implementation are examined, with the originality that they do not involve a priori finite dimensional approximation of the solution and consider a hilbertian basis or enumerable dense family of V. The results may be improved on a finite-dimensional subspace by an optimization procedure, in order to get higher-quality solutions. Numerical examples involving both classical situation and an engineering application issued from calculus of variations are presented and establish that the method is effective to calculate.
PubDate: 2015-08-28

• Semidefinite programming relaxation methods for global optimization
problems with sparse polynomials and unbounded semialgebraic feasible sets

• Abstract: Abstract We propose a hierarchy of semidefinite programming (SDP) relaxations for polynomial optimization with sparse patterns over unbounded feasible sets. The convergence of the proposed SDP hierarchy is established for a class of polynomial optimization problems. This is done by employing known sums-of-squares sparsity techniques of Kojima and Muramatsu Comput Optim Appl 42(1):31–41, (2009) and Lasserre SIAM J Optim 17:822–843, (2006) together with a representation theorem for polynomials over unbounded sets obtained recently in Jeyakumar et al. J Optim Theory Appl 163(3):707–718, (2014). We demonstrate that the proposed sparse SDP hierarchy can solve some classes of large scale polynomial optimization problems with unbounded feasible sets using the polynomial optimization solver SparsePOP developed by Waki et al. ACM Trans Math Softw 35:15 (2008).
PubDate: 2015-08-28

• On sufficient optimality conditions for multiobjective control problems
• Abstract: Abstract This paper is devoted to presenting optimality conditions for the sufficiency of the maximum principle for multiobjective optimal control problems with nonsmooth data. Such conditions are the most general as possible in the sense that problems in which the set of necessary conditions from the maximum principle are also sufficient, necessarily obey them. A variation of such conditions is also presented, under which the set of optimal solutions of the multiobjective problem can be determined by resolving a related scalar weighting problem.
PubDate: 2015-08-23

• Dynamic programming approximation algorithms for the capacitated
lot-sizing problem
• Abstract: Abstract This paper provides a new idea for approximating the inventory cost function to be used in a truncated dynamic program for solving the capacitated lot-sizing problem. The proposed method combines dynamic programming with regression, data fitting, and approximation techniques to estimate the inventory cost function at each stage of the dynamic program. The effectiveness of the proposed method is analyzed on various types of the capacitated lot-sizing problem instances with different cost and capacity characteristics. Computational results show that approximation approaches could significantly decrease the computational time required by the dynamic program and the integer program for solving different types of the capacitated lot-sizing problem instances. Furthermore, in most cases, the proposed approximate dynamic programming approaches can accurately capture the optimal solution of the problem with consistent computational performance over different instances.
PubDate: 2015-08-23

• Constrained optimization with stochastic feasibility regions applied to
vehicle path planning
• Abstract: Abstract In real-time trajectory planning for unmanned vehicles, on-board sensors, radars and other instruments are used to collect information on possible obstacles to be avoided and pathways to be followed. Since, in practice, observations of the sensors have measurement errors, the stochasticity of the data has to be incorporated into the models. In this paper, we consider using a genetic algorithm for the constrained optimization problem of finding the trajectory with minimum length between two locations, avoiding the obstacles on the way. To incorporate the variability of the sensor readings, we propose a modified genetic algorithm, addressing the stochasticity of the feasible regions. In this way, the probability that a possible solution in the search space, say x, is feasible can be derived from the random observations of obstacles and pathways, creating a real-time data learning algorithm. By building a confidence region from the observed data such that its border intersects with the solution point x, the level of the confidence region defines the probability that x is feasible. We propose using a smooth penalty function based on the Gaussian distribution, facilitating the borders of the feasible regions to be reached by the algorithm.
PubDate: 2015-08-22

• Extended reverse-convex programming: an approximate enumeration approach
to global optimization
• Abstract: Abstract A new approach to solving a large class of factorable nonlinear programming (NLP) problems to global optimality is presented in this paper. Unlike the traditional strategy of partitioning the decision-variable space employed in many branch-and-bound methods, the proposed approach approximates the NLP problem by a reverse-convex programming (RCP) problem to a controlled precision, with the latter then solved by an enumerative search. To establish the theoretical guarantees of the method, the notion of “RCP regularity” is introduced and it is proven that enumeration is guaranteed to yield a global optimum when the RCP problem is regular. An extended RCP algorithmic framework is then presented and its performance is examined for a small set of test problems.
PubDate: 2015-08-22

• Eigenvalue analysis of constrained minimization problem for homogeneous
polynomial
• Abstract: Abstract In this paper, the concepts of Pareto H-eigenvalue and Pareto Z-eigenvalue are introduced for studying constrained minimization problem and the necessary and sufficient conditions of such eigenvalues are given. It is proved that a symmetric tensor has at least one Pareto H-eigenvalue (Pareto Z-eigenvalue). Furthermore, the minimum Pareto H-eigenvalue (or Pareto Z-eigenvalue) of a symmetric tensor is exactly equal to the minimum value of constrained minimization problem of homogeneous polynomial deduced by such a tensor, which gives an alternative methods for solving the minimum value of constrained minimization problem. In particular, a symmetric tensor $${\mathcal {A}}$$ is strictly copositive if and only if every Pareto H-eigenvalue (Z-eigenvalue) of $${\mathcal {A}}$$ is positive, and $${\mathcal {A}}$$ is copositive if and only if every Pareto H-eigenvalue (Z-eigenvalue) of $${\mathcal {A}}$$ is non-negative.
PubDate: 2015-08-14

• Variable-fidelity modeling of structural analysis of assemblies
• Abstract: Abstract This paper deals with the advantages of using variable-fidelity metamodeling strategies in order to develop a valid metamodel more rapidly than by using traditional methods. In our mechanical assembly design, we use the term “variable-fidelity” in reference to the convergence (or accuracy) level of the iterative solver being used. Variable-fidelity metamodeling is a way to improve the prediction of the output of a complex system by incorporating rapidly available auxiliary lower-fidelity data. This work uses two fidelity levels, but more levels can be added. The LATIN iterative algorithm is used along with a “multiparametric” strategy to calculate the various data and their different fidelity levels by means of an error indicator. Three main categories of variable-fidelity strategies are currently available. We tested at least one method from each of these categories, which comes to a total of five methods for calculating a valid metamodel using low- and high-fidelity data. Here, our objective is to compare the performances of these five methods in solving three mechanical examples.
PubDate: 2015-08-13

• Design of space thrusters: a topology optimization problem solved via a
Branch and Bound method
• Abstract: Abstract In this paper, an exact Branch and Bound Algorithm has been developed to solve a difficult global optimization problem concerning the design of space thrusters. This optimization problem is hard to solve mainly because the objective function to be minimized is implicit and must be computed by using a Finite Element method code. In a previous paper, we implement a method based on local search algorithms and we then proved that this problem is non convex yielding a strong dependency between the obtained local solution and the starting points. In this paper, by taking into account a monotonicity hypothesis that we validated numerically, we provide properties making it possible the computation of bounds. This yields the development of a topology optimization Branch and Bound code. Some numerical examples show the efficiency of this new approach.
PubDate: 2015-08-11

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