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 Subjects -> ENGINEERING (Total: 2173 journals)     - CHEMICAL ENGINEERING (183 journals)    - CIVIL ENGINEERING (171 journals)    - ELECTRICAL ENGINEERING (95 journals)    - ENGINEERING (1173 journals)    - ENGINEERING MECHANICS AND MATERIALS (358 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 Heat and Mass Transfer       (Followers: 133) 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: 3) 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: 13) 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: 6) 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: 240) 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       (Followers: 1) ISA Transactions       (Followers: 1)
 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  [2280 journals]
• A polynomial-time nearly-optimal algorithm for an edge coloring problem in
outerplanar graphs
• Abstract: Abstract Given a graph G, we study the problem of finding the minimum number of colors required for a proper edge coloring of G such that any pair of vertices at distance 2 have distinct sets consisting of colors of their incident edges. This minimum number is called the 2-distance vertex-distinguishing index, denoted by $$\chi '_{d2}(G)$$ . Using the breadth first search method, this paper provides a polynomial-time algorithm producing nearly-optimal solution in outerplanar graphs. More precisely, if G is an outerplanar graph with maximum degree $$\varDelta$$ , then the produced solution uses colors at most $$\varDelta +8$$ . Since $$\chi '_{d2}(G)\ge \varDelta$$ for any graph G, our solution is within eight colors from optimal.
PubDate: 2015-10-05

• Supply chain performance assessment and supplier and component importance
identification in a general competitive multitiered supply chain network
model
• Abstract: Abstract In this paper, we develop a multitiered competitive supply chain network game theory model, which includes the supplier tier. The firms are differentiated by brands and can produce their own components, as reflected by their capacities, and/or obtain components from one or more suppliers, who also are capacitated. The firms compete in a Cournot–Nash fashion, whereas the suppliers compete a la Bertrand since firms are sensitive to prices. All decision-makers seek to maximize their profits with consumers reflecting their preferences through the demand price functions associated with the demand markets for the firms’ products. We construct supply chain network performance measures for the full supply chain and the individual firm levels that assess the efficiency of the supply chain or firm, respectively, and also allow for the identification and ranking of the importance of suppliers as well as the components of suppliers with respect to the full supply chain or individual firm. The framework is illustrated through a series of numerical supply chain network examples.
PubDate: 2015-10-03

• Kriging-based infill sampling criterion for constraint handling in
multi-objective optimization
• Abstract: Abstract This paper proposes a novel infill sampling criterion for constraint handling in multi-objective optimization of computationally expensive black-box functions. To reduce the computational burden, Kriging models are used to emulate the objective and constraint functions. The challenge of this multi-objective optimization problem arises from the fact that the epistemic uncertainty of the Kriging models should be taken into account to find Pareto-optimal solutions in the feasible domain. This is done by the proposed sampling criterion combining the Expected HyperVolume Improvement of the front of nondominated solutions and the Probability of Feasibility of new candidates. The proposed criterion is non-intrusive and derivative-free, and it is oriented to: (1) problems in which the computational cost is mainly from the function evaluation rather than optimization, and (2) problems that use complex in-house or commercial software that cannot be modified. The results using the proposed sampling criterion are compared with the results using Multi-Objective Evolutionary Algorithms. These results show that the proposed sampling criterion permits to identify both the feasible domain and an approximation of the Pareto front using a reduced number of computationally expensive simulations.
PubDate: 2015-10-01

• Semi-continuous quadratic optimization: existence conditions and duality
scheme
• Abstract: Abstract In this work, we study the class of problems called semi-continuous optimization, which contains constrained minimization (maximization) problems with lower (upper) semi-continuous objective functions. We show some existence conditions for solutions based on asymptotic techniques, as well as a duality scheme based on the Fenchel–Moreau conjugation specifically applied to semi-continuous problems. Promising results are obtained, when we apply this scheme to minimize quadratic functions (whose Hessians can be symmetric indefinite) over nonempty, closed and convex polyhedral sets.
PubDate: 2015-10-01

• Convex mixed integer nonlinear programming problems and an outer
approximation algorithm
• Abstract: Abstract In this paper, we mainly study one class of convex mixed-integer nonlinear programming problems (MINLPs) with non-differentiable data. By dropping the differentiability assumption, we substitute gradients with subgradients obtained from KKT conditions, and use the outer approximation method to reformulate convex MINLP as one equivalent MILP master program. By solving a finite sequence of subproblems and relaxed MILP problems, we establish an outer approximation algorithm to find the optimal solution of this convex MINLP. The convergence of this algorithm is also presented. The work of this paper generalizes and extends the outer approximation method in the sense of dealing with convex MINLPs from differentiable case to non-differentiable one.
PubDate: 2015-10-01

• Optimal learning with a local parametric belief model
• Abstract: Abstract We are interested in maximizing smooth functions where observations are noisy and expensive to compute, as might arise in computer simulations or laboratory experimentations. We derive a knowledge gradient policy, which chooses measurements which maximize the expected value of information, while using a locally parametric belief model that uses linear approximations with radial basis functions. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. Our technique uses the expected value of a measurement in terms of its ability to improve our estimate of the optimum, capturing correlations in our beliefs about neighboring regions of the function, without posing any assumptions on the global shape of the underlying function a priori. Experimental work suggests that the method adapts to a range of arbitrary, continuous functions, and appears to reliably find the optimal solution. Moreover, the policy is shown to be asymptotically optimal.
PubDate: 2015-10-01

• Augmented Lagrangian methods for nonlinear programming with possible
infeasibility
• Abstract: Abstract In this paper, we consider a nonlinear programming problem for which the constraint set may be infeasible. We propose an algorithm based on a large family of augmented Lagrangian functions and analyze its global convergence properties taking into account the possible infeasibility of the problem. We show that, in a finite number of iterations, the algorithm stops detecting the infeasibility of the problem or finds an approximate feasible/optimal solution with any required precision. We illustrate, by means of numerical experiments, that our algorithm is reliable for different Lagrangian/penalty functions proposed in the literature.
PubDate: 2015-10-01

• Confidence in heuristic solutions?
• Abstract: Abstract Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an intractable objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the corresponding interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test $$p$$ -median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.
PubDate: 2015-10-01

• The Douglas–Rachford algorithm for the case of the sphere and the
line
• Abstract: Abstract In this paper, we solve a conjecture proposed by Borwein and Sims (Fixed-point algorithms for inverse problems in science and engineering, Springer optimization and its applications, 2011) in a Hilbert space setting. For the simple non-convex example of the sphere and the line, the sequence of Douglas–Rachford iterates converges in norm to a point of the intersection except when the initial value belongs to the hyperplane of symmetry.
PubDate: 2015-10-01

• Separable cubic modeling and a trust-region strategy for unconstrained
minimization with impact in global optimization
• Abstract: Abstract A separable cubic model, for smooth unconstrained minimization, is proposed and evaluated. The cubic model uses some novel secant-type choices for the parameters in the cubic terms. A suitable hard-case-free trust-region strategy that takes advantage of the separable cubic modeling is also presented. For the convergence analysis of our specialized trust region strategy we present as a general framework a model $$q$$ -order trust region algorithm with variable metric and we prove its convergence to $$q$$ -stationary points. Some preliminary numerical examples are also presented to illustrate the tendency of the specialized trust region algorithm, when combined with our cubic modeling, to escape from local minimizers.
PubDate: 2015-10-01

• Global optimization of expensive black box functions using potential
Lipschitz constants and response surfaces
• Abstract: Abstract This article develops a novel global optimization algorithm using potential Lipschitz constants and response surfaces (PLRS) for computationally expensive black box functions. With the usage of the metamodeling techniques, PLRS proposes a new approximate function $${\hat{F}}$$ to describe the lower bounds of the real function $$f$$ in a compact way, i.e., making the approximate function $${\hat{F}}$$ closer to $$f$$ . By adjusting a parameter $${\hat{K}}$$ (an estimate of the Lipschitz constant $$K$$ ), $${\hat{F}}$$ could approximate $$f$$ in a fine way to favor local exploitation in some interesting regions; $${\hat{F}}$$ can also approximate $$f$$ in a coarse way to favor global exploration over the entire domain. When doing optimization, PLRS cycles through a set of identified potential estimates of the Lipschitz constant to construct the approximate function from fine to coarse. Consequently, the optimization operates at both local and global levels. Comparative studies with several global optimization algorithms on 53 test functions and an engineering application indicate that the proposed algorithm is promising for expensive black box functions.
PubDate: 2015-10-01

• Smaller SDP for SOS decomposition
• Abstract: Abstract A popular numerical method to compute sum of squares (SOS of polynomials) decompositions for polynomials is to transform the problem into semi-definite programming (SDP) problems and then solve them by SDP solvers. In this paper, we focus on reducing the sizes of inputs to SDP solvers to improve the efficiency and reliability of those SDP based methods. Two types of polynomials, convex cover polynomials and split polynomials, are defined. A convex cover polynomial or a split polynomial can be decomposed into several smaller sub-polynomials such that the original polynomial is SOS if and only if the sub-polynomials are all SOS. Thus the original SOS problem can be decomposed equivalently into smaller sub-problems. It is proved that convex cover polynomials are split polynomials and it is quite possible that sparse polynomials with many variables are split polynomials, which can be efficiently detected in practice. Some necessary conditions for polynomials to be SOS are also given, which can help refute quickly those polynomials which have no SOS representations so that SDP solvers are not called in this case. All the new results lead to a new SDP based method to compute SOS decompositions, which improves this kind of methods by passing smaller inputs to SDP solvers in some cases. Experiments show that the number of monomials obtained by our program is often smaller than that by other SDP based software, especially for polynomials with many variables and high degrees. Numerical results on various tests are reported to show the performance of our program.
PubDate: 2015-10-01

• First order necessary optimality conditions for mathematical programs with
second-order cone complementarity constraints
• Abstract: Abstract This paper is to develop first order necessary optimality conditions for a mathematical program with second-order cone complementarity constraints (MPSCC) which includes the mathematical program with (vector) complementarity constraints (MPCC) as a special case. Like the case of MPCC, Robinson’s constraint qualification fails at every feasible point of MPSCC if we treat the MPSCC as an ordinary optimization problem. Using the formulas of regular and limiting coderivatives and generalized Clarke’s Jacobian of the projection operator onto second-order cones from the literature, we present the S-, M-, C- and A-stationary conditions for a MPSCC problem. Moreover, several constraint qualifications including MPSCC-Abadie CQ, MPSCC-LICQ, MPSCC-MFCQ and MPSCC-GMFCQ are proposed, under which a local minimizer of MPSCC is shown to be a S-, M-, C- or A-stationary point.
PubDate: 2015-10-01

• A scalarization proximal point method for quasiconvex multiobjective
minimization
• Abstract: Abstract In this paper we propose a scalarization proximal point method to solve multiobjective unconstrained minimization problems with locally Lipschitz and quasiconvex vector functions. We prove, under natural assumptions, that the sequence generated by the method is well defined and converges globally to a Pareto-Clarke critical point. Our method may be seen as an extension, for nonconvex case, of the inexact proximal method for multiobjective convex minimization problems studied by Bonnel et al. (SIAM J Optim 15(4):953–970, 2005).
PubDate: 2015-09-30

• On refinement of the unit simplex using regular simplices
• Abstract: Abstract A natural way to define branching in branch and bound (B&B) for blending problems is bisection. The consequence of using bisection is that partition sets are in general irregular. The question is how to use regular simplices in the refinement of the unit simplex. A regular simplex with fixed orientation can be represented by its center and size, facilitating storage of the search tree from a computational perspective. The problem is that a simplex defined in a space with dimension $$n>3$$ cannot be subdivided into regular subsimplices without overlapping. We study the characteristics of the refinement by regular simplices. The main challenge is to find a refinement with a good convergence ratio which allows discarding simplices in an overlapped and already evaluated region. As the efficiency of the division rule in B&B algorithms is instance dependent, we focus on the worst case behaviour, i.e. none of the branches are pruned. This paper shows that for this case surprisingly an overlapping regular refinement may generate less simplices to be evaluated than longest edge bisection. On the other hand, the number of evaluated vertices may be larger.
PubDate: 2015-09-30

• Application of Reduced-set Pareto-Lipschitzian Optimization to truss
optimization
• Abstract: Abstract In this paper, a recently proposed global Lipschitz optimization algorithm Pareto-Lipschitzian Optimization with Reduced-set (PLOR) is further developed, investigated and applied to truss optimization problems. Partition patterns of the PLOR algorithm are similar to those of DIviding RECTangles (DIRECT), which was widely applied to different real-life problems. However here a set of all Lipschitz constants is reduced to just two: the maximal and the minimal ones. In such a way the PLOR approach is independent of any user-defined parameters and balances equally local and global search during the optimization process. An expanded list of other well-known DIRECT-type algorithms is used in investigation and experimental comparison using the standard test problems and truss optimization problems. The experimental investigation shows that the PLOR algorithm gives very competitive results to other DIRECT-type algorithms using standard test problems and performs pretty well on real truss optimization problems.
PubDate: 2015-09-28

• Duality related to approximate proper solutions of vector optimization
problems
• Abstract: Abstract In this work we introduce two approximate duality approaches for vector optimization problems. The first one by means of approximate solutions of a scalar Lagrangian, and the second one by considering $$(C,\varepsilon )$$ -proper efficient solutions of a recently introduced set-valued vector Lagrangian. In both approaches we obtain weak and strong duality results for $$(C,\varepsilon )$$ -proper efficient solutions of the primal problem, under generalized convexity assumptions. Due to the suitable limit behaviour of the $$(C,\varepsilon )$$ -proper efficient solutions when the error $$\varepsilon$$ tends to zero, the obtained duality results extend and improve several others in the literature.
PubDate: 2015-09-25

• A class of shrinking projection extragradient methods for solving
non-monotone equilibrium problems in Hilbert spaces
• Abstract: Abstract A new class of extragradient-type methods is introduced for solving an equilibrium problem in a real Hilbert space without any monotonicity assumption on the equilibrium function. The strategy is to replace the second projection step in the classical extragradient method by a projection onto shrinking convex subsets of the feasible set. Furthermore, to ensure a sufficient decrease on the equilibrium function, a general Armijo-type condition is imposed. This condition is shown to be satisfied for four different linesearches used in the literature. Then, the weak and strong convergence of the resulting algorithms is obtained under non-monotonicity assumptions. Finally, some numerical experiments are reported.
PubDate: 2015-09-23

• Some feasibility sampling procedures in interval methods for constrained
global optimization
• Abstract: Abstract Three feasibility sampling procedures are developed as add-on acceleration strategies in interval methods for solving global optimization problem over a bounded interval domain subject to one or two additional linear constraints. The main features of all three procedures are their abilities to quickly test any sub-domain’s feasibility and to actually locate a feasible point if the feasible set within the sub-domain is nonempty. This add-on feature of feasibility sampling can significantly lower upper bounds of the best objective function value in any interval method and improve its convergence and effectiveness.
PubDate: 2015-09-16

• Heuristics for exact nonnegative matrix factorization
• Abstract: Abstract The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n nonnegative matrix X and a factorization rank r, find, if possible, an m-by-r nonnegative matrix W and an r-by-n nonnegative matrix H such that $$X = WH$$ . In this paper, we propose two heuristics for exact NMF, one inspired from simulated annealing and the other from the greedy randomized adaptive search procedure. We show empirically that these two heuristics are able to compute exact nonnegative factorizations for several classes of nonnegative matrices (namely, linear Euclidean distance matrices, slack matrices, unique-disjointness matrices, and randomly generated matrices) and as such demonstrate their superiority over standard multi-start strategies. We also consider a hybridization between these two heuristics that allows us to combine the advantages of both methods. Finally, we discuss the use of these heuristics to gain insight on the behavior of the nonnegative rank, i.e., the minimum factorization rank such that an exact NMF exists. In particular, we disprove a conjecture on the nonnegative rank of a Kronecker product, propose a new upper bound on the extension complexity of generic n-gons and conjecture the exact value of (i) the extension complexity of regular n-gons and (ii) the nonnegative rank of a submatrix of the slack matrix of the correlation polytope.
PubDate: 2015-09-05

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