In recent years, crowdsourcing has gradually become a promising way of using netizens to accomplish tiny tasks on, or even complex works through crowdsourcing workflows that decompose them into tiny ones to publish se...
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In recent years, crowdsourcing has gradually become a promising way of using netizens to accomplish tiny tasks on, or even complex works through crowdsourcing workflows that decompose them into tiny ones to publish sequentially on the crowdsourcing platforms. One of the significant challenges in this process is how to determine the parameters for task publishing. Still some technique applied constraint solving to select the optimal tasks parameters so that the total cost of completing all tasks is minimized However, experimental results show that computational complexity makes these tools unsuitable for solving large-scale problems because of its excessive execution time. Taking into account the real-time requirements of crowdsourcing, this study uses a heuristic algorithm with four heuristic strategies to solve the problem in order to reduce execution time. The experiment results also show that the proposed heuristic strategies produce good quality approximate solutions in an acceptable timeframe.
The ornamental horticultural industry continues to be one of the most rapidly expanding sectors in agriculture. This study examined a decision model for landscape plant production based on portfolio analysis. A quadra...
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The ornamental horticultural industry continues to be one of the most rapidly expanding sectors in agriculture. This study examined a decision model for landscape plant production based on portfolio analysis. A quadratic programming model was developed to generate an optimal crop portfolio for a selected southeastern nursery. Empirical results indicate opportunities exist for modest diversification to offset income variability in landscape plant production and marketing.
In this paper, we introduce an O(N) algorithm for the computation of the centroidal momentum matrix (CMM) and its time derivative using spatial algebra and expressed with Lie algebra operators. The proposed algorithm ...
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In this paper, we introduce an O(N) algorithm for the computation of the centroidal momentum matrix (CMM) and its time derivative using spatial algebra and expressed with Lie algebra operators. The proposed algorithm is applied to the postural balance of a humanoid robot using whole body control with quadratic programming. The employed tasks only require the CMM and its time derivative without the need of the joint space inertia matrix and the Coriolis terms reducing this way the computational cost of the controller. Finally, four simulation scenarios programmed in Julia are considered where several perturbations for the balance of the robot have been taken into account and according to the tracking graphs of the center of mass, centroidal momentum and the trajectories of the center of pressure it is concluded that the performance of the proposed algorithm is satisfactory.
This work is concerned with a mechanical model of a sympodial tree with first-level branches, which has been shown to exhibit certain properties potentially suitable for biomimetic applications. To investigate these p...
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This work is concerned with a mechanical model of a sympodial tree with first-level branches, which has been shown to exhibit certain properties potentially suitable for biomimetic applications. To investigate these potential benefits further from the viewpoint of the system nonlinear behavior under external periodic excitation, modern numerical tools related to the concept of dynamical integrity are either adjusted or newly developed for this system for the first time. First, multistable regions of interest are isolated from bifurcation diagrams and the effect of damping is investigated. Then, in order to obtain the corresponding basins of attraction of this highly dimensional model, an original computational procedure is developed that includes cell mapping with 40(6) cells, where each cell represents an initial condition required to construct the map. Full 6D basins are computed, and they are reported for various values of the damping parameter and the excitation frequency. Those basins are then used to calculate the dynamic integrity factors so that the dominant steady-state can be determined. Finally, the integrity profiles are reported to illustrate how the robustness varies by changing the system parameters.
In this paper we develop an analytical set of equations to describe the motion of discrete dynamical systems subjected to holonomic and/or nonholonomic Pfaffian equality constraints. These equations are obtained by us...
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In this paper we develop an analytical set of equations to describe the motion of discrete dynamical systems subjected to holonomic and/or nonholonomic Pfaffian equality constraints. These equations are obtained by using Gauss's Principle to recast the problem of the constrained motion of dynamical systems in the form of a quadratic programming problem. The closed-form solution to this programming problem then explicitly yields the equations that describe the time evolution of constrained linear and nonlinear mechanical systems. The direct approach used here does not require the use of any Lagrange multipliers, and the resulting equations are expressed in terms of two different classes of generalized inverses-the first class pertinent to the constraints, the second to the dynamics of the motion. These equations can be numerically solved using any of the standard numerical techniques for solving differential equations. A closed-form analytical expression for the constraint forces required for a given mechanical system to satisfy a specific set of nonholonomic constraints is also provided. An example dealing with the position tracking control of a nonlinear system shows the power of the analytical results and provides new insights into application areas such as robotics, and the control of structural and mechanical systems.
Active feedback stabilization of the dominant resistive wall mode (RWM) for an ITER H-mode scenario at high plasma pressure using infinite-horizon model predictive control (MPC) is presented. The MPC approach is close...
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Active feedback stabilization of the dominant resistive wall mode (RWM) for an ITER H-mode scenario at high plasma pressure using infinite-horizon model predictive control (MPC) is presented. The MPC approach is closely-related to linear-quadratic-Gaussian (LQG) control, improving the performance in the vicinity of constraints. The control-oriented model for MPC is obtained with model reduction from a high-dimensional model produced by CarMa code. Due to the limited time for on-line optimization, a suitable MPC formulation considering only input (coil voltage) constraints is chosen, and the primal fast gradient method is used for solving the associated quadratic programming problem. The performance is evaluated in simulation in comparison to LQG control. Sensitivity to noise, robustness to changes of unstable RWM dynamics, and size of the domain of attraction of the initial conditions of the unstable modes are examined.
In this paper, an optimization-based computational framework for the spatial tailoring of a metal-ceramic composite panel subjected to high-speed flow is discussed. The framework includes the modeling, evaluation, and...
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In this paper, an optimization-based computational framework for the spatial tailoring of a metal-ceramic composite panel subjected to high-speed flow is discussed. The framework includes the modeling, evaluation, and optimization of the spatial material grading and thermostructural response of the metal-ceramic composites over a wide range of temperatures. The framework relies on micromechanics and a finite-element analysis (FEA) of representative volume elements (RVEs) to obtain the overall elastic, thermoelastic, and thermal properties of the graded microstructure as functions of temperature and spatial position. The effective thermostructural response of the airframe is analyzed using the FEA. The time-dependent thermal and structural loads are representative of a characteristic high-speed trajectory. Optimal multivariable material distribution is determined numerically using a constrained sequential quadratic programming (SQP) method of surrogate models to evaluate the response at multiple design locations efficiently. Three example cases are presented to showcase the developed framework. Tn all three example cases, optimal material variation and panel thickness are found such that they reduce the section mass when compared to a benchmark titanium (Ti-6Al-4V) structural skin and Acusill II thermal protection system (TPS) solution. Furthermore, these studies demonstrate that the use of metal-ceramic spatially tailored materials makes excellent material choices for operation in the high-speed environment. (C) 2020 American Society of Civil Engineers.
We identify a source of numerical instability of quadratic programming problems that is hidden in its linear equality constraints. We propose a new theoretical approach to rewrite the original optimization problem in ...
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We identify a source of numerical instability of quadratic programming problems that is hidden in its linear equality constraints. We propose a new theoretical approach to rewrite the original optimization problem in an equivalent reformulation using the singular value decomposition and substituting the ill-conditioned original matrix of the restrictions with a suitable optimally conditioned one. The proposed novel approach is showed, both empirically and theoretically, to solve ill-conditioning related numerical issues, not only when they depend on bad scaling and are relative easy to handle, but also when they result from almost collinearity or when numerically rank-deficient matrices are involved. Furthermore, our strategy looks very promising even when additional inequality constraints are considered in the optimization problem, as it occurs in several practical applications. In this framework, even if no closed form solution is available, we show, through empirical evidence, how the equivalent reformulation of the original problem greatly improves the performances of MatLab (R)'s quadratic programming solver and Gurobi (R). The experimental validation is provided through numerical examples performed on real financial data in the portfolio optimization context.
The paper investigates strategies for expansion of active set that can be employed by the MPRGP algorithm. The standard MPRGP expansion uses a projected line search in the free gradient direction with a fixed step len...
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The paper investigates strategies for expansion of active set that can be employed by the MPRGP algorithm. The standard MPRGP expansion uses a projected line search in the free gradient direction with a fixed step length. Such a scheme is often too slow to identify the active set, requiring a large number of expansions. We propose to use adaptive step lengths based on the current gradient, which guarantees the decrease of the unconstrained cost function with different gradient-based search directions. Moreover, we also propose expanding the active set by projecting the optimal step for the unconstrained minimization. Numerical experiments demonstrate the benefits (up to 78% decrease in the number of Hessian multiplications) of our expansion step modifications on two benchmarks - contact problem of linear elasticity solved by TFETI and machine learning problems of SVM type, both implemented in PERMON toolbox.
作者：
Kristan TemmeCenter for Theoretical Physics
Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA and IQIM California Institute of Technology Pasadena California 91125 USA
We show that it is impossible to obtain a quantum speedup for a faulty Hamiltonian oracle. The effect of dephasing noise to this continuous-time oracle model has first been investigated by Shenvi, Brown, and Whaley [P...
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We show that it is impossible to obtain a quantum speedup for a faulty Hamiltonian oracle. The effect of dephasing noise to this continuous-time oracle model has first been investigated by Shenvi, Brown, and Whaley [Phys. Rev. A 68, 052313 (2003).]. The authors consider a faulty oracle described by a continuous-time master equation that acts as dephasing noise in the basis determined by the marked item. The analysis focuses on the implementation with a particular driving Hamiltonian. A universal lower bound for this oracle model, which rules out a better performance with a different driving Hamiltonian, has so far been lacking. Here, we derive an adversary-type lower bound which shows that the evolution time T has to be at least in the order of N, i.e., the size of the search space, when the error rate of the oracle is constant. This means that quadratic quantum speedup vanishes and the runtime assumes again the classical scaling. For the standard quantum oracle model this result was first proven by Regev and Schiff [in Automata, Languages and programming, Lecture Notes in Computer Science Vol. 5125 (Springer, Berlin, 2008), pp. 773–781]. Here, we extend this result to the continuous-time setting.
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