1,191,505 research outputs found

    On the Selection of Optimal Index Configuration in OO Databases

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    An operation in object-oriented databases gives rise to the processing of a path. Several database operations may result into the same path. The authors address the problem of optimal index configuration for a single path. As it is shown an optimal index configuration for a path can be achieved by splitting the path into subpaths and by indexing each subpath with the optimal index organization. The authors present an algorithm which is able to select an optimal index configuration for a given path. The authors consider a limited number of existing indexing techniques (simple index, inherited index, nested inherited index, multi-index, and multi-inherited index) but the principles of the algorithm remain the same adding more indexing technique

    Optimal Path to Epigenetic Switching

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    We use large deviation methods to calculate rates of noise-induced transitions between states in multistable genetic networks. We analyze a synthetic biochemical circuit, the toggle switch, and compare the results to those obtained from a numerical solution of the master equation.Comment: 5 pages. 2 figures, uses revtex 4. PR-E reviewed for publicatio

    Asymptotic Optimality of a Time Optimal Path Parametrization Algorithm

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    Time Optimal Path Parametrization is the problem of minimizing the time interval during which an actuation constrained agent can traverse a given path. Recently, an efficient linear-time algorithm for solving this problem was proposed. However, its optimality was proved for only a strict subclass of problems solved optimally by more computationally intensive approaches based on convex programming. In this paper, we prove that the same linear-time algorithm is asymptotically optimal for all problems solved optimally by convex optimization approaches. We also characterize the optimum of the Time Optimal Path Parametrization Problem, which may be of independent interest

    Optimal execution with rough path signatures

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    We present a method for obtaining approximate solutions to the problem of optimal execution, based on a signature method. The framework is general, only requiring that the price process is a geometric rough path and the price impact function is a continuous function of the trading speed. Following an approximation of the optimisation problem, we are able to calculate an optimal solution for the trading speed in the space of linear functions on a truncation of the signature of the price process. We provide strong numerical evidence illustrating the accuracy and flexibility of the approach. Our numerical investigation both examines cases where exact solutions are known, demonstrating that the method accurately approximates these solutions, and models where exact solutions are not known. In the latter case, we obtain favourable comparisons with standard execution strategies

    Scaling of optimal-path-lengths distribution in complex networks

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    We study the distribution of optimal path lengths in random graphs with random weights associated with each link (``disorder''). With each link ii we associate a weight τi=exp(ari)\tau_i = \exp(ar_i) where rir_i is a random number taken from a uniform distribution between 0 and 1, and the parameter aa controls the strength of the disorder. We suggest, in analogy with the average length of the optimal path, that the distribution of optimal path lengths has a universal form which is controlled by the expression 1pca\frac{1}{p_c}\frac{\ell_{\infty}}{a}, where \ell_{\infty} is the optimal path length in strong disorder (aa \to \infty) and pcp_c is the percolation threshold. This relation is supported by numerical simulations for Erd\H{o}s-R\'enyi and scale-free graphs. We explain this phenomenon by showing explicitly the transition between strong disorder and weak disorder at different length scales in a single network

    Time-Optimal Path Tracking via Reachability Analysis

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    Given a geometric path, the Time-Optimal Path Tracking problem consists in finding the control strategy to traverse the path time-optimally while regulating tracking errors. A simple yet effective approach to this problem is to decompose the controller into two components: (i)~a path controller, which modulates the parameterization of the desired path in an online manner, yielding a reference trajectory; and (ii)~a tracking controller, which takes the reference trajectory and outputs joint torques for tracking. However, there is one major difficulty: the path controller might not find any feasible reference trajectory that can be tracked by the tracking controller because of torque bounds. In turn, this results in degraded tracking performances. Here, we propose a new path controller that is guaranteed to find feasible reference trajectories by accounting for possible future perturbations. The main technical tool underlying the proposed controller is Reachability Analysis, a new method for analyzing path parameterization problems. Simulations show that the proposed controller outperforms existing methods.Comment: 6 pages, 3 figures, ICRA 201
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