Successive linear programming (SLP) is a practical approach for solving large-scale nonlinear optimization problems. Alternating current optimal power flow (ACOPF) is no exception, particularly the large size of real ...
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Successive linear programming (SLP) is a practical approach for solving large-scale nonlinear optimization problems. Alternating current optimal power flow (ACOPF) is no exception, particularly the large size of real world networks. However, in order to achieve tractability, it is essential to tune the SLP algorithm presented in the literature. This paper presents a modified SLP algorithm to solve the ACOPF problem, specified by the U.S. Department of Energy's (DOE) Grid Optimization (GO) Competition Challenge 1, within strict time limits. The algorithm first finds a near-optimal solution for the relaxed problem (i.e., Stage 1). Then, it finds a feasible solution in the proximity of the near-optimal solution (i.e., Stage 2 and Stage 3). The numerical experiments on test cases ranging from 500-bus to 30,000-bus systems show that the algorithm is tractable. The results show that our proposed algorithm is tractable and can solve more than 80% of test cases faster than the well-known Interior Point Method while significantly reduce the number of iterations required to solve ACOPF. The number of iterations is considered an important factor in the examination of tractability which can drastically reduce the computational time required within each iteration.
We study the tractability frontier of outlier detection problems, by analyzing it with respect to (i) the considered outlier detection problem, (ii) the reference default logic fragment, and (iii) the adopted notion o...
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We study the tractability frontier of outlier detection problems, by analyzing it with respect to (i) the considered outlier detection problem, (ii) the reference default logic fragment, and (iii) the adopted notion of outlier. As for point (i), we shall consider three problems of increasing complexity, called Outlier-Witness Recognition, Outlier Recognition and Outlier Existence, respectively. As for point (ii), as we look for conditions under which outlier detection can be done efficiently, attention will be limited to subsets of Disjunction-free propositional default theories. As for point (iii), we shall refer to both the notion of outlier introduced in [3] and a new and more restrictive one, called strong outlier. We also present a polynomial time algorithm for enumerating all strong outliers of bounded size in a quasi-acyclic normal unary default theory. Some of our tractability results rely on the Incremental Lemma that provides conditions for a default logic fragment to have a monotonic behavior. Finally, in order to show that the simple fragments of DL we deal with are still rich enough to solve interesting problems and, therefore, that the tractability results that we prove are interesting not merely on the theoretical side, insights into the expressive capabilities of these fragments are provided, by showing that normal unary theories express all NL queries, hereby indirectly answering a question raised by Kautz and Selman [16]. (C) 2014 Elsevier B.V. All rights reserved.
We develop a tractable algorithms for finding the optimal power spectral density of the Gaussian input excitation for identifying a Wiener model. This problem is known as a difficult problem for two reasons. Firstly, ...
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Algorithm-to-hardware High-Level Synthesis (HLS) tools are becoming increasingly practical, particularly the domain specific approaches to HLS. Storage allocation is an important step in HLS where variables are mapped...
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ISBN:
(纸本)9781479964925
Algorithm-to-hardware High-Level Synthesis (HLS) tools are becoming increasingly practical, particularly the domain specific approaches to HLS. Storage allocation is an important step in HLS where variables are mapped to onchip storage structures (OSS). HLS flows almost exclusively do this allocation to random access OSS whereas custom designers often pick from a repertoire of intuitive algorithm-appropriate OSS. In this work, revisiting a sparsely addressed problem of storage allocation to sequential access OSS, we report tractable algorithms for storage allocation to three kinds of sequential access style memories-Queue, Queue-Read Sequential-Write memory (QRSWM), and Sequential-Read Sequential-Write memory (SRSWM)-suitable for domains such as signal processing and matrix computations. A basic C to Verilog HLS flow was developed integrating these new allocations options to evaluate their impact on the overall design metrics of interest such as area and power. On application cases such as matrix multiplication and 2D/3D wavelet filtering, a comparison vis-a-vis RAM shows significant improvements in power consumption when targeting TSMC 0.18 mu technology.
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