In elastic optical networks (EONs) employing weakly coupled single-mode multi-core fibers (MCFs), inter-core crosstalk (XT) can affect significantly the network performance, particularly when the number of cores and t...
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In elastic optical networks (EONs) employing weakly coupled single-mode multi-core fibers (MCFs), inter-core crosstalk (XT) can affect significantly the network performance, particularly when the number of cores and the path length increase. Hence, from the network perspective, the impairment-aware routing, spectrum and core assignment (IA-RSCA) problem is the most important concern of MCF-EONs. In this paper, we propose a XT-aware greedy algorithm to minimize the XT impact on the MCF-EONs performance. To achieve the XT impact minimization, we decompose the IA-RSCA problem into two sub-problems: the IA routing sub-problem and the IA spectrum and core assignment (IA-SCA) sub-problem. For the routing solution, a pre-computation method based on the k-shortest path is used, and a physical layer impairment verification phase is performed taking the required optical signal to noise ratio into account. For the IA-SCA sub-problem, the novel XT-aware greedy algorithm is used to minimize the XT impact on the MCF-EONs performance as follows: for each new connection, the level of detected XT power of the new connection and interfering connections relative to the XT power threshold of each connection is minimized on the average over all those connections. This minimization is achieved by choosing the core and frequency slot of the new connection. In order to take the spectral overlapping extension of the new and interfering connections into account in the detected XT power, a novel frequency slot overlapping index is introduced. The performance of the proposed algorithm is evaluated through computer simulations. The results show that the total blocking probability and network average utilization achieved by the proposed algorithm are better than the ones obtained by core prioritization, random and first-fit strategies, for different scenarios of XT level and spectrum fragmentation.
greedy algorithms have attracted considerable interest for sparse signal recovery (SSR) due to their appealing efficiency and performance recently. However, conventional greedy algorithms utilize the l(2) norm based l...
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greedy algorithms have attracted considerable interest for sparse signal recovery (SSR) due to their appealing efficiency and performance recently. However, conventional greedy algorithms utilize the l(2) norm based loss function and suffer from severe performance degradation in the presence of gross corruption and outliers. Furthermore, they cannot be directly applied to the recovery of quaternion sparse signals due to the noncommutativity of quaternion multiplication. To alleviate these problems, we propose a robust greedy algorithm referred as Cauchy matching pursuit (CauchyMP) for SSR and extend it for quaternion SSR. By leveraging the Cauchy estimator and generalizing it to the quaternion space to measure the residual error, our method can robustly recover the sparse signal in both real and quaternion space from noisy data corrupted by various severe noises and outliers. To tackle the resulting quaternion optimization problem, we develop an efficient half-quadratic optimization algorithm by introducing two quaternion operators. In addition, we have also devised a CauchyMP based classifier termed CauchyMPC for robust multiclass classification. The experiments on both synthetic and real-world datasets validate the efficacy and robustness of the proposed methods for SSR, block SSR, quaternion SSR and multiclass classification. (C) 2019 Elsevier B.V. All rights reserved.
In the context of increasing flexible load represented by smart household appliances, this study aims to establish a demand response model of residential flexible load to minimize electricity cost and reduce grid load...
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In the context of increasing flexible load represented by smart household appliances, this study aims to establish a demand response model of residential flexible load to minimize electricity cost and reduce grid load variance. In this study, the flexible loads of residents are classified considering different load demand response modes, and demand response models are established for all kinds of loads. To make full use of residential electricity data, this paper established a user side flexible load multi -objective optimization scheduling model, the model for electricity cost and power grid load variance minimizing the objective function, and the safe operation of the meter and the adjustable resources as constraint, load and energy storage battery time-sharing electricity price for resident's flexible optimization scheduling. Finally, the greedy algorithm is use to calculate and analyze the model. The result show that the model is effective and feasible.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
The regular periodicity of astronomical tides allows their accurate prediction, and so it should be possible to determine how best to optimise the future distribution of arrays of tidal energy devices for any shelf se...
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The regular periodicity of astronomical tides allows their accurate prediction, and so it should be possible to determine how best to optimise the future distribution of arrays of tidal energy devices for any shelf sea region. By considering together the magnitude and phase of tidal currents over a shelf sea region, maximum aggregated power generation, with minimal periods of low generation, can be deduced. Here, we make use of the greedy algorithm to optimise future exploitation of the tidal stream resource over the northwest European shelf seas, a region which contains a world-leading tidal energy resource. We also apply a penalty function to the greedy algorithm, favouring the selection of future hypothetical sites where power generation would be out-of-phase with previously developed sites. Our results demonstrate that the Pentland Firth and Channel Islands would be optimal sites for parallel development for relatively low numbers of arrays, with important contributions from the Irish Sea for larger scale exploitation. Although there is minimal phase diversity between European tidal stream sites to deliver firm power generation, it is possible that the vertical tide could contribute to such baseload through the parallel development of lagoons or impoundments. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/3.0/).
Task allocation is a key issue in multi-agent systems, and finding the optimal strategy for task allocation has been proved to be an NP-hard problem. Existing task allocation methods for multi-agent systems mainly ado...
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Task allocation is a key issue in multi-agent systems, and finding the optimal strategy for task allocation has been proved to be an NP-hard problem. Existing task allocation methods for multi-agent systems mainly adopt distributed full search strategies or local search strategies. The former requires a lot of computation and communication costs, while the latter cannot ensure the diversity and quality of solutions. Therefore, in this paper, we combine a distributed many-objective evolutionary algorithm called D-NSGA3 with a greedy algorithm to search the task allocation solutions, and we comprehensively consider the constraints related to space, time, energy consumption and agent function in multi-agent systems. Specifically, D-NSGA3 is used to optimize multiple objectives simultaneously so as to ensure the search capability and the diversity of solutions. Alternate search between D-NSGA3 and the greedy algorithm is conducted to enhance the local optimizing ability. Experimental results show that the proposed method can effectively solve large-scale task allocation problems (e.g., the number of agents is not less than 250, and that of tasks is not less than 1000). Compared with the existing work called MSEA, the proposed method could achieve better and more diverse solutions.
We study a disturbed variant of the classical greedy algorithm for weight functions defined on some given finite set E and show that the greedy algorithm for matroids is stable with respect to changes in the input dat...
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We study a disturbed variant of the classical greedy algorithm for weight functions defined on some given finite set E and show that the greedy algorithm for matroids is stable with respect to changes in the input data. (C) 1999 Elsevier Science Ltd. All rights reserved.
An efficient method for solving the classical NP-hard problem of scheduling theory for one device-the problem of minimizing the total delay 1 parallel to Sigma T-j-is presented. An algorithm for solving the problem is...
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An efficient method for solving the classical NP-hard problem of scheduling theory for one device-the problem of minimizing the total delay 1 parallel to Sigma T-j-is presented. An algorithm for solving the problem is proposed based on the decomposition of the original problem into subproblems of timely servicing each of the requests and placing those of them for which the increase in the delay is most compensated for by the reduction in the delay of the previous requests at the end of the schedules. The complexity of the algorithm does not exceed O (n(2)) operations, where n is the number of requests.
Phasor measurement units (PMUs) provide synchronized measurements of real-time phasors of voltages and currents. It is considered as an important element of the smart wide area measurement system used in advanced powe...
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Phasor measurement units (PMUs) provide synchronized measurements of real-time phasors of voltages and currents. It is considered as an important element of the smart wide area measurement system used in advanced power system monitoring, protection, and control applications. This paper proposes a new approach based on a greedy algorithm to solve the optimal phasor measurement unit placement (OPP) problem in the power network. The main purpose of proposed approach is to find out a high-quality solution in a reasonable time that ensures the practicability when applying for a real power network. The OPP problem is solved under both normal operating and contingency conditions. Moreover, some other realistic aspects that may affect the OPP problem, such as PMU channel limitation, zero injection bus, the presence of conventional measurements, are also considered to solve simultaneously. The simulations on IEEE 14-bus, 30-bus, 57-bus, 118-bus test systems, and especially on a large-scale network-the Polish 2383-bus system, are presented for evaluating the feasibility of proposed approach. The results of this study showed that the proposed method is effective and feasible to solve the OPP problem for a real power network.
In this paper, a method for approximating a multi-input multi-output (MIMO) transfer function by a causal finite-impulse response (FIR) paraunitary (PU) system in a weighted least-squares sense is presented. Using a c...
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In this paper, a method for approximating a multi-input multi-output (MIMO) transfer function by a causal finite-impulse response (FIR) paraunitary (PU) system in a weighted least-squares sense is presented. Using a complete parameterization of FIR PU systems in terms of Householder-like building blocks, an iterative algorithm is proposed that is greedy in the sense that the observed mean-squared error at each iteration is guaranteed to not increase. For certain design problems in which there is a phase-type ambiguity in the desired response, which is formally defined in the paper, a phase feedback modification is proposed in which the phase of the FIR approximant is fed back to the desired response. With this modification in effect, it is shown that the resulting iterative algorithm not only still remains greedy, but also offers a better magnitude-type fit to the desired response. Simulation results show the usefulness and versatility of the proposed algorithm with respect to the design of principal component filter bank (PCFB)-like filter banks and the FIR PU interpolation problem. Concerning the PCFB design problem, it is shown that as the McMillan degree of the FIR PU approximant increases, the resulting filter bank behaves more and more like the infinite-order PCFB, consistent with intuition. In particular, this PCFB-like behavior is shown in terms of filter response shape, multiresolution, coding gain, noise reduction with zeroth- order Wiener filtering in the subbands, and power minimization for discrete multitone (DMT)-type transmultiplexers.
With the rapid development of civil aviation in recent years,the management and assignment of airport resources are becoming more and more *** the various airport resources,gates and taxiways are very important,theref...
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With the rapid development of civil aviation in recent years,the management and assignment of airport resources are becoming more and more *** the various airport resources,gates and taxiways are very important,therefore,many researchers focus on the airport gate and taxiway assignment ***,the joint assignment algorithm of airport gates and taxiways with realistic airport data has not been well studied.A greedy algorithm based on joint assignment of airport gates and taxiways using the data of a large hub airport in China is *** objective is maximizing the ratio of fixed gates and minimizing the ratio of taxiway *** results show that it outperforms other assignment schemes.
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