Genetic algorithm and neural network hybrid approach for job-shop scheduling

Copyright @ 1998 ACTA PressThis paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and the speed of calculation.This research is supported by the National Nature Science Foundation and National High -Tech Program of P. R. China

Evidence for very strong electron-phonon coupling in YBa_{2}Cu_{3}O_{6}

From the observed oxygen-isotope shift of the mid-infrared two-magnon absorption peak of YBa$_{2}$Cu$_{3}$O$_{6}$, we evaluate the oxygen-isotope effect on the in-plane antiferromagnetic exchange energy $J$. The exchange energy $J$ in YBa$_{2}$Cu$_{3}$O$_{6}$ is found to decrease by about 0.9% upon replacing $^{16}$O by $^{18}$O, which is slightly larger than that (0.6%) in La$_{2}$CuO$_{4}$. From the oxygen-isotope effects, we determine the lower limit of the polaron binding energy, which is about 1.7 eV for YBa$_{2}$Cu$_{3}$O$_{6}$ and 1.5 eV for La$_{2}$CuO$_{4}$, in quantitative agreement with angle-resolved photoemission data, optical conductivity data, and the parameter-free theoretical estimate. The large polaron binding energies in the insulating parent compounds suggest that electron-phonon coupling should also be strong in doped superconducting cuprates and may play an essential role in high-temperature superconductivity.Comment: 4 pages, 1 figur

Probing Dark Energy Dynamics from Current and Future Cosmological Observations

We report the constraints on the dark energy equation-of-state w(z) using the latest 'Constitution' SNe sample combined with the WMAP5 and SDSS data. Based on the localized principal component analysis and the model selection criteria, we find that the LCDM model is generally consistent with the current data, yet there exists weak hint of the possible dynamics of dark energy. In particular, a model predicting w(z)-1 at z\in[0.5,0.75), which means that w(z) crosses -1 in the range of z\in[0.25,0.75), is mildly favored at 95% confidence level. Given the best fit model for current data as a fiducial model, we make future forecast from the joint data sets of JDEM, Planck and LSST, and we find that the future surveys can reduce the error bars on the w bins by roughly a factor of 10 for a 5-w-bin model.Comment: Accepted by PRD; minor changes from v

Learning-aided Stochastic Network Optimization with Imperfect State Prediction

We investigate the problem of stochastic network optimization in the presence of imperfect state prediction and non-stationarity. Based on a novel distribution-accuracy curve prediction model, we develop the predictive learning-aided control (PLC) algorithm, which jointly utilizes historic and predicted network state information for decision making. PLC is an online algorithm that requires zero a-prior system statistical information, and consists of three key components, namely sequential distribution estimation and change detection, dual learning, and online queue-based control. Specifically, we show that PLC simultaneously achieves good long-term performance, short-term queue size reduction, accurate change detection, and fast algorithm convergence. In particular, for stationary networks, PLC achieves a near-optimal $[O(\epsilon)$, $O(\log(1/\epsilon)^2)]$ utility-delay tradeoff. For non-stationary networks, \plc{} obtains an $[O(\epsilon), O(\log^2(1/\epsilon)$ $+ \min(\epsilon^{c/2-1}, e_w/\epsilon))]$ utility-backlog tradeoff for distributions that last $\Theta(\frac{\max(\epsilon^{-c}, e_w^{-2})}{\epsilon^{1+a}})$ time, where $e_w$ is the prediction accuracy and $a=\Theta(1)>0$ is a constant (the Backpressue algorithm \cite{neelynowbook} requires an $O(\epsilon^{-2})$ length for the same utility performance with a larger backlog). Moreover, PLC detects distribution change $O(w)$ slots faster with high probability ($w$ is the prediction size) and achieves an $O(\min(\epsilon^{-1+c/2}, e_w/\epsilon)+\log^2(1/\epsilon))$ convergence time. Our results demonstrate that state prediction (even imperfect) can help (i) achieve faster detection and convergence, and (ii) obtain better utility-delay tradeoffs

Kinetic Alfv\'{e}n turbulence below and above ion-cyclotron frequency

Alfv\'{e}nic turbulent cascade perpendicular and parallel to the background magnetic field is studied accounting for anisotropic dispersive effects and turbulent intermittency. The perpendicular dispersion and intermittency make the perpendicular-wavenumber magnetic spectra steeper and speed up production of high ion-cyclotron frequencies by the turbulent cascade. On the contrary, the parallel dispersion makes the spectra flatter and decelerate the frequency cascade above the ion-cyclotron frequency. Competition of the above factors results in spectral indices distributed in the interval [-2,-3], where -2 is the index of high-frequency space-filling turbulence, and -3 is the index of low-frequency intermittent turbulence formed by tube-like fluctuations. Spectra of fully intermittent turbulence fill a narrower range of spectral indices [-7/3,-3], which almost coincides with the range of indexes measured in the solar wind. This suggests that the kinetic-scale turbulent spectra are shaped mainly by dispersion and intermittency. A small mismatch with measured indexes of about 0.1 can be associated with damping effects not studied here.Comment: 9 Pages, 3 Figures, and 2 Table

Observation of enhanced optical spring damping in a macroscopic mechanical resonator and application for parametric instability control in advanced gravitational-wave detectors

We show that optical spring damping in an optomechanical resonator can be enhanced by injecting a phase delay in the laser frequency-locking servo to rotate the real and imaginary components of the optical spring constant. This enhances damping at the expense of optical rigidity. We demonstrate enhanced parametric damping which reduces the Q factor of a 0.1-kg-scale resonator from 1.3×10^5 to 6.5×10^3. By using this technique adequate optical spring damping can be obtained to damp parametric instability predicted for advanced laser interferometer gravitational-wave detectors

Leptonic decay of Heavy-light Mesons in a QCD Potential Model

We study the masses and decay constants of heavy-light flavour mesons D, Ds, B and Bs in a QCD Potential model. The mesonic wavefunction is used to compute the masses of D and B mesons in the ground state and the wavefunction is transformed to momentum space to estimate the pseudoscalar decay constants of these mesons. The leptonic decay widths and branching ratio of these mesons for different leptonic channels are also computed to compare with the experimental values. The results are found to be compatible with available data.Comment: 9 pages,3 table

From Jeff=1/2 insulator to p-wave superconductor in single-crystal Sr2Ir1-xRuxO4 (0 < x< 1)

Sr2IrO4 is a magnetic insulator assisted by strong spin-orbit coupling (SOC) whereas the Sr2RuO4 is a p-wave superconductor. The contrasting ground states have been shown to result from the critical role of the strong SOC in the iridate. Our investigation of structural, transport, and magnetic properties reveals that substituting 4d Ru4+ (4d4) ions for 5d Ir4+(5d5) ions in Sr2IrO4 directly adds holes to the t2g bands, reduces the SOC and thus rebalances the competing energies in single-crystal Sr2Ir1-xRuxO4. A profound effect of Ru doping driving a rich phase diagram is a structural phase transition from a distorted I41/acd to a more ideal I4/mmm tetragonal structure near x=0.50 that accompanies a phase transition from an antiferromagnetic-insulating state to a paramagnetic-metal state. We also make a comparison drawn with Rh doped Sr2IrO4, highlighting important similarities and differences.Comment: 18 pages,7 figure