The spectral analysis of cyclo-non-stationary signals

Science.gov (United States)

Abboud, D.; Baudin, S.; Antoni, J.; Rémond, D.; Eltabach, M.; Sauvage, O.

2016-06-01

Condition monitoring of rotating machines in speed-varying conditions remains a challenging task and an active field of research. Specifically, the produced vibrations belong to a particular class of non-stationary signals called cyclo-non-stationary: although highly non-stationary, they contain hidden periodicities related to the shaft angle; the phenomenon of long term modulations is what makes them different from cyclostationary signals which are encountered under constant speed regimes. In this paper, it is shown that the optimal way of describing cyclo-non-stationary signals is jointly in the time and the angular domains. While the first domain describes the waveform characteristics related to the system dynamics, the second one reveals existing periodicities linked to the system kinematics. Therefore, a specific class of signals - coined angle-time cyclostationary is considered, expressing the angle-time interaction. Accordingly, the related spectral representations, the order-frequency spectral correlation and coherence functions are proposed and their efficiency is demonstrated on two industrial cases.

Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags

Science.gov (United States)

ZHAO, Ning; YE, Song; LI, Kaidian; CHEN, Siyu

2017-05-01

Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.

On the dynamics of non-stationary binary stellar systems

International Nuclear Information System (INIS)

Bekov, A. A.; Bejsekov, A.N.; Aldibaeva, L.T.

2005-01-01

The motion of test body in the external gravitational field of the binary stellar system with slowly variable some physical parameters of radiating components is considered on the base of restricted non-stationary photo-gravitational three and two bodies problem. The family of polar and coplanar solutions are obtained. These solutions give the possibility of the dynamical and structure interpretation of the binary young evolving stars and galaxies. (author)

Non-stationary covariance function modelling in 2D least-squares collocation

Science.gov (United States)

Darbeheshti, N.; Featherstone, W. E.

2009-06-01

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non- stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.

A non-permutation flowshop scheduling problem with lot streaming: A Mathematical model

Directory of Open Access Journals (Sweden)

Daniel Rossit

2016-06-01

Full Text Available In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems. The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines. In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming. Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied. The benefits grow as the number of stages in the production process increases but reach a limit. Beyond a certain point, the division of jobs into additional sublots does not improve the solution.

Optimal inventory policies with non-stationary supply disruptions and advance supply information

NARCIS (Netherlands)

Atasoy, B.; Güllü, R.; Tan, T.

2012-01-01

We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages – and hence supply disruption to (some of) her customers

Optimal inventory policies with non-stationary supply disruptions and advance supply information

NARCIS (Netherlands)

Atasoy, B.; Güllü, R.; Tan, T.

2011-01-01

We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages -and hence supply disruption to (some of) her customers-

Non-stationary condition monitoring through event alignment

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik; Larsen, Jan

2004-01-01

We present an event alignment framework which enables change detection in non-stationary signals. change detection. Classical condition monitoring frameworks have been restrained to laboratory settings with stationary operating conditions, which are not resembling real world operation....... In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...... Analysis or Gaussian Processes modeling. We are especially interested in the true performance of the condition monitoring performance with mixed aligned and unaligned data, e.g. detection of fault condition of unaligned examples versus false alarms of aligned normal condition data. Further, we expect...

Scheduling Non-Preemptible Jobs to Minimize Peak Demand

Directory of Open Access Journals (Sweden)

Sean Yaw

2017-10-01

Full Text Available This paper examines an important problem in smart grid energy scheduling; peaks in power demand are proportionally more expensive to generate and provision for. The issue is exacerbated in local microgrids that do not benefit from the aggregate smoothing experienced by large grids. Demand-side scheduling can reduce these peaks by taking advantage of the fact that there is often flexibility in job start times. We focus attention on the case where the jobs are non-preemptible, meaning once started, they run to completion. The associated optimization problem is called the peak demand minimization problem, and has been previously shown to be NP-hard. Our results include an optimal fixed-parameter tractable algorithm, a polynomial-time approximation algorithm, as well as an effective heuristic that can also be used in an online setting of the problem. Simulation results show that these methods can reduce peak demand by up to 50% versus on-demand scheduling for household power jobs.

Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates

DEFF Research Database (Denmark)

Han, Heejoon; Kristensen, Dennis

as captured by its long-memory parameter dx; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE'’s of the regression coefficients entering the volatility equation are consistent and normally distributed in large samples independently of the degree of persistence....... This implies that standard inferential tools, such as t-statistics, do not have to be adjusted to the level of persistence. On the other hand, the intercept in the volatility equation is not identifi…ed when the covariate is non-stationary which is akin to the results of Jensen and Rahbek (2004, Econometric...

A note on a model for quay crane scheduling with non-crossing constraints

DEFF Research Database (Denmark)

Santini, Alberto; Friberg, Henrik Alsing; Røpke, Stefan

2015-01-01

This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced. Computatio......This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced...

Staffing a call center with uncertain non-stationary arrival rate and flexibility

NARCIS (Netherlands)

Liao, S.; van Delft, C.; Jouini, O.; Koole, G.M.

2012-01-01

We consider a multi-period staffing problem in a single-shift call center. The call center handles inbound calls, as well as some alternative back-office jobs. The call arrival process is assumed to follow a doubly non-stationary stochastic process with a random mean arrival rate. The inbound calls

Non-Stationary Internal Tides Observed with Satellite Altimetry

Science.gov (United States)

Ray, Richard D.; Zaron, E. D.

2011-01-01

Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

Non-stationary reconstruction for dynamic fluorescence molecular tomography with extended kalman filter.

Science.gov (United States)

Liu, Xin; Wang, Hongkai; Yan, Zhuangzhi

2016-11-01

Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.

Production planning of a perishable product with lead time and non-stationary demand

NARCIS (Netherlands)

Pauls-Worm, K.G.J.; Haijema, R.; Hendrix, E.M.T.; Rossi, R.; Vorst, van der J.G.A.J.

2012-01-01

We study a production planning problem for a perishable product with a fixed lifetime, under a service-level constraint. The product has a non-stationary stochastic demand. Food supply chains of fresh products like cheese and several crop products, are characterised by long lead times due to

Integrated network design and scheduling problems :

Energy Technology Data Exchange (ETDEWEB)

Nurre, Sarah G.; Carlson, Jeffrey J.

2014-01-01

We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

STABLE STATIONARY STATES OF NON-LOCAL INTERACTION EQUATIONS

KAUST Repository

FELLNER, KLEMENS

2010-12-01

In this paper, we are interested in the large-time behaviour of a solution to a non-local interaction equation, where a density of particles/individuals evolves subject to an interaction potential and an external potential. It is known that for regular interaction potentials, stable stationary states of these equations are generically finite sums of Dirac masses. For a finite sum of Dirac masses, we give (i) a condition to be a stationary state, (ii) two necessary conditions of linear stability w.r.t. shifts and reallocations of individual Dirac masses, and (iii) show that these linear stability conditions imply local non-linear stability. Finally, we show that for regular repulsive interaction potential Wε converging to a singular repulsive interaction potential W, the Dirac-type stationary states ρ̄ ε approximate weakly a unique stationary state ρ̄ ∈ L∞. We illustrate our results with numerical examples. © 2010 World Scientific Publishing Company.

A Generalized Framework for Non-Stationary Extreme Value Analysis

Science.gov (United States)

Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.

2017-12-01

Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA

Regularized non-stationary morphological reconstruction algorithm for weak signal detection in microseismic monitoring: methodology

Science.gov (United States)

Huang, Weilin; Wang, Runqiu; Chen, Yangkang

2018-05-01

Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.

Dynamics of Inhomogeneous Shell Systems Under Non-Stationary Loading (Survey)

Science.gov (United States)

Lugovoi, P. Z.; Meish, V. F.

2017-09-01

Experimental works on the determination of dynamics of smooth and stiffened cylindrical shells contacting with a soil medium under various non-stationary loading are reviewed. The results of studying three-layer shells of revolution whose motion equations are obtained within the framework of the hypotheses of the Timoshenko geometrically nonlinear theory are stated. The numerical results for shells with a piecewise or discrete filler enable the analysis of estimation of the influence of geometrical and physical-mechanical parameters of structures on their dynamics and reveal new mechanical effects. Basing on the classical theory of shells and rods, the effect of the discrete arrangement of ribs and coefficients of the Winkler or Pasternak elastic foundation on the normal frequencies and modes of rectangular planar cylindrical and spherical shells is studied. The number and shape of dispersion curves for longitudinal harmonic waves in a stiffened cylindrical shell are determined. The equations of vibrations of ribbed shells of revolution on Winkler or Pasternak elastic foundation are obtained using the geometrically nonlinear theory and the Timoshenko hypotheses. On applying the integral-interpolational method, numerical algorithms are developed and the corresponding non-stationary problems are solved. The special attention is paid to the statement and solution of coupled problems on the dynamical interaction of cylindrical or spherical shells with the soil water-saturated medium of different structure.

Non-stationary Markov chains

OpenAIRE

Mallak, Saed

1996-01-01

Ankara : Department of Mathematics and Institute of Engineering and Sciences of Bilkent University, 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves leaf 29 In thi.s work, we studierl the Ergodicilv of Non-Stationary .Markov chains. We gave several e.xainples with different cases. We proved that given a sec[uence of Markov chains such that the limit of this sec|uence is an Ergodic Markov chain, then the limit of the combination ...

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable

A non-stationary cost-benefit analysis approach for extreme flood estimation to explore the nexus of 'Risk, Cost and Non-stationarity'

Science.gov (United States)

Qi, Wei

2017-11-01

Cost-benefit analysis is commonly used for engineering planning and design problems in practice. However, previous cost-benefit based design flood estimation is based on stationary assumption. This study develops a non-stationary cost-benefit based design flood estimation approach. This approach integrates a non-stationary probability distribution function into cost-benefit analysis, and influence of non-stationarity on expected total cost (including flood damage and construction costs) and design flood estimation can be quantified. To facilitate design flood selections, a 'Risk-Cost' analysis approach is developed, which reveals the nexus of extreme flood risk, expected total cost and design life periods. Two basins, with 54-year and 104-year flood data respectively, are utilized to illustrate the application. It is found that the developed approach can effectively reveal changes of expected total cost and extreme floods in different design life periods. In addition, trade-offs are found between extreme flood risk and expected total cost, which reflect increases in cost to mitigate risk. Comparing with stationary approaches which generate only one expected total cost curve and therefore only one design flood estimation, the proposed new approach generate design flood estimation intervals and the 'Risk-Cost' approach selects a design flood value from the intervals based on the trade-offs between extreme flood risk and expected total cost. This study provides a new approach towards a better understanding of the influence of non-stationarity on expected total cost and design floods, and could be beneficial to cost-benefit based non-stationary design flood estimation across the world.

Scalability of Direct Solver for Non-stationary Cahn-Hilliard Simulations with Linearized time Integration Scheme

KAUST Repository

Woźniak, M.; Smołka, M.; Cortes, Adriano Mauricio; Paszyński, M.; Schaefer, R.

2016-01-01

We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme

Heuristic algorithm for single resource constrained project scheduling problem based on the dynamic programming

Directory of Open Access Journals (Sweden)

Stanimirović Ivan

2009-01-01

Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.

Frequency Analysis of Extreme Sub-Daily Precipitation under Stationary and Non-Stationary Conditions across Two Contrasting Hydroclimatic Environments

Science.gov (United States)

Demaria, E. M.; Goodrich, D. C.; Keefer, T.

2017-12-01

Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration Frequency (IDF) curves under stationary and nonstationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5- to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25% for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in storm design.

Noise Diagnostics of Stationary and Non-Stationary Reactor Processes

Energy Technology Data Exchange (ETDEWEB)

Sunde, Carl

2007-04-15

This thesis concerns the application of noise diagnostics on different problems in the area of reactor physics involving both stationary and non-stationary core processes. Five different problems are treated, divided into three different parts. The first problem treated in the first part is the classification of two-phase flow regimes from neutron radiographic and visible light images with a neuro-wavelet algorithm. The algorithm consists of wavelet pre-processing and of an artificial neural network. The result indicates that the wavelet pre-processing is improving the training of the neural network. Next, detector tubes which are suspected of impacting on nearby fuel-assemblies in a boiling water reactor (BWR) are identified by both a classical spectral method and wavelet-based methods. It was found that there is good agreement between the different methods as well as with visual inspections of detector tube and fuel assembly damage made during the outage at the plant. The third problem addresses the determination of the decay ratio of a BWR from the auto-correlation function (ACF). Here wavelets are used, with some success, both for de-trending and de-nosing of the ACF and also for direct estimation of the decay ratio from the ACF. The second part deals with the analysis of beam-mode and shell-mode core-barrel vibrations in pressurised water reactors (PWRs). The beam-mode vibrations are analysed by using parameters of the vibration peaks, in spectra from ex core detectors. A trend analysis of the peak amplitude shows that the peak amplitude is changing during the fuel cycle. When it comes to the analysis of the shell-mode vibration, 1-D analytical and numerical calculations are performed in order to calculate the neutron noise induced in the core. The two calculations are in agreement and show that a large local noise component is present in the core which could be used to classify the shell-mode vibrations. However, a measurement made in the PWR Ringhals-3 shows

Noise Diagnostics of Stationary and Non-Stationary Reactor Processes

International Nuclear Information System (INIS)

Sunde, Carl

2007-01-01

This thesis concerns the application of noise diagnostics on different problems in the area of reactor physics involving both stationary and non-stationary core processes. Five different problems are treated, divided into three different parts. The first problem treated in the first part is the classification of two-phase flow regimes from neutron radiographic and visible light images with a neuro-wavelet algorithm. The algorithm consists of wavelet pre-processing and of an artificial neural network. The result indicates that the wavelet pre-processing is improving the training of the neural network. Next, detector tubes which are suspected of impacting on nearby fuel-assemblies in a boiling water reactor (BWR) are identified by both a classical spectral method and wavelet-based methods. It was found that there is good agreement between the different methods as well as with visual inspections of detector tube and fuel assembly damage made during the outage at the plant. The third problem addresses the determination of the decay ratio of a BWR from the auto-correlation function (ACF). Here wavelets are used, with some success, both for de-trending and de-nosing of the ACF and also for direct estimation of the decay ratio from the ACF. The second part deals with the analysis of beam-mode and shell-mode core-barrel vibrations in pressurised water reactors (PWRs). The beam-mode vibrations are analysed by using parameters of the vibration peaks, in spectra from ex core detectors. A trend analysis of the peak amplitude shows that the peak amplitude is changing during the fuel cycle. When it comes to the analysis of the shell-mode vibration, 1-D analytical and numerical calculations are performed in order to calculate the neutron noise induced in the core. The two calculations are in agreement and show that a large local noise component is present in the core which could be used to classify the shell-mode vibrations. However, a measurement made in the PWR Ringhals-3 shows

A Liouville Problem for the Stationary Fractional Navier-Stokes-Poisson System

Science.gov (United States)

Wang, Y.; Xiao, J.

2017-06-01

This paper deals with a Liouville problem for the stationary fractional Navier-Stokes-Poisson system whose special case k=0 covers the compressible and incompressible time-independent fractional Navier-Stokes systems in R^{N≥2} . An essential difficulty raises from the fractional Laplacian, which is a non-local operator and thus makes the local analysis unsuitable. To overcome the difficulty, we utilize a recently-introduced extension-method in Wang and Xiao (Commun Contemp Math 18(6):1650019, 2016) which develops Caffarelli-Silvestre's technique in Caffarelli and Silvestre (Commun Partial Diff Equ 32:1245-1260, 2007).

Hydrothermal self-scheduling problem in a day-ahead electricity market

International Nuclear Information System (INIS)

Bisanovic, Smajo; Dlakic, Muris; Hajro, Mensur

2008-01-01

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis. (author)

Flood frequency analysis of historical flood data under stationary and non-stationary modelling

Science.gov (United States)

Machado, M. J.; Botero, B. A.; López, J.; Francés, F.; Díez-Herrero, A.; Benito, G.

2015-06-01

Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913-2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency

Inventory control for a perishable product with non-stationary demand and service level constraints

NARCIS (Netherlands)

Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.

2013-01-01

We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at

A review on application of neural networks and fuzzy logic to solve hydrothermal scheduling problem

International Nuclear Information System (INIS)

Haroon, S.; Malik, T.N.; Zafar, S.

2014-01-01

Electrical power system is highly complicated having hydro and thermal mix with large number of machines. To reduce power production cost, hydro and thermal resources are mixed. Hydrothermal scheduling is the optimal coordination of hydro and thermal plants to meet the system load demand at minimum possible operational cost while satisfying the system constraints. Hydrothermal scheduling is dynamic, large scale, non-linear and non-convex optimization problem. The classical techniques have failed in solving such problem. Artificial Intelligence Tools based techniques are used now a day to solve this complex optimization problem because of their no requirements on the nature of the problem. The aim of this research paper is to provide a comprehensive survey of literature related to both Artificial Neural Network (ANN) and Fuzzy Logic (FL) as effective optimization algorithms for the hydrothermal scheduling problem. The outcomes along with the merits and demerits of individual techniques are also discussed. (author)

Unit-time scheduling problems with time dependent resources

NARCIS (Netherlands)

Tautenhahn, T.; Woeginger, G.

1997-01-01

We investigate the computational complexity of scheduling problems, where the operations consume certain amounts of renewable resources which are available in time-dependent quantities. In particular, we consider unit-time open shop problems and unit-time scheduling problems with identical parallel

Problem specific heuristics for group scheduling problems in cellular manufacturing

OpenAIRE

Neufeld, Janis Sebastian

2016-01-01

The group scheduling problem commonly arises in cellular manufacturing systems, where parts are grouped into part families. It is characterized by a sequencing task on two levels: on the one hand, a sequence of jobs within each part family has to be identified while, on the other hand, a family sequence has to be determined. In order to solve this NP-hard problem usually heuristic solution approaches are used. In this thesis different aspects of group scheduling are discussed and problem spec...

On the non-stationary generalized Langevin equation

Science.gov (United States)

Meyer, Hugues; Voigtmann, Thomas; Schilling, Tanja

2017-12-01

In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of such averages is described by the generalized Langevin equation. By contrast, if the dynamics is not stationary, it is not a priori clear which form the equation of motion for an averaged observable has. We employ the formalism of time-dependent projection operator techniques to derive the equation of motion for a non-equilibrium trajectory-averaged observable as well as for its non-stationary auto-correlation function. The equation is similar in structure to the generalized Langevin equation but exhibits a time-dependent memory kernel as well as a fluctuating force that implicitly depends on the initial conditions of the process. We also derive a relation between this memory kernel and the autocorrelation function of the fluctuating force that has a structure similar to a fluctuation-dissipation relation. In addition, we show how the choice of the projection operator allows us to relate the Taylor expansion of the memory kernel to data that are accessible in MD simulations and experiments, thus allowing us to construct the equation of motion. As a numerical example, the procedure is applied to Brownian motion initialized in non-equilibrium conditions and is shown to be consistent with direct measurements from simulations.

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Directory of Open Access Journals (Sweden)

Yingni Zhai

2014-10-01

Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

Non-steady state modeling of wheel-rail contact problem

OpenAIRE

Guiral, A.; Alonso, A.; Baeza González, Luis Miguel; Giménez, J.G.

2013-01-01

Among all the algorithms to solve the wheel–rail contact problem, Kalker's FastSim has become the most useful computation tool since it combines a low computational cost and enough precision for most of the typical railway dynamics problems. However, some types of dynamic problems require the use of a non-steady state analysis. Alonso and Giménez developed a non-stationary method based on FastSim, which provides both, sufficiently accurate results and a low computational cost. However, it pre...

On structural identifiability analysis of the cascaded linear dynamic systems in isotopically non-stationary 13C labelling experiments.

Science.gov (United States)

Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang

2018-06-01

The isotopically non-stationary 13C labelling experiments, as an emerging experimental technique, can estimate the intracellular fluxes of the cell culture under an isotopic transient period. However, to the best of our knowledge, the issue of the structural identifiability analysis of non-stationary isotope experiments is not well addressed in the literature. In this work, the local structural identifiability analysis for non-stationary cumomer balance equations is conducted based on the Taylor series approach. The numerical rank of the Jacobian matrices of the finite extended time derivatives of the measured fractions with respect to the free parameters is taken as the criterion. It turns out that only one single time point is necessary to achieve the structural identifiability analysis of the cascaded linear dynamic system of non-stationary isotope experiments. The equivalence between the local structural identifiability of the cascaded linear dynamic systems and the local optimum condition of the nonlinear least squares problem is elucidated in the work. Optimal measurements sets can then be determined for the metabolic network. Two simulated metabolic networks are adopted to demonstrate the utility of the proposed method. Copyright © 2018 Elsevier Inc. All rights reserved.

From Preemptive to Non-preemptive Scheduling Using Rejections

OpenAIRE

Lucarelli , Giorgio; Srivastav , Abhinav; Trystram , Denis

2016-01-01

International audience; We study the classical problem of scheduling a set of independent jobs with release dates on a single machine. There exists a huge literature on the preemptive version of the problem, where the jobs can be interrupted at any moment. However, we focus here on the non-preemptive case, which is harder, but more relevant in practice. For instance, the jobs submitted to actual high performance platforms cannot be interrupted or migrated once they start their execution (due ...

Non-stationary flow of hydraulic oil in long pipe

Directory of Open Access Journals (Sweden)

Hružík Lumír

2014-03-01

Full Text Available The paper deals with experimental evaluation and numerical simulation of non-stationary flow of hydraulic oil in a long hydraulic line. Non-stationary flow is caused by a quick closing of valves at the beginning and the end of the pipe. Time dependence of pressure is measured by means of pressure sensors at the beginning and the end of the pipe. A mathematical model of a given circuit is created using Matlab SimHydraulics software. The long line is simulated by means of segmented pipe. The simulation is verified by experiment.

An MILP approximation for ordering perishable products with non-stationary demand and service level constraints

NARCIS (Netherlands)

Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.

2014-01-01

We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at

The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

Science.gov (United States)

Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.

2016-08-01

In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.

Robust Forecasting of Non-Stationary Time Series

OpenAIRE

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...

Some extensions of the discrete lotsizing and scheduling problem

NARCIS (Netherlands)

M. Salomon (Marc); L.G. Kroon (Leo); R. Kuik (Roelof); L.N. van Wassenhove (Luk)

1991-01-01

textabstractIn this paper the Discrete Lotsizing and Scheduling Problem (DLSP) is considered. DLSP relates to capacitated lotsizing as well as to job scheduling problems and is concerned with determining a feasible production schedule with minimal total costs in a single-stage manufacturing process.

Effect of non-stationary climate on infectious gastroenteritis transmission in Japan

Science.gov (United States)

Onozuka, Daisuke

2014-06-01

Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Infectious gastroenteritis cases were non-stationary and significantly associated with the IOD and ENSO (Multivariate ENSO Index [MEI], Niño 1 + 2, Niño 3, Niño 4, and Niño 3.4) for a period of approximately 1 to 2 years. This association was non-stationary and appeared to have a major influence on the synchrony of infectious gastroenteritis transmission. Our results suggest that non-stationary patterns of association between global climate factors and incidence of infectious gastroenteritis should be considered when developing early warning systems for epidemics of infectious gastroenteritis.

Non-stationary ionization in the low ionosphere by gravitational wave action

International Nuclear Information System (INIS)

Nikitin, M.A.; Kashchenko, N.M.

1977-01-01

Non-stationary effects in the lower ionosphere caused by gravitation waves are analyzed. Time dependences are obtained for extremum electron concentrations, which describe the dynamics of heterogeneous layer formation from the initially homogeneous distribution under the effect of gravitation waves. Diffusion of plasma and its complex composition are not taken into account. The problem is solved for two particular cases of low and high frequency gravitation waves impact on the ionosphere. Only in the former case electron concentration in the lower ionosphere deviates considerably from the equilibrium

AUTOMATIC CONTROL OF PARAMETERS OF A NON-STATIONARY OBJECT WITH CROSS LINKS

Directory of Open Access Journals (Sweden)

A. Pavlov

2018-04-01

Full Text Available Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The consequence of this is the low quality of many industrial control systems. The solution problem is the use of robust controllers. ACS with traditional PI and PID controllers have a very limited range of normal operation modes due to the appearance of parametric disturbances due to changes in the characteristics of the automated unit and changes in the load on it. The situation is different when using in the architecture of artificial neural network controllers. It is known that when training a neural network, the adaptation procedure is often used. This makes it possible to greatly expand the area of normal operating modes of ACS with neural automatic regulators in comparison with traditional linear regulators. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional object, provided that when designing the ACS at the stage of its simulation in the model of the regulatory object model, an adequate simulation model of the executive device. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional regulatory object model, an adequate simulation model of the executive device. Especially actual implementation of all these requirements in the application of electric actuators. This article fully complies with these requirements. This is what makes it possible to provide a guaranteed quality of control in non-stationary ACS with multidimensional objects and cross-links between control channels. The possibility of using a known hybrid automatic regulator to stabilize the parameters of a two-channel non-stationary object with two cross-linked. A

Mathematical models for a batch scheduling problem to minimize earliness and tardiness

Directory of Open Access Journals (Sweden)

Basar Ogun

2018-05-01

Full Text Available Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.

Distributing Flexibility to Enhance Robustness in Task Scheduling Problems

NARCIS (Netherlands)

Wilmer, D.; Klos, T.B.; Wilson, M.

2013-01-01

Temporal scheduling problems occur naturally in many diverse application domains such as manufacturing, transportation, health and education. A scheduling problem arises if we have a set of temporal events (or variables) and some constraints on those events, and we have to find a schedule, which is

Around and about an application of the GAMLSS package to non-stationary flood frequency analysis

Science.gov (United States)

Debele, S. E.; Bogdanowicz, E.; Strupczewski, W. G.

2017-08-01

The non-stationarity of hydrologic processes due to climate change or human activities is challenging for the researchers and practitioners. However, the practical requirements for taking into account non-stationarity as a support in decision-making procedures exceed the up-to-date development of the theory and the of software. Currently, the most popular and freely available software package that allows for non-stationary statistical analysis is the GAMLSS (generalized additive models for location, scale and shape) package. GAMLSS has been used in a variety of fields. There are also several papers recommending GAMLSS in hydrological problems; however, there are still important issues which have not previously been discussed concerning mainly GAMLSS applicability not only for research and academic purposes, but also in a design practice. In this paper, we present a summary of our experiences in the implementation of GAMLSS to non-stationary flood frequency analysis, highlighting its advantages and pointing out weaknesses with regard to methodological and practical topics.

Downlink scheduling using non-orthogonal uplink beams

KAUST Repository

Eltayeb, Mohammed E.

2014-04-01

Opportunistic schedulers rely on the feedback of the channel state information of users in order to perform user selection and downlink scheduling. This feedback increases with the number of users, and can lead to inefficient use of network resources and scheduling delays. We tackle the problem of feedback design, and propose a novel class of nonorthogonal codes to feed back channel state information. Users with favorable channel conditions simultaneously transmit their channel state information via non-orthogonal beams to the base station. The proposed formulation allows the base station to identify the strong users via a simple correlation process. After deriving the minimum required code length and closed-form expressions for the feedback load and downlink capacity, we show that i) the proposed algorithm reduces the feedback load while matching the achievable rate of full feedback algorithms operating over a noiseless feedback channel, and ii) the proposed codes are superior to the Gaussian codes.

Downlink scheduling using non-orthogonal uplink beams

KAUST Repository

Eltayeb, Mohammed E.; Al-Naffouri, Tareq Y.; Bahrami, Hamid Reza Talesh

2014-01-01

Opportunistic schedulers rely on the feedback of the channel state information of users in order to perform user selection and downlink scheduling. This feedback increases with the number of users, and can lead to inefficient use of network resources and scheduling delays. We tackle the problem of feedback design, and propose a novel class of nonorthogonal codes to feed back channel state information. Users with favorable channel conditions simultaneously transmit their channel state information via non-orthogonal beams to the base station. The proposed formulation allows the base station to identify the strong users via a simple correlation process. After deriving the minimum required code length and closed-form expressions for the feedback load and downlink capacity, we show that i) the proposed algorithm reduces the feedback load while matching the achievable rate of full feedback algorithms operating over a noiseless feedback channel, and ii) the proposed codes are superior to the Gaussian codes.

Heuristic Method for Decision-Making in Common Scheduling Problems

Directory of Open Access Journals (Sweden)

Edyta Kucharska

2017-10-01

Full Text Available The aim of the paper is to present a heuristic method for decision-making regarding an NP-hard scheduling problem with limitations related to tasks and the resources dependent on the current state of the process. The presented approach is based on the algebraic-logical meta-model (ALMM, which enables making collective decisions in successive process stages, not separately for individual objects or executors. Moreover, taking into account the limitations of the problem, it involves constructing only an acceptable solution and significantly reduces the amount of calculations. A general algorithm based on the presented method is composed of the following elements: preliminary analysis of the problem, techniques for the choice of decision at a given state, the pruning non-perspective trajectory, selection technique of the initial state for the trajectory final part, and the trajectory generation parameters modification. The paper includes applications of the presented approach to scheduling problems on unrelated parallel machines with a deadline and machine setup time dependent on the process state, where the relationship between tasks is defined by the graph. The article also presents the results of computational experiments.

Utilization Bound of Non-preemptive Fixed Priority Schedulers

Science.gov (United States)

Park, Moonju; Chae, Jinseok

It is known that the schedulability of a non-preemptive task set with fixed priority can be determined in pseudo-polynomial time. However, since Rate Monotonic scheduling is not optimal for non-preemptive scheduling, the applicability of existing polynomial time tests that provide sufficient schedulability conditions, such as Liu and Layland's bound, is limited. This letter proposes a new sufficient condition for non-preemptive fixed priority scheduling that can be used for any fixed priority assignment scheme. It is also shown that the proposed schedulability test has a tighter utilization bound than existing test methods.

A meta-heuristic method for solving scheduling problem: crow search algorithm

Science.gov (United States)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

A new derivation of the conformally flat stationary cyclic non-circular spacetimes

International Nuclear Information System (INIS)

Ayon-Beato, Eloy; Campuzano, Cuauhtemoc; GarcIa, Alberto

2007-01-01

We present an alternative way to derive the conformally flat stationary cyclic non-circular spacetimes. We show that there is no room for stationary axisymmetric non-circular axisymmetric spacetimes. We reproduce the well know results for this sort of spacetimes recently reported in [1

A new derivation of the conformally flat stationary cyclic non-circular spacetimes

Energy Technology Data Exchange (ETDEWEB)

Ayon-Beato, Eloy [Departamento de Fisica, Facultad de Fisica e Inteligencia Artificial, Universidad Veracruzana, 91000 Xalapa, Veracruz (Mexico); Campuzano, Cuauhtemoc [Departamento de Fisica, Facultad de Fisica e Inteligencia Artificial, Universidad Veracruzana, 91000 Xalapa, Veracruz (Mexico); GarcIa, Alberto [Department of Physics, University of California, Davis, CA 95616 (United States)

2007-11-15

We present an alternative way to derive the conformally flat stationary cyclic non-circular spacetimes. We show that there is no room for stationary axisymmetric non-circular axisymmetric spacetimes. We reproduce the well know results for this sort of spacetimes recently reported in [1].

Solving a chemical batch scheduling problem by local search

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.

1999-01-01

A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.

Thin viscoelastic disc subjected to radial non-stationary loading

Directory of Open Access Journals (Sweden)

Adámek V.

2010-07-01

Full Text Available The investigation of non-stationary wave phenomena in isotropic viscoelastic solids using analytical approaches is the aim of this paper. Concretely, the problem of a thin homogeneous disc subjected to radial pressure load nonzero on the part of its rim is solved. The external excitation is described by the Heaviside function in time, so the nonstationary state of stress is induced in the disc. Dissipative material behaviour of solid studied is represented by the discrete material model of standard linear viscoelastic solid in the Zener configuration. After the derivation of motion equations final form, the method of integral transforms in combination with the Fourier method is used for finding the problem solution. The solving process results in the derivation of integral transforms of radial and circumferential displacement components. Finally, the type of derived functions singularities and possible methods for their inverse Laplace transform are mentioned.

Evaluation of stationary and non-stationary geostatistical models for inferring hydraulic conductivity values at Aespoe

International Nuclear Information System (INIS)

La Pointe, P.R.

1994-11-01

This report describes the comparison of stationary and non-stationary geostatistical models for the purpose of inferring block-scale hydraulic conductivity values from packer tests at Aespoe. The comparison between models is made through the evaluation of cross-validation statistics for three experimental designs. The first experiment consisted of a 'Delete-1' test previously used at Finnsjoen. The second test consisted of 'Delete-10%' and the third test was a 'Delete-50%' test. Preliminary data analysis showed that the 3 m and 30 m packer test data can be treated as a sample from a single population for the purposes of geostatistical analyses. Analysis of the 3 m data does not indicate that there are any systematic statistical changes with depth, rock type, fracture zone vs non-fracture zone or other mappable factor. Directional variograms are ambiguous to interpret due to the clustered nature of the data, but do not show any obvious anisotropy that should be accounted for in geostatistical analysis. Stationary analysis suggested that there exists a sizeable spatially uncorrelated component ('Nugget Effect') in the 3 m data, on the order of 60% of the observed variance for the various models fitted. Four different nested models were automatically fit to the data. Results for all models in terms of cross-validation statistics were very similar for the first set of validation tests. Non-stationary analysis established that both the order of drift and the order of the intrinsic random functions is low. This study also suggests that conventional cross-validation studies and automatic variogram fitting are not necessarily evaluating how well a model will infer block scale hydraulic conductivity values. 20 refs, 20 figs, 14 tabs

Non-stationary dynamics of climate variability in synchronous influenza epidemics in Japan

Science.gov (United States)

Onozuka, Daisuke; Hagihara, Akihito

2015-09-01

Seasonal variation in the incidence of influenza is widely assumed. However, few studies have examined non-stationary relationships between global climate factors and influenza epidemics. We examined the monthly incidence of influenza in Fukuoka, Japan, from 2000 to 2012 using cross-wavelet coherency analysis to assess the patterns of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). The monthly incidence of influenza showed cycles of 1 year with the IOD and 2 years with ENSO indices (Multivariate, Niño 4, and Niño 3.4). These associations were non-stationary and appeared to have major influences on the synchrony of influenza epidemics. Our study provides quantitative evidence that non-stationary associations have major influences on synchrony between the monthly incidence of influenza and the dynamics of the IOD and ENSO. Our results call for the consideration of non-stationary patterns of association between influenza cases and climatic factors in early warning systems.

A hybrid electromagnetism-like algorithm for a multi-mode resource-constrained project scheduling problem

Directory of Open Access Journals (Sweden)

Mohammad Hossein Sadeghi

2013-08-01

Full Text Available In this paper, two different sub-problems are considered to solve a resource constrained project scheduling problem (RCPSP, namely i assignment of modes to tasks and ii scheduling of these tasks in order to minimize the makespan of the project. The modified electromagnetism-like algorithm deals with the first problem to create an assignment of modes to activities. This list is used to generate a project schedule. When a new assignment is made, it is necessary to fix all mode dependent requirements of the project activities and to generate a random schedule with the serial SGS method. A local search will optimize the sequence of the activities. Also in this paper, a new penalty function has been proposed for solutions which are infeasible with respect to non-renewable resources. Performance of the proposed algorithm has been compared with the best algorithms published so far on the basis of CPU time and number of generated schedules stopping criteria. Reported results indicate excellent performance of the algorithm.

Real-time reservoir operation considering non-stationary inflow prediction

Science.gov (United States)

Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

2011-12-01

Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

Non-stationary compositions of Anosov diffeomorphisms

International Nuclear Information System (INIS)

Stenlund, Mikko

2011-01-01

Motivated by non-equilibrium phenomena in nature, we study dynamical systems whose time-evolution is determined by non-stationary compositions of chaotic maps. The constituent maps are topologically transitive Anosov diffeomorphisms on a two-dimensional compact Riemannian manifold, which are allowed to change with time—slowly, but in a rather arbitrary fashion. In particular, such systems admit no invariant measure. By constructing a coupling, we prove that any two sufficiently regular distributions of the initial state converge exponentially with time. Thus, a system of this kind loses memory of its statistical history rapidly

Solving project scheduling problems by minimum cut computations

NARCIS (Netherlands)

Möhring, R.H.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen

In project scheduling, a set of precedence-constrained jobs has to be scheduled so as to minimize a given objective. In resource-constrained project scheduling, the jobs additionally compete for scarce resources. Due to its universality, the latter problem has a variety of applications in

Non-stationary and relaxation phenomena in cavity-assisted quantum memories

Science.gov (United States)

Veselkova, N. G.; Sokolov, I. V.

2017-12-01

We investigate the non-stationary and relaxation phenomena in cavity-assisted quantum memories for light. As a storage medium we consider an ensemble of cold atoms with standard Lambda-scheme of working levels. Some theoretical aspects of the problem were treated previously by many authors, and recent experiments stimulate more deep insight into the ultimate ability and limitations of the device. Since quantum memories can be used not only for the storage of quantum information, but also for a substantial manipulation of ensembles of quantum states, the speed of such manipulation and hence the ability to write and retrieve the signals of relatively short duration becomes important. In our research we do not apply the so-called bad cavity limit, and consider the memory operation of the signals whose duration is not much larger than the cavity field lifetime, accounting also for the finite lifetime of atomic coherence. In our paper we present an effective approach that makes it possible to find the non-stationary amplitude and phase behavior of strong classical control field, that matches the desirable time profile of both the envelope and the phase of the retrieved quantized signal. The phase properties of the retrieved quantized signals are of importance for the detection and manipulation of squeezing, entanglement, etc by means of optical mixing and homodyning.

Identification of QRS complex in non-stationary electrocardiogram of sick infants.

Science.gov (United States)

Kota, S; Swisher, C B; Al-Shargabi, T; Andescavage, N; du Plessis, A; Govindan, R B

2017-08-01

Due to the high-frequency of routine interventions in an intensive care setting, electrocardiogram (ECG) recordings from sick infants are highly non-stationary, with recurrent changes in the baseline, alterations in the morphology of the waveform, and attenuations of the signal strength. Current methods lack reliability in identifying QRS complexes (a marker of individual cardiac cycles) in the non-stationary ECG. In the current study we address this problem by proposing a novel approach to QRS complex identification. Our approach employs lowpass filtering, half-wave rectification, and the use of instantaneous Hilbert phase to identify QRS complexes in the ECG. We demonstrate the application of this method using ECG recordings from eight preterm infants undergoing intensive care, as well as from 18 normal adult volunteers available via a public database. We compared our approach to the commonly used approaches including Pan and Tompkins (PT), gqrs, wavedet, and wqrs for identifying QRS complexes and then compared each with manually identified QRS complexes. For preterm infants, a comparison between the QRS complexes identified by our approach and those identified through manual annotations yielded sensitivity and positive predictive values of 99% and 99.91%, respectively. The comparison metrics for each method are as follows: PT (sensitivity: 84.49%, positive predictive value: 99.88%), gqrs (85.25%, 99.49%), wavedet (95.24%, 99.86%), and wqrs (96.99%, 96.55%). Thus, the sensitivity values of the four methods previously described, are lower than the sensitivity of the method we propose; however, the positive predictive values of these other approaches is comparable to those of our method, with the exception of the wqrs approach, which yielded a slightly lower value. For adult ECG, our approach yielded a sensitivity of 99.78%, whereas PT yielded 99.79%. The positive predictive value was 99.42% for both our approach as well as for PT. We propose a novel method for

An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

Directory of Open Access Journals (Sweden)

Chandramouli Anandaraman

2011-10-01

Full Text Available Job Shop Scheduling Problem (JSSP and Flow Shop Scheduling Problem (FSSP are strong NP-complete combinatorial optimization problems among class of typical production scheduling problems. An improved Sheep Flock Heredity Algorithm (ISFHA is proposed in this paper to find a schedule of operations that can minimize makespan. In ISFHA, the pairwise mutation operation is replaced by a single point mutation process with a probabilistic property which guarantees the feasibility of the solutions in the local search domain. A Robust-Replace (R-R heuristic is introduced in place of chromosomal crossover to enhance the global search and to improve the convergence. The R-R heuristic is found to enhance the exploring potential of the algorithm and enrich the diversity of neighborhoods. Experimental results reveal the effectiveness of the proposed algorithm, whose optimization performance is markedly superior to that of genetic algorithms and is comparable to the best results reported in the literature.

The Vessel Schedule Recovery Problem

DEFF Research Database (Denmark)

Brouer, Berit Dangaard; Plum, Christian Edinger Munk; Vaaben, Bo

Maritime transportation is the backbone of world trade and is accountable for around 3% of the worlds CO2 emissions. We present the Vessel Schedule Recovery Problem (VSRP) to evaluate a given disruption scenario and to select a recovery action balancing the trade off between increased bunker cons...... consumption and the impact on the remaining network and the customer service level. The model is applied to 4 real cases from Maersk Line. Solutions are comparable or superior to those chosen by operations managers. Cost savings of up to 58% may be achieved.......Maritime transportation is the backbone of world trade and is accountable for around 3% of the worlds CO2 emissions. We present the Vessel Schedule Recovery Problem (VSRP) to evaluate a given disruption scenario and to select a recovery action balancing the trade off between increased bunker...

Approximate Forward Difference Equations for the Lower Order Non-Stationary Statistics of Geometrically Non-Linear Systems subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

Geometrically non-linear multi-degree-of-freedom (MDOF) systems subject to random excitation are considered. New semi-analytical approximate forward difference equations for the lower order non-stationary statistical moments of the response are derived from the stochastic differential equations...... of motion, and, the accuracy of these equations is numerically investigated. For stationary excitations, the proposed method computes the stationary statistical moments of the response from the solution of non-linear algebraic equations....

Existence of stationary solutions in the coronal loop problem

Energy Technology Data Exchange (ETDEWEB)

Hulshof, J; Terman, D; Verhulst, F

1988-01-01

The study of a hot plasma confined to a magnetic loop in the sun's corona leads to a singularly perturbed nonlinear reaction-diffusion equation with rather unusual side conditions. Monotone solutions of the stationary problem appear as fixed points of an iteration map which is contractive if the perturbation parameter is sufficiently small.

A review on prognostic techniques for non-stationary and non-linear rotating systems

Science.gov (United States)

Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph

2015-10-01

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

On Rigorous Drought Assessment Using Daily Time Scale: Non-Stationary Frequency Analyses, Revisited Concepts, and a New Method to Yield Non-Parametric Indices

Directory of Open Access Journals (Sweden)

Charles Onyutha

2017-10-01

Full Text Available Some of the problems in drought assessments are that: analyses tend to focus on coarse temporal scales, many of the methods yield skewed indices, a few terminologies are ambiguously used, and analyses comprise an implicit assumption that the observations come from a stationary process. To solve these problems, this paper introduces non-stationary frequency analyses of quantiles. How to use non-parametric rescaling to obtain robust indices that are not (or minimally skewed is also introduced. To avoid ambiguity, some concepts on, e.g., incidence, extremity, etc., were revisited through shift from monthly to daily time scale. Demonstrations on the introduced methods were made using daily flow and precipitation insufficiency (precipitation minus potential evapotranspiration from the Blue Nile basin in Africa. Results show that, when a significant trend exists in extreme events, stationarity-based quantiles can be far different from those when non-stationarity is considered. The introduced non-parametric indices were found to closely agree with the well-known standardized precipitation evapotranspiration indices in many aspects but skewness. Apart from revisiting some concepts, the advantages of the use of fine instead of coarse time scales in drought assessment were given. The links for obtaining freely downloadable tools on how to implement the introduced methods were provided.

Can we identify non-stationary dynamics of trial-to-trial variability?

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Emili Balaguer-Ballester

Full Text Available Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation. This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies

Inferential framework for non-stationary dynamics: theory and applications

International Nuclear Information System (INIS)

Duggento, Andrea; Luchinsky, Dmitri G; McClintock, Peter V E; Smelyanskiy, Vadim N

2009-01-01

An extended Bayesian inference framework is presented, aiming to infer time-varying parameters in non-stationary nonlinear stochastic dynamical systems. The convergence of the method is discussed. The performance of the technique is studied using, as an example, signal reconstruction for a system of neurons modeled by FitzHugh–Nagumo oscillators: it is applied to reconstruction of the model parameters and elements of the measurement matrix, as well as to inference of the time-varying parameters of the non-stationary system. It is shown that the proposed approach is able to reconstruct unmeasured (hidden) variables of the system, to determine the model parameters, to detect stepwise changes of control parameters for each oscillator and to track the continuous evolution of the control parameters in the adiabatic limit

Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site

Directory of Open Access Journals (Sweden)

Xuhui He

2017-09-01

Full Text Available The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.

Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site.

Science.gov (United States)

He, Xuhui; Qin, Hongxi; Tao, Tianyou; Liu, Wenshuo; Wang, Hao

2017-09-22

The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.

Bayesian soft X-ray tomography using non-stationary Gaussian Processes

International Nuclear Information System (INIS)

Li, Dong; Svensson, J.; Thomsen, H.; Werner, A.; Wolf, R.; Medina, F.

2013-01-01

In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods

Bayesian soft X-ray tomography using non-stationary Gaussian Processes

Science.gov (United States)

Li, Dong; Svensson, J.; Thomsen, H.; Medina, F.; Werner, A.; Wolf, R.

2013-08-01

In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.

Non-standard work schedules, gender, and parental stress

Directory of Open Access Journals (Sweden)

Mariona Lozano

2016-02-01

Full Text Available Background: Working non-standard hours changes the temporal structure of family life, constraining the time that family members spend with one another and threatening individuals' well-being. However, the empirical research on the link between stress and non-standard schedules has provided mixed results. Some studies have indicated that working non-standard hours is harmful whereas others have suggested that working atypical hours might facilitate the balance between family and work. Moreover, there is some evidence that the association between stress and non-standard employment has different implications for men and women. Objective: This paper examines the association between non-standard work schedules and stress among dual-earner couples with children. Two research questions are addressed. First, do predictability of the schedule and time flexibility moderate the link between non-standard work hours and stress? Second, do non-standard schedules affect men's and women's perceptions of stress differently? Methods: We use a sample of 1,932 working parents from the Canadian 2010 General Social Survey, which includes a time-use diary. A sequential logit regression analysis stratified by gender is employed to model two types of result. First, we estimate the odds of being stressed versus not being stressed. Second, for all respondents feeling stressed, we estimate the odds of experiencing high levels versus moderate levels of stress. Results: Our analysis shows that the link between non-standard working hours and perceived stress differs between mothers and fathers. First, fathers with non-standard schedules appear more likely to experience stress than those working standard hours, although the results are not significant. Among mothers, having a non-standard schedule is associated with a significantly lower risk of experiencing stress. Second, the analysis focusing on the mediating role of flexibility and predictability indicates that

Approximating multi-objective scheduling problems

NARCIS (Netherlands)

Dabia, S.; Talbi, El-Ghazali; Woensel, van T.; Kok, de A.G.

2013-01-01

In many practical situations, decisions are multi-objective by nature. In this paper, we propose a generic approach to deal with multi-objective scheduling problems (MOSPs). The aim is to determine the set of Pareto solutions that represent the interactions between the different objectives. Due to

Advantages of the non-stationary approach: test on eddy current signals

International Nuclear Information System (INIS)

Brunel, P.

1993-12-01

Conventional signal processing is often unsuitable for the interpretation of intrinsically non-stationary signals, such as surveillance or non destructive testing signals. In these cases, ''advanced'' methods are required. This report presents two applications of non-stationary signal processing methods to the complex signals obtained in eddy current non destructive testing of steam generator tubes. The first application consists in segmenting the absolute channel, which can be likened to a piecewise constant signal. The Page-Hinkley cumulative sum algorithm is used, enabling detection of unknown mean amplitude jumps in a piecewise constant signal disturbed by a white noise. Results are comparable to those obtained with the empirical method currently in use. As easy to implement as the latter, the Page-Hinkley algorithm has the added advantage of being well formalized and of identifying whether the jumps in mean are positive or negative. The second application concerns assistance in detecting characteristic fault transients in the differential channels, using the continuous wavelet transform. The useful signal and noise spectra are fairly close, but not strictly identical. With the continuous wavelet transform, these frequency differences can be turned to account. The method was tested on synthetic signals obtained by summing noise and real defect signals. Using the continuous wavelet transform reduces the minimum signal-to-noise ratio by 5 dB for detection of a transient as compared with direct detection on the original signal. Finally, a summary of non-stationary methods using our data is presented. The two investigations described confirm that non-stationary methods may be considered as interesting signal and image analysis tools, as an efficient complement to conventional methods. (author). 24 figs., 13 refs

Flow-shop scheduling problem under uncertainties: Review and trends

Directory of Open Access Journals (Sweden)

Eliana María González-Neira

2017-03-01

Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

On a strong solution of the non-stationary Navier-Stokes equations under slip or leak boundary conditions of friction type

Science.gov (United States)

Kashiwabara, Takahito

Strong solutions of the non-stationary Navier-Stokes equations under non-linearized slip or leak boundary conditions are investigated. We show that the problems are formulated by a variational inequality of parabolic type, to which uniqueness is established. Using Galerkin's method and deriving a priori estimates, we prove global and local existence for 2D and 3D slip problems respectively. For leak problems, under no-leak assumption at t=0 we prove local existence in 2D and 3D cases. Compatibility conditions for initial states play a significant role in the estimates.

Performance comparison of some evolutionary algorithms on job shop scheduling problems

Science.gov (United States)

Mishra, S. K.; Rao, C. S. P.

2016-09-01

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

Identification of the structure parameters using short-time non-stationary stochastic excitation

Science.gov (United States)

Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra

2011-07-01

In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

Science.gov (United States)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

SOLVING FLOWSHOP SCHEDULING PROBLEMS USING A DISCRETE AFRICAN WILD DOG ALGORITHM

Directory of Open Access Journals (Sweden)

M. K. Marichelvam

2013-04-01

Full Text Available The problem of m-machine permutation flowshop scheduling is considered in this paper. The objective is to minimize the makespan. The flowshop scheduling problem is a typical combinatorial optimization problem and has been proved to be strongly NP-hard. Hence, several heuristics and meta-heuristics were addressed by the researchers. In this paper, a discrete African wild dog algorithm is applied for solving the flowshop scheduling problems. Computational results using benchmark problems show that the proposed algorithm outperforms many other algorithms addressed in the literature.

Autocalibration method for non-stationary CT bias correction.

Science.gov (United States)

Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José

2018-02-01

Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic Scheduling for Cloud Reliability using Transportation Problem

OpenAIRE

P. Balasubramanie; S. K. Senthil Kumar

2012-01-01

Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a sch...

Condition Monitoring of Machinery in Non-Stationary Operations : Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations"

CERN Document Server

Bartelmus, Walter; Chaari, Fakher; Zimroz, Radoslaw; Haddar, Mohamed

2012-01-01

Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers...

A non-stationary cost-benefit based bivariate extreme flood estimation approach

Science.gov (United States)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Self-organising mixture autoregressive model for non-stationary time series modelling.

Science.gov (United States)

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Non-stationary dynamics in the bouncing ball: A wavelet perspective

Energy Technology Data Exchange (ETDEWEB)

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in [Department of Physical Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246 (India); Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in [Plasma Physics Division, Saha Institute of Nuclear Physics (SINP), Sector 1, Block-AF, Bidhannagar, Kolkata 700064 (India)

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.

Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling

Science.gov (United States)

Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina

2018-01-01

The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.

The application of artificial intelligence to astronomical scheduling problems

Science.gov (United States)

Johnston, Mark D.

1992-01-01

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike

The Simultaneous Vehicle Scheduling and Passenger Service Problem

DEFF Research Database (Denmark)

Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.

2013-01-01

, by modifying the timetable. The planning approach is referred to as the simultaneous vehicle scheduling and passenger service problem (SVSPSP). The SVSPSP is modelled as an integer programming problem and solved using a large neighborhood search metaheuristic. The proposed framework is tested on data inspired......Passengers using public transport systems often experience waiting times when transferring between two scheduled services. In this paper we propose a planning approach that seeks to obtain a favourable trade-off between the two contrasting objectives, passenger service and operating cost...

Optimizing the Steel Plate Storage Yard Crane Scheduling Problem Using a Two Stage Planning/Scheduling Approach

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Clausen, Jens

This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning...

Self-adaptive change detection in streaming data with non-stationary distribution

KAUST Repository

Zhang, Xiangliang; Wang, Wei

2010-01-01

Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non

NON-INVASIVE INVERSE PROBLEM IN CIVIL ENGINEERING

Directory of Open Access Journals (Sweden)

Jan Havelka

2017-11-01

Full Text Available In this contribution we focus on recovery of spatial distribution of material parameters utilizing only non-invasive boundary measurements. Such methods has gained its importance as imaging techniques in medicine, geophysics or archaeology. We apply similar principles for non-stationary heat transfer in civil engineering. In oppose to standard technique which rely on external loading devices, we assume the natural fluctuation of temperature throughout day and night can provide sufficient information to recover the underlying material parameters. The inverse problem was solved by a modified regularised Gauss-Newton iterative scheme and the underlying forward problem is solved with a finite element space-time discretisation. We show a successful reconstruction of material parameters on a synthetic example with real measurements. The virtual experiment also reveals the insensitivity to practical precision of sensor measurements.

Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Larsen, Jan

2008-01-01

We present a method for suppression of non-stationary noise in single channel recordings of speech. The method is based on a non-negative latent variable decomposition model for the speech and noise signals, learned directly from a noisy mixture. In non-speech regions an over complete basis...... is learned for the noise that is then used to jointly estimate the speech and the noise from the mixture. We compare the method to the classical spectral subtraction approach, where the noise spectrum is estimated as the average over non-speech frames. The proposed method significantly outperforms...

The Synthesis of a Hardware Scheduler for Non-Manifest Loops

NARCIS (Netherlands)

Mansour, O.; Molenkamp, Egbert; Krol, Th.

This paper addresses the hardware implementation of a dynamic scheduler for non-manifest data dependent periodic loops. Static scheduling techniques which are known to give near optimal scheduling-solutions for manifest loops, fail at scheduling non-manifest loops, since they lack the run time

A review of scheduling problem and resolution methods in flexible flow shop

Directory of Open Access Journals (Sweden)

Tian-Soon Lee

2019-01-01

Full Text Available The Flexible flow shop (FFS is defined as a multi-stage flow shops with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. This review paper gives a comprehensive exploration review on the FFS scheduling problem and guides the reader by considering and understanding different environmental assumptions, system constraints and objective functions for future research works. The published papers are classified into two categories. First is the FFS system characteristics and constraints including the problem differences and limitation defined by different studies. Second, the scheduling performances evaluation are elaborated and categorized into time, job and multi related objectives. In addition, the resolution approaches that have been used to solve FFS scheduling problems are discussed. This paper gives a comprehensive guide for the reader with respect to future research work on the FFS scheduling problem.

Non-steady state modelling of wheel-rail contact problem

Science.gov (United States)

Guiral, A.; Alonso, A.; Baeza, L.; Giménez, J. G.

2013-01-01

Among all the algorithms to solve the wheel-rail contact problem, Kalker's FastSim has become the most useful computation tool since it combines a low computational cost and enough precision for most of the typical railway dynamics problems. However, some types of dynamic problems require the use of a non-steady state analysis. Alonso and Giménez developed a non-stationary method based on FastSim, which provides both, sufficiently accurate results and a low computational cost. However, it presents some limitations; the method is developed for one time-dependent creepage and its accuracy for varying normal forces has not been checked. This article presents the required changes in order to deal with both problems and compares its results with those given by Kalker's Variational Method for rolling contact.

A comparison of three approaches to non-stationary flood frequency analysis

Science.gov (United States)

Debele, S. E.; Strupczewski, W. G.; Bogdanowicz, E.

2017-08-01

Non-stationary flood frequency analysis (FFA) is applied to statistical analysis of seasonal flow maxima from Polish and Norwegian catchments. Three non-stationary estimation methods, namely, maximum likelihood (ML), two stage (WLS/TS) and GAMLSS (generalized additive model for location, scale and shape parameters), are compared in the context of capturing the effect of non-stationarity on the estimation of time-dependent moments and design quantiles. The use of a multimodel approach is recommended, to reduce the errors due to the model misspecification in the magnitude of quantiles. The results of calculations based on observed seasonal daily flow maxima and computer simulation experiments showed that GAMLSS gave the best results with respect to the relative bias and root mean square error in the estimates of trend in the standard deviation and the constant shape parameter, while WLS/TS provided better accuracy in the estimates of trend in the mean value. Within three compared methods the WLS/TS method is recommended to deal with non-stationarity in short time series. Some practical aspects of the GAMLSS package application are also presented. The detailed discussion of general issues related to consequences of climate change in the FFA is presented in the second part of the article entitled "Around and about an application of the GAMLSS package in non-stationary flood frequency analysis".

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

Science.gov (United States)

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

Science.gov (United States)

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

Science.gov (United States)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

A DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM

Directory of Open Access Journals (Sweden)

Shahnazari-Shahrezaei, P.

2012-11-01

Full Text Available Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers objectives and nurses preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics a differential evolution algorithm (DE and a greedy randomised adaptive search procedure (GRASP to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP.

The Liner Shipping Routing and Scheduling Problem Under Environmental Considerations

DEFF Research Database (Denmark)

Dithmer, Philip; Reinhardt, Line Blander; Kontovas, Christos

2017-01-01

This paper deals with the Liner Shipping Routing and Scheduling Problem (LSRSP), which consists of designing the time schedule for a vessel to visit a fixed set of ports while minimizing costs. We extend the classical problem to include the external cost of ship air emissions and we present some...

Influence of stationary and non-stationary conditions on drying time and mechanical properties of a porcelain slab

Science.gov (United States)

Hammouda, Imen; Mihoubi, Daoued

2017-12-01

This work deals with a numerical study of the response of a porcelain slab when subjected to convective drying in stationary and non-stationary conditions. The used model describes heat, mass, and momentum transfers is applied to an unsaturated viscoelastic medium described by a Maxwell model. The numerical code allows us to determine the effect of the surrounding air temperature on drying kinetics and on mechanical stress intensities. Von Mises stresses are analysed in order to foresee an eventual damage that may occur during drying. Simulation results for several temperatures in the range of [30 °C, 90 °C] shows that for the temperature from 30 °C to 60 °C, Von Mises stresses are always lower than the yield strength. But above 70 °C, Von Mises stresses are higher than the ultimate strength, and consequently there is a risk of crack at the end of the constant drying rate period. The idea proposed in this work is to integrate a reducing temperature phase when the predicted Von Mises stress intensity exceeds the admissible stress. Simulation results shows that a non-stationary convective drying (90-60 °C) allows us to optimize costs and quality by reducing the drying time and maintaining Von Mises stress values under the admissible stress.

Recovery and deformation substructures of zircaloy-4 in high temperature plasticity under stationary or non-stationary stress

International Nuclear Information System (INIS)

Bocek, M.; Armas, I.

1982-01-01

It was the aim of the present investigation to examine how the recovery rate in creep is influenced by a non-stationary stress. For purposes of phenomenological analysis it is postulated that, irrespective of whether the applied stress is stationary or not, for large strains the mean internal stress sigmasub(i) approaches a stationary value sigmasub(i,s). The stationary recovery rate Rsub(s) for constant load creep turns out be governed by the applied stress indicating that the recovery mechanism is dynamic in nature. For sigma-ramp loading, Rsub(s) is dependent on the stress rate sigma. In tensional stress cycling, Rsub(s) is governed by the maximum stress sigmasub(M) and is also dependent on the ratio of sigmasub(M) to the minimum stress sigma 0 . TEM examination of Zircaloy-4 specimens crept at 800 0 C at constant and cycling load respectively could not reveal any differences in the deformation substructure for the two loading types. Subgrain formation did not appear, individual dislocations were observed only rarely. However, typical networks were formed as well as pileups which perhaps are responsible for the back stress in high temperature plasticity (HTP). (orig.)

The local–global conjecture for scheduling with non-linear cost

NARCIS (Netherlands)

Bansal, N.; Dürr, C.; Thang, N.K.K.; Vásquez, Ó.C.

2017-01-01

We consider the classical scheduling problem on a single machine, on which we need to schedule sequentially n given jobs. Every job j has a processing time pj and a priority weight wj, and for a given schedule a completion time Cj. In this paper, we consider the problem of minimizing the objective

The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

Directory of Open Access Journals (Sweden)

Denis Pinha

2016-11-01

Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

The Simultaneous Vehicle Scheduling and Passenger Service Problem

DEFF Research Database (Denmark)

Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.

modifications of the timetable during the vehicle scheduling phase. This planning approach is referred to as the Simultaneous Vehicle Scheduling and Passenger Service Problem (SVSPSP). The SVSPSP is solved using a large neighbourhood search metaheuristic. The proposed framework is tested on data inspired......Passengers using public transport systems often experience waiting times when transferring between two scheduled services. We propose a planning approach which seeks to obtain a favorable trade-off between the conflicting objectives passenger service and operating cost, by allowing some moderate...

Algorithms for classical and modern scheduling problems

OpenAIRE

Ott, Sebastian

2016-01-01

Subject of this thesis is the design and the analysis of algorithms for scheduling problems. In the first part, we focus on energy-efficient scheduling, where one seeks to minimize the energy needed for processing certain jobs via dynamic adjustments of the processing speed (speed scaling). We consider variations and extensions of the standard model introduced by Yao, Demers, and Shenker in 1995 [79], including the addition of a sleep state, the avoidance of preemption, and variable speed lim...

Cointegration and Econometric Analysis of Non-Stationary Data in ...

African Journals Online (AJOL)

This is in conformity with the philosophy underlying the cointegration theory. Therefore, ignoring cointegration in non-stationary time series variables could lead to misspecification of the underlying process in the determination of corporate income tax in Nigeria. Thus, the study conclude that cointegration is greatly enhanced ...

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

Science.gov (United States)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

Producing Satisfactory Solutions to Scheduling Problems: An Iterative Constraint Relaxation Approach

Science.gov (United States)

Chien, S.; Gratch, J.

1994-01-01

One drawback to using constraint-propagation in planning and scheduling systems is that when a problem has an unsatisfiable set of constraints such algorithms typically only show that no solution exists. While, technically correct, in practical situations, it is desirable in these cases to produce a satisficing solution that satisfies the most important constraints (typically defined in terms of maximizing a utility function). This paper describes an iterative constraint relaxation approach in which the scheduler uses heuristics to progressively relax problem constraints until the problem becomes satisfiable. We present empirical results of applying these techniques to the problem of scheduling spacecraft communications for JPL/NASA antenna resources.

The operational flight and multi-crew scheduling problem

Directory of Open Access Journals (Sweden)

Stojković Mirela

2005-01-01

Full Text Available This paper introduces a new kind of operational multi-crew scheduling problem which consists in simultaneously modifying, as necessary, the existing flight departure times and planned individual work days (duties for the set of crew members, while respecting predefined aircraft itineraries. The splitting of a planned crew is allowed during a day of operations, where it is more important to cover a flight than to keep planned crew members together. The objective is to cover a maximum number of flights from a day of operations while minimizing changes in both the flight schedule and the next-day planned duties for the considered crew members. A new type of the same flight departure time constraints is introduced. They ensure that a flight which belongs to several personalized duties, where the number of duties is equal to the number of crew members assigned to the flight, will have the same departure time in each of these duties. Two variants of the problem are considered. The first variant allows covering of flights by less than the planned number of crew members, while the second one requires covering of flights by a complete crew. The problem is mathematically formulated as an integer nonlinear multi-commodity network flow model with time windows and supplementary constraints. The optimal solution approach is based on Dantzig-Wolfe decomposition/column generation embedded into a branch-and-bound scheme. The resulting computational times on commercial-size problems are very good. Our new simultaneous approach produces solutions whose quality is far better than that of the traditional sequential approach where the flight schedule has been changed first and then input as a fixed data to the crew scheduling problem.

Detection of Unusual Events and Trends in Complex Non-Stationary Data Streams

International Nuclear Information System (INIS)

Perez, Rafael B.; Protopopescu, Vladimir A.; Worley, Brian Addison; Perez, Cristina

2006-01-01

The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for a host of different applications, ranging from nuclear power plant and electric grid operation to internet traffic and implementation of non-proliferation protocols. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden intermittent events inside non-stationary signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method

Introduction and application of non-stationary standardized precipitation index considering probability distribution function and return period

Science.gov (United States)

Park, Junehyeong; Sung, Jang Hyun; Lim, Yoon-Jin; Kang, Hyun-Suk

2018-05-01

The widely used meteorological drought index, the Standardized Precipitation Index (SPI), basically assumes stationarity, but recent changes in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process was proposed. The results were evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered that the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite that these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the probability distribution wider than before. This implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.

Flow-shop scheduling problem under uncertainties: Review and trends

OpenAIRE

Eliana María González-Neira; Jairo R. Montoya-Torres; David Barrera

2017-01-01

Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of co...

Multi-objective problem of the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints

Science.gov (United States)

Amallynda, I.; Santosa, B.

2017-11-01

This paper proposes a new generalization of the distributed parallel machine and assembly scheduling problem (DPMASP) with eligibility constraints referred to as the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints. Within this generalization, we assume that there are a set non-identical factories or production lines, each one with a set unrelated parallel machine with different speeds in processing them disposed to a single assembly machine in series. A set of different products that are manufactured through an assembly program of a set of components (jobs) according to the requested demand. Each product requires several kinds of jobs with different sizes. Beside that we also consider to the multi-objective problem (MOP) of minimizing mean flow time and the number of tardy products simultaneously. This is known to be NP-Hard problem, is important to practice, as the former criterions to reflect the customer's demand and manufacturer's perspective. This is a realistic and complex problem with wide range of possible solutions, we propose four simple heuristics and two metaheuristics to solve it. Various parameters of the proposed metaheuristic algorithms are discussed and calibrated by means of Taguchi technique. All proposed algorithms are tested by Matlab software. Our computational experiments indicate that the proposed problem and fourth proposed algorithms are able to be implemented and can be used to solve moderately-sized instances, and giving efficient solutions, which are close to optimum in most cases.

Numerical Clifford Analysis for the Non-stationary Schroedinger Equation

International Nuclear Information System (INIS)

Faustino, N.; Vieira, N.

2007-01-01

We construct a discrete fundamental solution for the parabolic Dirac operator which factorizes the non-stationary Schroedinger operator. With such fundamental solution we construct a discrete counterpart for the Teodorescu and Cauchy-Bitsadze operators and the Bergman projectors. We finalize this paper with convergence results regarding the operators and a concrete numerical example

A Mathematical Model for Scheduling a Batch Processing Machine with Multiple Incompatible Job Families, Non-identical Job dimensions, Non-identical Job sizes, Non-agreeable release times and due dates

International Nuclear Information System (INIS)

Ramasubramaniam, M; Mathirajan, M

2013-01-01

The paper addresses the problem scheduling a batch processing machine with multiple incompatible job families, non-identical job dimensions, non-identical job sizes and non-agreeable release dates to minimize makespan. The research problem is solved by proposing a mixed integer programming model that appropriately takes into account the parameters considered in the problem. The proposed is validated using a numerical example. The experiment conducted show that the model can pose significant difficulties in solving the large scale instances. The paper concludes by giving the scope for future work and some alternative approaches one can use for solving these class of problems.

Multi-Objective Flexible Flow Shop Scheduling Problem Considering Variable Processing Time due to Renewable Energy

Directory of Open Access Journals (Sweden)

Xiuli Wu

2018-03-01

Full Text Available Renewable energy is an alternative to non-renewable energy to reduce the carbon footprint of manufacturing systems. Finding out how to make an alternative energy-efficient scheduling solution when renewable and non-renewable energy drives production is of great importance. In this paper, a multi-objective flexible flow shop scheduling problem that considers variable processing time due to renewable energy (MFFSP-VPTRE is studied. First, the optimization model of the MFFSP-VPTRE is formulated considering the periodicity of renewable energy and the limitations of energy storage capacity. Then, a hybrid non-dominated sorting genetic algorithm with variable local search (HNSGA-II is proposed to solve the MFFSP-VPTRE. An operation and machine-based encoding method is employed. A low-carbon scheduling algorithm is presented. Besides the crossover and mutation, a variable local search is used to improve the offspring’s Pareto set. The offspring and the parents are combined and those that dominate more are selected to continue evolving. Finally, two groups of experiments are carried out. The results show that the low-carbon scheduling algorithm can effectively reduce the carbon footprint under the premise of makespan optimization and the HNSGA-II outperforms the traditional NSGA-II and can solve the MFFSP-VPTRE effectively and efficiently.

Trend analysis using non-stationary time series clustering based on the finite element method

Science.gov (United States)

Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.

2014-05-01

In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

Science.gov (United States)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Demagnetization diagnosis in permanent magnet synchronous motors under non-stationary speed conditions

Energy Technology Data Exchange (ETDEWEB)

Ruiz, Jordi-Roger Riba [EUETII, Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya, Placa del Rei 15, 08700 Igualada, Barcelona (Spain); Garcia Espinosa, Antonio [Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain); Romeral, Luis; Cusido, Jordi [Dept. d' Enginyeria Electronica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain)

2010-10-15

Permanent magnet synchronous motors (PMSMs) are applied in high performance positioning and variable speed applications because of their enhanced features with respect to other AC motor types. Fault detection and diagnosis of electrical motors for critical applications is an active field of research. However, much research remains to be done in the field of PMSM demagnetization faults, especially when running under non-stationary conditions. This paper presents a time-frequency method specifically focused to detect and diagnose demagnetization faults in PMSMs running under non-stationary speed conditions, based on the Hilbert Huang transform. The effectiveness of the proposed method is proven by means of experimental results. (author)

Stability of stationary states of non-local equations with singular interaction potentials

KAUST Repository

Fellner, Klemens

2011-04-01

We study the large-time behaviour of a non-local evolution equation for the density of particles or individuals subject to an external and an interaction potential. In particular, we consider interaction potentials which are singular in the sense that their first derivative is discontinuous at the origin.For locally attractive singular interaction potentials we prove under a linear stability condition local non-linear stability of stationary states consisting of a finite sum of Dirac masses. For singular repulsive interaction potentials we show the stability of stationary states of uniformly bounded solutions under a convexity condition.Finally, we present numerical simulations to illustrate our results. © 2010 Elsevier Ltd.

The Home Care Crew Scheduling Problem:

DEFF Research Database (Denmark)

Rasmussen, Matias Sevel; Justesen, Tor; Dohn, Anders

In the Home Care Crew Scheduling Problem a staff of caretakers has to be assigned a number of visits to patients' homes, such that the overall service level is maximised. The problem is a generalisation of the vehicle routing problem with time windows. Required travel time between visits and time...... preference constraints. The algorithm is tested both on real-life problem instances and on generated test instances inspired by realistic settings. The use of the specialised branching scheme on real-life problems is novel. The visit clustering decreases run times significantly, and only gives a loss...... windows of the visits must be respected. The challenge when assigning visits to caretakers lies in the existence of soft preference constraints and in temporal dependencies between the start times of visits. We model the problem as a set partitioning problem with side constraints and develop an exact...

Teaching geographical hydrology in a non-stationary world

Science.gov (United States)

Hendriks, Martin R.; Karssenberg, Derek

2010-05-01

cooperate. Besides fieldwork, a student should also learn to make use of the many available data sets, such as google earth, or as provided by remote sensing, or automatic data loggers. In our opinion the following sequence of activities should be applied for a student to attain a desirable working knowledge level. As mentioned earlier, a student first of all needs to have sufficient classical hydrological knowledge. After this a student should be educated in using simple models, in which field knowledge is incorporated. After this, a student should learn how to build models for solving typical hydrological problems. Modelling is especially worthwhile when the model is applied to a known area, as this certifies integration of fieldwork and modelling activities. To learn how to model, tailored courses with software that provides a set of easily learned functions to match the student's conceptual thought processes are needed. It is not easy to bring theoretical, field, and modelling knowledge together, and a pitfall may be the lack of knowledge of one or more of the above. Also, a student must learn to be able to deal with uncertainties in data and models, and must be trained to deal with unpredictability. Therefore, in our opinion a modern student should strive to become an integrating specialist in all of the above mentioned fields if we are to take geographical hydrology to a higher level and if we want to come to grips with it in a non-stationary world. A student must learn to think and act in an integrative way, and for this combining classical hydrology, field hydrology and modelling at a high education level in our hydrology curricula, in our opinion, is the way to proceed.

Non-stationary (13)C-metabolic flux ratio analysis.

Science.gov (United States)

Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola

2013-12-01

(13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media. © 2013 Wiley Periodicals, Inc.

Instantaneous angular speed monitoring of gearboxes under non-cyclic stationary load conditions

Science.gov (United States)

Stander, C. J.; Heyns, P. S.

2005-07-01

Recent developments in the condition monitoring and asset management market have led to the commercialisation of online vibration-monitoring systems. These systems are primarily utilised to monitor large mineral mining equipment such as draglines, continuous miners and hydraulic shovels. Online monitoring systems make diagnostic information continuously available for asset management, production outsourcing and maintenance alliances with equipment manufacturers. However, most online vibration-monitoring systems are based on conventional vibration-monitoring technologies, which are prone to giving false equipment deterioration warnings on gears that operate under fluctuating load conditions. A simplified mathematical model of a gear system was developed to illustrate the feasibility of monitoring the instantaneous angular speed (IAS) as a means of monitoring the condition of gears that are subjected to fluctuating load conditions. A distinction is made between cyclic stationary load modulation and non-cyclic stationary load modulation. It is shown that rotation domain averaging will suppress the modulation caused by non-cyclic stationary load conditions but will not suppress the modulation caused by cyclic stationary load conditions. An experimental investigation on a test rig indicated that the IAS of a gear shaft could be monitored with a conventional shaft encoder to indicate a deteriorating gear fault condition.

Algorithms for Scheduling and Network Problems

Science.gov (United States)

1991-09-01

time. We already know, by Lemma 2.2.1, that WOPT = O(log( mpU )), so if we could solve this integer program optimally we would be done. However, the...Folydirat, 15:177-191, 1982. [6] I.S. Belov and Ya. N. Stolin. An algorithm in a single path operations scheduling problem. In Mathematical Economics and

Permutation flow-shop scheduling problem to optimize a quadratic objective function

Science.gov (United States)

Ren, Tao; Zhao, Peng; Zhang, Da; Liu, Bingqian; Yuan, Huawei; Bai, Danyu

2017-09-01

A flow-shop scheduling model enables appropriate sequencing for each job and for processing on a set of machines in compliance with identical processing orders. The objective is to achieve a feasible schedule for optimizing a given criterion. Permutation is a special setting of the model in which the processing order of the jobs on the machines is identical for each subsequent step of processing. This article addresses the permutation flow-shop scheduling problem to minimize the criterion of total weighted quadratic completion time. With a probability hypothesis, the asymptotic optimality of the weighted shortest processing time schedule under a consistency condition (WSPT-CC) is proven for sufficiently large-scale problems. However, the worst case performance ratio of the WSPT-CC schedule is the square of the number of machines in certain situations. A discrete differential evolution algorithm, where a new crossover method with multiple-point insertion is used to improve the final outcome, is presented to obtain high-quality solutions for moderate-scale problems. A sequence-independent lower bound is designed for pruning in a branch-and-bound algorithm for small-scale problems. A set of random experiments demonstrates the performance of the lower bound and the effectiveness of the proposed algorithms.

Probing Gamma-ray Emission of Geminga & Vela with Non-stationary Models

Directory of Open Access Journals (Sweden)

Yating Chai

2016-06-01

Full Text Available It is generally believed that the high energy emissions from isolated pulsars are emitted from relativistic electrons/positrons accelerated in outer magnetospheric accelerators (outergaps via a curvature radiation mechanism, which has a simple exponential cut-off spectrum. However, many gamma-ray pulsars detected by the Fermi LAT (Large Area Telescope cannot be fitted by simple exponential cut-off spectrum, and instead a sub-exponential is more appropriate. It is proposed that the realistic outergaps are non-stationary, and that the observed spectrum is a superposition of different stationary states that are controlled by the currents injected from the inner and outer boundaries. The Vela and Geminga pulsars have the largest fluxes among all targets observed, which allows us to carry out very detailed phase-resolved spectral analysis. We have divided the Vela and Geminga pulsars into 19 (the off pulse of Vela was not included and 33 phase bins, respectively. We find that most phase resolved spectra still cannot be fitted by a simple exponential spectrum: in fact, a sub-exponential spectrum is necessary. We conclude that non-stationary states exist even down to the very fine phase bins.

A New Method for Non-linear and Non-stationary Time Series Analysis:
The Hilbert Spectral Analysis

CERN Multimedia

CERN. Geneva

2000-01-01

A new method for analysing non-linear and non-stationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero crossing and extreme, and also having symmetric envelopes defined by the local maximal and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to non-linear and non-stationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical non-l...

Regime shifts under forcing of non-stationary attractors: Conceptual model and case studies in hydrologic systems.

Science.gov (United States)

Park, Jeryang; Rao, P Suresh C

2014-11-15

We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.

Non-stationary hydrologic frequency analysis using B-spline quantile regression

Science.gov (United States)

Nasri, B.; Bouezmarni, T.; St-Hilaire, A.; Ouarda, T. B. M. J.

2017-11-01

Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic and water resources systems under the assumption of stationarity. However, with increasing evidence of climate change, it is possible that the assumption of stationarity, which is prerequisite for traditional frequency analysis and hence, the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extremes based on B-Spline quantile regression which allows to model data in the presence of non-stationarity and/or dependence on covariates with linear and non-linear dependence. A Markov Chain Monte Carlo (MCMC) algorithm was used to estimate quantiles and their posterior distributions. A coefficient of determination and Bayesian information criterion (BIC) for quantile regression are used in order to select the best model, i.e. for each quantile, we choose the degree and number of knots of the adequate B-spline quantile regression model. The method is applied to annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in the variable of interest and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for an annual maximum and minimum discharge with high annual non-exceedance probabilities.

Genetic algorithm to solve the problems of lectures and practicums scheduling

Science.gov (United States)

Syahputra, M. F.; Apriani, R.; Sawaluddin; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.

2018-02-01

Generally, the scheduling process is done manually. However, this method has a low accuracy level, along with possibilities that a scheduled process collides with another scheduled process. When doing theory class and practicum timetable scheduling process, there are numerous problems, such as lecturer teaching schedule collision, schedule collision with another schedule, practicum lesson schedules that collides with theory class, and the number of classrooms available. In this research, genetic algorithm is implemented to perform theory class and practicum timetable scheduling process. The algorithm will be used to process the data containing lists of lecturers, courses, and class rooms, obtained from information technology department at University of Sumatera Utara. The result of scheduling process using genetic algorithm is the most optimal timetable that conforms to available time slots, class rooms, courses, and lecturer schedules.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

Science.gov (United States)

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

Enhancement and Noise Statistics Estimation for Non-Stationary Voiced Speech

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2016-01-01

In this paper, single channel speech enhancement in the time domain is considered. We address the problem of modelling non-stationary speech by describing the voiced speech parts by a harmonic linear chirp model instead of using the traditional harmonic model. This means that the speech signal...... through simulations on synthetic and speech signals, that the chirp versions of the filters perform better than their harmonic counterparts in terms of output signal-to-noise ratio (SNR) and signal reduction factor. For synthetic signals, the output SNR for the harmonic chirp APES based filter...... is increased 3 dB compared to the harmonic APES based filter at an input SNR of 10 dB, and at the same time the signal reduction factor is decreased. For speech signals, the increase is 1.5 dB along with a decrease in the signal reduction factor of 0.7. As an implicit part of the APES filter, a noise...

Flexible job shop scheduling problem in manufacturing

OpenAIRE

Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo

2013-01-01

This paper addresses a real assembly cell: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France. This system can be viewed as a Flexible Job Shop, leading to the formulation of a Flexible Job Shop Scheduling Problem (FJSSP).

Resource-constrained project scheduling: computing lower bounds by solving minimum cut problems

NARCIS (Netherlands)

Möhring, R.H.; Nesetril, J.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen

1999-01-01

We present a novel approach to compute Lagrangian lower bounds on the objective function value of a wide class of resource-constrained project scheduling problems. The basis is a polynomial-time algorithm to solve the following scheduling problem: Given a set of activities with start-time dependent

An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction

Directory of Open Access Journals (Sweden)

Zhi Yang

2016-01-01

Full Text Available Uncertainty is common in ship construction. However, few studies have focused on scheduling problems under uncertainty in shipbuilding. This paper formulates the scheduling problem of panel block construction as a multiobjective fuzzy flow shop scheduling problem (FSSP with a fuzzy processing time, a fuzzy due date, and the just-in-time (JIT concept. An improved multiobjective particle swarm optimization called MOPSO-M is developed to solve the scheduling problem. MOPSO-M utilizes a ranked-order-value rule to convert the continuous position of particles into the discrete permutations of jobs, and an available mapping is employed to obtain the precedence-based permutation of the jobs. In addition, to improve the performance of MOPSO-M, archive maintenance is combined with global best position selection, and mutation and a velocity constriction mechanism are introduced into the algorithm. The feasibility and effectiveness of MOPSO-M are assessed in comparison with general MOPSO and nondominated sorting genetic algorithm-II (NSGA-II.

The Application of Artificial Intelligence to Astronomical Scheduling Problems

Science.gov (United States)

Johnston, Mark D.

1993-01-01

As artificial intelligence (AI) technology has moved from the research laboratory into more and more widespread use, one of the leading applications in astronomy has been to high-profile observation scheduling. The Spike scheduling system was developed by the Space Telescope Science Institute (STScI) for the purpose of long-range scheduling of Hubble Space Telescope (HST). Spike has been in daily operational use at STScI since well before HST launch in April 1990. The system has also been adapted to schedule other missions: one of these missions (EUVE) is currently operational, while another (ASTRO-D) will be launched in February 1993. Some other future space astronomy missions (XTE, SWAS, and AXAF) are making tentative plans to use Spike. Spike has proven to be a powerful and flexible scheduling framework with applicability to a wide variety of problems.

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

Science.gov (United States)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

Lyapunov Functions, Stationary Distributions, and Non-equilibrium Potential for Reaction Networks

DEFF Research Database (Denmark)

Anderson, David F; Craciun, Gheorghe; Gopalkrishnan, Manoj

2015-01-01

We consider the relationship between stationary distributions for stochastic models of reaction systems and Lyapunov functions for their deterministic counterparts. Specifically, we derive the well-known Lyapunov function of reaction network theory as a scaling limit of the non-equilibrium potent...

Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility

DEFF Research Database (Denmark)

Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

Many key macro-economic and financial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

Directory of Open Access Journals (Sweden)

Behnam Barzegar

2012-01-01

Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Noor Hasnah Moin

2015-01-01

Full Text Available The job shop scheduling problem (JSSP is one of the well-known hard combinatorial scheduling problems. This paper proposes a hybrid genetic algorithm with multiparents crossover for JSSP. The multiparents crossover operator known as extended precedence preservative crossover (EPPX is able to recombine more than two parents to generate a single new offspring distinguished from common crossover operators that recombine only two parents. This algorithm also embeds a schedule generation procedure to generate full-active schedule that satisfies precedence constraints in order to reduce the search space. Once a schedule is obtained, a neighborhood search is applied to exploit the search space for better solutions and to enhance the GA. This hybrid genetic algorithm is simulated on a set of benchmarks from the literatures and the results are compared with other approaches to ensure the sustainability of this algorithm in solving JSSP. The results suggest that the implementation of multiparents crossover produces competitive results.

Solving cyclical nurse scheduling problem using preemptive goal programming

Science.gov (United States)

Sundari, V. E.; Mardiyati, S.

2017-07-01

Nurse scheduling system in a hospital is being modeled as a preemptive goal programming problem that is solved by using LINGO software with the objective function to minimize deviation variable at each goal. The scheduling is done cyclically, so every nurse is treated fairly since they have the same work shift portion with the other nurses. By paying attention to the hospital's rules regarding nursing work shift cyclically, it can be obtained that numbers of nurse needed in every ward are 18 nurses and the numbers of scheduling periods are 18 periods where every period consists of 21 days.

Integrated Production-Distribution Scheduling Problem with Multiple Independent Manufacturers

Directory of Open Access Journals (Sweden)

Jianhong Hao

2015-01-01

Full Text Available We consider the nonstandard parts supply chain with a public service platform for machinery integration in China. The platform assigns orders placed by a machinery enterprise to multiple independent manufacturers who produce nonstandard parts and makes production schedule and batch delivery schedule for each manufacturer in a coordinate manner. Each manufacturer has only one plant with parallel machines and is located at a location far away from other manufacturers. Orders are first processed at the plants and then directly shipped from the plants to the enterprise in order to be finished before a given deadline. We study the above integrated production-distribution scheduling problem with multiple manufacturers to maximize a weight sum of the profit of each manufacturer under the constraints that all orders are finished before the deadline and the profit of each manufacturer is not negative. According to the optimal condition analysis, we formulate the problem as a mixed integer programming model and use CPLEX to solve it.

Multi-objective Mobile Robot Scheduling Problem with Dynamic Time Windows

DEFF Research Database (Denmark)

Dang, Vinh Quang; Nielsen, Izabela Ewa; Steger-Jensen, Kenn

2012-01-01

This paper deals with the problem of scheduling feeding tasks of a single mobile robot which has capability of supplying parts to feeders on pro-duction lines. The performance criterion is to minimize the total traveling time of the robot and the total tardiness of the feeding tasks being scheduled...

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

OpenAIRE

Amjad, Muhammad Kamal; Butt, Shahid Ikramullah; Kousar, Rubeena; Ahmad, Riaz; Agha, Mujtaba Hassan; Faping, Zhang; Anjum, Naveed; Asgher, Umer

2018-01-01

Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in...

Resource-constrained project scheduling problem: review of past and recent developments

Directory of Open Access Journals (Sweden)

Farhad Habibi

2018-01-01

Full Text Available The project scheduling problem is both practically and theoretically of paramount importance. From the practical perspective, improvement of project scheduling as a critical part of project management process can lead to successful project completion and significantly decrease of the relevant costs. From the theoretical perspective, project scheduling is regarded as one of the in-teresting optimization issues, which has attracted the attention of many researchers in the area of operations research. Therefore, the project scheduling issue has been significantly evaluated over time and has been developed from various aspects. In this research, the topics related to Re-source-Constrained Project Scheduling Problem (RCPSP are reviewed, recent developments in this field are evaluated, and the results are presented for future studies. In this regard, first, the standard problem of RCPSP is expressed and related developments are presented from four as-pects of resources, characteristics of activities, type of objective functions, and availability level of information. Following that, details about 216 articles conducted on RCPSP during 1980-2017 are expressed. At the end, in line with the statistics obtained from the evaluation of previ-ous articles, suggestions are made for the future studies in order to help the development of new issues in this area.

Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, A. M. Robert

Many key macro-economic and …nancial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...

Is the Labour Force Participation Rate Non-Stationary in Romania?

Directory of Open Access Journals (Sweden)

Tiwari Aviral Kumar

2015-01-01

Full Text Available The purpose of this paper is to test hysteresis of the Romanian labour force participation rate, by using time series data, with quarterly frequency, covering the period 1999Q1-2013Q4. The main results reveal that the Romanian labour force participation rate is a nonlinear process and has a partial unit root (i.e. it is stationary in the first regime and non-stationary in the second one, the main breaking point being registered around year 2005. In this context, the value of using unemployment rate as an indicator for capturing joblessness in this country is debatable. Starting from 2005, the participation rate has not followed long-term changes in unemployment rate, the disturbances having permanent effects on labour force participation rate.

A new genetic algorithm for flexible job-shop scheduling problems

International Nuclear Information System (INIS)

Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia

2015-01-01

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

A new genetic algorithm for flexible job-shop scheduling problems

Energy Technology Data Exchange (ETDEWEB)

Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia [University of Batna, Batna (Algeria)

2015-03-15

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

Flowshop Scheduling Problems with a Position-Dependent Exponential Learning Effect

Directory of Open Access Journals (Sweden)

Mingbao Cheng

2013-01-01

Full Text Available We consider a permutation flowshop scheduling problem with a position-dependent exponential learning effect. The objective is to minimize the performance criteria of makespan and the total flow time. For the two-machine flow shop scheduling case, we show that Johnson’s rule is not an optimal algorithm for minimizing the makespan given the exponential learning effect. Furthermore, by using the shortest total processing times first (STPT rule, we construct the worst-case performance ratios for both criteria. Finally, a polynomial-time algorithm is proposed for special cases of the studied problem.

The Home Care Crew Scheduling Problem

DEFF Research Database (Denmark)

Rasmussen, Matias Sevel; Justesen, Tor

In the Home Care Crew Scheduling Problem (HCCSP) a staff of caretakers has to be assigned a number of visits, such that the total number of assigned visits is maximised. The visits have different locations and positions in time, and travelling time and time windows must be respected. The challenge...... when assigning visits to caretakers lies in the existence of soft constraints and indeed also in temporal dependencies between the starting times of visits. Most former approaches to solving the HCCSP involve the use of heuristic methods. Here we develop an exact branch-and-price algorithm that uses...... clustering of the visits based on the problem structure. The algorithm is tested on real-life problem instances and we obtain solutions that are better than current practice in all cases....

Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

Directory of Open Access Journals (Sweden)

Wenming Cheng

2012-01-01

Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

A location-based multiple point statistics method: modelling the reservoir with non-stationary characteristics

Directory of Open Access Journals (Sweden)

Yin Yanshu

2017-12-01

Full Text Available In this paper, a location-based multiple point statistics method is developed to model a non-stationary reservoir. The proposed method characterizes the relationship between the sedimentary pattern and the deposit location using the relative central position distance function, which alleviates the requirement that the training image and the simulated grids have the same dimension. The weights in every direction of the distance function can be changed to characterize the reservoir heterogeneity in various directions. The local integral replacements of data events, structured random path, distance tolerance and multi-grid strategy are applied to reproduce the sedimentary patterns and obtain a more realistic result. This method is compared with the traditional Snesim method using a synthesized 3-D training image of Poyang Lake and a reservoir model of Shengli Oilfield in China. The results indicate that the new method can reproduce the non-stationary characteristics better than the traditional method and is more suitable for simulation of delta-front deposits. These results show that the new method is a powerful tool for modelling a reservoir with non-stationary characteristics.

Optimizing a Military Supply Chain in the Presence of Random, Non-Stationary Demands

National Research Council Canada - National Science Library

Yew

2003-01-01

... logistics supply chain that satisfies uncertain, non-stationary demands, while taking into account the volatility and singularity of military operations This research focuses on the development...

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Lvjiang Yin

2016-12-01

Full Text Available Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T, cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II, Strength Pareto Evolutionary Algorithm 2 (SPEA2, Multiobjective Particle Swarm Optimization (OMOPSO, and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D. Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.

Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

Science.gov (United States)

Buddala, Raviteja; Mahapatra, Siba Sankar

2017-11-01

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

Flexible ship loading problem with transfer vehicle assignment and scheduling

DEFF Research Database (Denmark)

Iris, Çağatay; Christensen, Jonas; Pacino, Dario

2018-01-01

This paper presents the flexible containership loading problem for seaport container terminals. The integrated management of loading operations, planning of the transport vehicles to use and their scheduling is what we define as the Flexible Ship Loading Problem (FSLP). The flexibility comes from...

Extended precedence preservative crossover for job shop scheduling problems

Science.gov (United States)

Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd

2013-04-01

Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.

Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

Science.gov (United States)

López, J.; Francés, F.

2013-08-01

Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.

Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

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J. López

2013-08-01

Full Text Available Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS. Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.

A Distributed Particle Swarm Optimization Zlgorithmfor Flexible Job-hop Scheduling Problem

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LIU Sheng--hui

2017-06-01

Full Text Available According to the characteristics of the Flexible job shop scheduling problem the minimum makespan as measures we proposed a distributed particle swarm optimization algorithm aiming to solve flexible job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi agent particle swarm optimization model in this algorithm it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the FJSP and it also verified the reasonableness of the multi}gent particle swarm optimization model.

A Study on the Enhanced Best Performance Algorithm for the Just-in-Time Scheduling Problem

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Sivashan Chetty

2015-01-01

Full Text Available The Just-In-Time (JIT scheduling problem is an important subject of study. It essentially constitutes the problem of scheduling critical business resources in an attempt to optimize given business objectives. This problem is NP-Hard in nature, hence requiring efficient solution techniques. To solve the JIT scheduling problem presented in this study, a new local search metaheuristic algorithm, namely, the enhanced Best Performance Algorithm (eBPA, is introduced. This is part of the initial study of the algorithm for scheduling problems. The current problem setting is the allocation of a large number of jobs required to be scheduled on multiple and identical machines which run in parallel. The due date of a job is characterized by a window frame of time, rather than a specific point in time. The performance of the eBPA is compared against Tabu Search (TS and Simulated Annealing (SA. SA and TS are well-known local search metaheuristic algorithms. The results show the potential of the eBPA as a metaheuristic algorithm.

Stability of stationary solutions for inflow problem on the micropolar fluid model

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Yin, Haiyan

2017-04-01

In this paper, we study the asymptotic behavior of solutions to the initial boundary value problem for the micropolar fluid model in a half-line R+:=(0,∞). We prove that the corresponding stationary solutions of the small amplitude to the inflow problem for the micropolar fluid model are time asymptotically stable under small H1 perturbations in both the subsonic and degenerate cases. The microrotation velocity brings us some additional troubles compared with Navier-Stokes equations in the absence of the microrotation velocity. The proof of asymptotic stability is based on the basic energy method.

Modified fluctuation-dissipation theorem for general non-stationary states and application to the Glauber–Ising chain

International Nuclear Information System (INIS)

Verley, Gatien; Lacoste, David; Chétrite, Raphaël

2011-01-01

In this paper, we present a general derivation of a modified fluctuation-dissipation theorem (MFDT) valid near an arbitrary non-stationary state for a system obeying Markovian dynamics. We show that the method for deriving modified fluctuation-dissipation theorems near non-equilibrium stationary states used by Prost et al (2009 Phys. Rev. Lett. 103 090601) is generalizable to non-stationary states. This result follows from both standard linear response theory and from a transient fluctuation theorem, analogous to the Hatano–Sasa relation. We show that this modified fluctuation-dissipation theorem can be interpreted at the trajectory level using the notion of stochastic trajectory entropy, in a way which is similar to what has been done recently in the case of the MFDT near non-equilibrium steady states (NESS). We illustrate this framework with two solvable examples: the first example corresponds to a Brownian particle in a harmonic trap subjected to a quench of temperature and to a time-dependent stiffness; the second example is a classic model of coarsening systems, namely the 1D Ising model with Glauber dynamics

Solving a manpower scheduling problem for airline catering using metaheuristics

DEFF Research Database (Denmark)

Ho, Sin C.; Leung, Janny M. Y.

2010-01-01

We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off.  Jobs (flights) must...

Gaussian variable neighborhood search for the file transfer scheduling problem

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Dražić Zorica

2016-01-01

Full Text Available This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results. [Projekat Ministarstava nauke Republike Srbije, br. 174010

Solving Large Scale Crew Scheduling Problems in Practice

NARCIS (Netherlands)

E.J.W. Abbink (Erwin); L. Albino; T.A.B. Dollevoet (Twan); D. Huisman (Dennis); J. Roussado; R.L. Saldanha

2010-01-01

textabstractThis paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of guards. Some labor rules restrict the duties of a certain crew base

Schedulability using native non-preemptive groups on an AUTOSAR/OSEK platform

NARCIS (Netherlands)

Hatvani, L.; Bril, R.J.

To combine the relative strengths of fully preemptive and non-preemptive fixed priority scheduling, we can use limited preemptive scheduling methods. One such method is fixed-priority threshold scheduling (FPTS). This approach defines dual priorities for every task, a priority assigned to the

An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem

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Jianhui Mou

2014-01-01

Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.

Stochastic optimal control of non-stationary response of a single-degree-of-freedom vehicle model

Science.gov (United States)

Narayanan, S.; Raju, G. V.

1990-09-01

An active suspension system to control the non-stationary response of a single-degree-of-freedom (sdf) vehicle model with variable velocity traverse over a rough road is investigated. The suspension is optimized with respect to ride comfort and road holding, using stochastic optimal control theory. The ground excitation is modelled as a spatial homogeneous random process, being the output of a linear shaping filter to white noise. The effect of the rolling contact of the tyre is considered by an additional filter in cascade. The non-stationary response with active suspension is compared with that of a passive system.

Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

Science.gov (United States)

Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

2017-09-01

The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

The approximate thermal-model-testing method for non-stationary temperature fields in central zones of fast reactor assemblies

International Nuclear Information System (INIS)

Mikhin, V.I.; Matukhin, N.M.

2000-01-01

The approach to generalization of the non-stationary heat exchange data for the central zones of the nuclear reactor fuel assemblies and the approximate thermal-model-testing criteria are proposed. The fuel assemblies of fast and water-cooled reactors with different fuel compositions have been investigated. The reason of the non-stationary heat exchange is the fuel-energy-release time dependence. (author)

A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

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Muhammad Farhan Ausaf

2015-12-01

Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

Generation of Stationary Non-Gaussian Time Histories with a Specified Cross-spectral Density

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David O. Smallwood

1997-01-01

Full Text Available The paper reviews several methods for the generation of stationary realizations of sampled time histories with non-Gaussian distributions and introduces a new method which can be used to control the cross-spectral density matrix and the probability density functions (pdfs of the multiple input problem. Discussed first are two methods for the specialized case of matching the auto (power spectrum, the skewness, and kurtosis using generalized shot noise and using polynomial functions. It is then shown that the skewness and kurtosis can also be controlled by the phase of a complex frequency domain description of the random process. The general case of matching a target probability density function using a zero memory nonlinear (ZMNL function is then covered. Next methods for generating vectors of random variables with a specified covariance matrix for a class of spherically invariant random vectors (SIRV are discussed. Finally the general case of matching the cross-spectral density matrix of a vector of inputs with non-Gaussian marginal distributions is presented.

Study on multi-objective flexible job-shop scheduling problem considering energy consumption

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Zengqiang Jiang

2014-06-01

Full Text Available Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II based on blood variation for above scheduling model.Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model.Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption.Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.

Detrending of non-stationary noise data by spline techniques

International Nuclear Information System (INIS)

Behringer, K.

1989-11-01

An off-line method for detrending non-stationary noise data has been investigated. It uses a least squares spline approximation of the noise data with equally spaced breakpoints. Subtraction of the spline approximation from the noise signal at each data point gives a residual noise signal. The method acts as a high-pass filter with very sharp frequency cutoff. The cutoff frequency is determined by the breakpoint distance. The steepness of the cutoff is controlled by the spline order. (author) 12 figs., 1 tab., 5 refs

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

Science.gov (United States)

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem

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Jian Gao

2011-08-01

Full Text Available Distributed Permutation Flowshop Scheduling Problem (DPFSP is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper, we propose a GA-based algorithm, denoted by GA_LS, for solving this problem with objective to minimize the maximum completion time. In the proposed GA_LS, crossover and mutation operators are designed to make it suitable for the representation of DPFSP solutions, where the set of partial job sequences is employed. Furthermore, GA_LS utilizes an efficient local search method to explore neighboring solutions. The local search method uses three proposed rules that move jobs within a factory or between two factories. Intensive experiments on the benchmark instances, extended from Taillard instances, are carried out. The results indicate that the proposed hybrid genetic algorithm can obtain better solutions than all the existing algorithms for the DPFSP, since it obtains better relative percentage deviation and differences of the results are also statistically significant. It is also seen that best-known solutions for most instances are updated by our algorithm. Moreover, we also show the efficiency of the GA_LS by comparing with similar genetic algorithms with the existing local search methods.

Hybrid IP/CP Methods for Solving Sports Scheduling Problems

DEFF Research Database (Denmark)

Rasmussen, Rasmus Vinther

2006-01-01

The field of sports scheduling comprises a challenging research areawith a great variety of hard combinatorial optimization problems andchallenging practical applications. This dissertation gives acomprehensive survey of the area and a number of new contributionsare presented. First a general sol...

Heuristics for no-wait flow shop scheduling problem

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Kewal Krishan Nailwal

2016-09-01

Full Text Available No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard’s benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard’s instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.

A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem

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Yongyi Shou

2014-01-01

Full Text Available A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.

Local polynomial Whittle estimation covering non-stationary fractional processes

DEFF Research Database (Denmark)

Nielsen, Frank

to the non-stationary region. By approximating the short-run component of the spectrum by a polynomial, instead of a constant, in a shrinking neighborhood of zero we alleviate some of the bias that the classical local Whittle estimators is prone to. This bias reduction comes at a cost as the variance is in...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....

Artificial immune algorithm for multi-depot vehicle scheduling problems

Science.gov (United States)

Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling

2008-10-01

In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.

Neural networks prediction and fault diagnosis applied to stationary and non stationary ARMA (Autoregressive moving average) modeled time series

International Nuclear Information System (INIS)

Marseguerra, M.; Minoggio, S.; Rossi, A.; Zio, E.

1992-01-01

The correlated noise affecting many industrial plants under stationary or cyclo-stationary conditions - nuclear reactors included -has been successfully modeled by autoregressive moving average (ARMA) due to the versatility of this technique. The relatively recent neural network methods have similar features and much effort is being devoted to exploring their usefulness in forecasting and control. Identifying a signal by means of an ARMA model gives rise to the problem of selecting its correct order. Similar difficulties must be faced when applying neural network methods and, specifically, particular care must be given to the setting up of the appropriate network topology, the data normalization procedure and the learning code. In the present paper the capability of some neural networks of learning ARMA and seasonal ARMA processes is investigated. The results of the tested cases look promising since they indicate that the neural networks learn the underlying process with relative ease so that their forecasting capability may represent a convenient fault diagnosis tool. (Author)

Enhancement of Non-Stationary Speech using Harmonic Chirp Filters

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2015-01-01

In this paper, the issue of single channel speech enhancement of non-stationary voiced speech is addressed. The non-stationarity of speech is well known, but state of the art speech enhancement methods assume stationarity within frames of 20–30 ms. We derive optimal distortionless filters that take...... the non-stationarity nature of voiced speech into account via linear constraints. This is facilitated by imposing a harmonic chirp model on the speech signal. As an implicit part of the filter design, the noise statistics are also estimated based on the observed signal and parameters of the harmonic chirp...... model. Simulations on real speech show that the chirp based filters perform better than their harmonic counterparts. Further, it is seen that the gain of using the chirp model increases when the estimated chirp parameter is big corresponding to periods in the signal where the instantaneous fundamental...

Inference for local autocorrelations in locally stationary models.

Science.gov (United States)

Zhao, Zhibiao

2015-04-01

For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides an important generalization of the R function acf() to locally stationary Gaussian processes. Simulation studies and two empirical applications are developed. For the global temperature series, we find that the local autocorrelations are time-varying and have a "V" shape during 1910-1960. For the S&P 500 index, we conclude that the returns satisfy the efficient-market hypothesis whereas the magnitudes of returns show significant local autocorrelations.

Technical Report: Optimizing the Slab Yard Planning and Crane Scheduling Problem using a Two-Stage Approach

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Clausen, Jens

2008-01-01

In this paper, we present The Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem...... considered here, is concerned with the generation of schedules for these. The problem is decomposed and modeled in two parts, namely a planning problem and a scheduling problem. In the planning problem a set of crane operations is created to take the yard from its current state to a desired goal state...... schedule for the cranes is generated, where each operation is assigned to a crane and is given a specific time of initiation. For both models, a thorough description of the modeling details is given along with a specification of objective criteria. Variants of the models are presented as well. Preliminary...

Optimization of the solution of the problem of scheduling theory ...

African Journals Online (AJOL)

This article describes the genetic algorithm used to solve the problem related to the scheduling theory. A large number of different methods is described in the scientific literature. The main issue that faced the problem in question is that it is necessary to search the optimal solution in a large search space for the set of ...

Cooperated Bayesian algorithm for distributed scheduling problem

Institute of Scientific and Technical Information of China (English)

QIANG Lei; XIAO Tian-yuan

2006-01-01

This paper presents a new distributed Bayesian optimization algorithm (BOA) to overcome the efficiency problem when solving NP scheduling problems.The proposed approach integrates BOA into the co-evolutionary schema,which builds up a concurrent computing environment.A new search strategy is also introduced for local optimization process.It integrates the reinforcement learning(RL) mechanism into the BOA search processes,and then uses the mixed probability information from BOA (post-probability) and RL (pre-probability) to enhance the cooperation between different local controllers,which improves the optimization ability of the algorithm.The experiment shows that the new algorithm does better in both optimization (2.2%) and convergence (11.7%),compared with classic BOA.

A Generalized Ant Colony Algorithm for Job一shop Scheduling Problem

Directory of Open Access Journals (Sweden)

ZHANG Hong-Guo

2017-02-01

Full Text Available Aiming at the problem of ant colony algorithm for solving Job一shop scheduling problem. Considering the complexity of the algorithm that uses disjunctive graph to describe the relationship between workpiece processing. To solve the problem of optimal solution，a generalized ant colony algorithm is proposed. Under the premise of considering constrained relationship between equipment and process，the pheromone update mechanism is applied to solve Job-shop scheduling problem，so as to improve the quality of the solution. In order to improve the search efficiency，according to the state transition rules of ant colony algorithm，this paper makes a detailed study on the selection and improvement of the parameters in the algorithm，and designs the pheromone update strategy. Experimental results show that a generalized ant colony algorithm is more feasible and more effective. Compared with other algorithms in the literature，the results prove that the algorithm improves in computing the optimal solution and convergence speed.

Solving a manpower scheduling problem for airline catering using tabu search

DEFF Research Database (Denmark)

Ho, Sin C.; Leung, Janny M. Y.

We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take off. Jobs (flights) must...

A duty-period-based formulation of the airline crew scheduling problem

Energy Technology Data Exchange (ETDEWEB)

Hoffman, K.

1994-12-31

We present a new formulation of the airline crew scheduling problem that explicitly considers the duty periods. We suggest an algorithm for solving the formulation by a column generation approach with branch-and-bound. Computational results are reported for a number of test problems.

A branch-and-price algorithm for the long-term home care scheduling problem

DEFF Research Database (Denmark)

Gamst, Mette; Jensen, Thomas Sejr

2012-01-01

In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans such that a high quality of service is maintained, the work hours of the employees are respected, and the overall cost is kept as low as possible. We...... propose a branchand-price algorithm for the long-term home care scheduling problem. The pricing problem generates a one-day plan for an employee, and the master problem merges the plans with respect to regularity constraints. The method is capable of generating plans with up to 44 visits during one week....

Assessment of autonomic nervous system by using empirical mode decomposition-based reflection wave analysis during non-stationary conditions

International Nuclear Information System (INIS)

Chang, C C; Hsiao, T C; Kao, S C; Hsu, H Y

2014-01-01

Arterial blood pressure (ABP) is an important indicator of cardiovascular circulation and presents various intrinsic regulations. It has been found that the intrinsic characteristics of blood vessels can be assessed quantitatively by ABP analysis (called reflection wave analysis (RWA)), but conventional RWA is insufficient for assessment during non-stationary conditions, such as the Valsalva maneuver. Recently, a novel adaptive method called empirical mode decomposition (EMD) was proposed for non-stationary data analysis. This study proposed a RWA algorithm based on EMD (EMD-RWA). A total of 51 subjects participated in this study, including 39 healthy subjects and 12 patients with autonomic nervous system (ANS) dysfunction. The results showed that EMD-RWA provided a reliable estimation of reflection time in baseline and head-up tilt (HUT). Moreover, the estimated reflection time is able to assess the ANS function non-invasively, both in normal, healthy subjects and in the patients with ANS dysfunction. EMD-RWA provides a new approach for reflection time estimation in non-stationary conditions, and also helps with non-invasive ANS assessment. (paper)

Comparison of heuristics for an economic lot scheduling problem with deliberated coproduction

Directory of Open Access Journals (Sweden)

Pilar I. Vidal-Carreras

2009-12-01

Full Text Available We built on the Economic Lot Scheduling Problem Scheduling (ELSP literature by making some modifications in order to introduce new constraints which had not been thoroughly studied with a view to simulating specific real situations. Specifically, our aim is to propose and simulate different scheduling policies for a new ELSP variant: Deliberated Coproduction. This problem comprises a product system in an ELSP environment in which we may choose if more than one product can be produced on the machine at a given time. We expressly consider the option of coproducing two products whose demand is not substitutable. In order to draw conclusions, a simulation model and its results were developed in the article by employing modified Bomberger data which include two items that could be produced simultaneously.

A canned food scheduling problem with batch due date

Science.gov (United States)

Chung, Tsui-Ping; Liao, Ching-Jong; Smith, Milton

2014-09-01

This article considers a canned food scheduling problem where jobs are grouped into several batches. Jobs can be sent to the next operation only when all the jobs in the same batch have finished their processing, i.e. jobs in a batch, have a common due date. This batch due date problem is quite common in canned food factories, but there is no efficient heuristic to solve the problem. The problem can be formulated as an identical parallel machine problem with batch due date to minimize the total tardiness. Since the problem is NP hard, two heuristics are proposed to find the near-optimal solution. Computational results comparing the effectiveness and efficiency of the two proposed heuristics with an existing heuristic are reported and discussed.

Does non-standard work mean non-standard health? Exploring links between non-standard work schedules, health behavior, and well-being

Directory of Open Access Journals (Sweden)

Megan R. Winkler

2018-04-01

Full Text Available The last century has seen dramatic shifts in population work circumstances, leading to an increasing normalization of non-standard work schedules (NSWSs, defined as non-daytime, irregular hours. An ever-growing body of evidence links NSWSs to a host of non-communicable chronic conditions; yet, these associations primarily concentrate on the physiologic mechanisms created by circadian disruption and insufficient sleep. While important, not all NSWSs create such chronobiologic disruption, and other aspects of working time and synchronization could be important to the relationships between work schedules and chronic disease. Leveraging survey data from Project EAT, a population-based study with health-related behavioral and psychological data from U.S. adults aged 25–36 years, this study explored the risks for a broad range of less healthful behavioral and well-being outcomes among NSWS workers compared to standard schedule workers (n = 1402. Variations across different NSWSs (evening, night/rotating, and irregular schedules were also explored. Results indicated that, relative to standard schedule workers, workers with NSWSs are at increased risk for non-optimal sleep, substance use, greater recreational screen time, worse dietary practices, obesity, and depression. There was minimal evidence to support differences in relative risks across workers with different types of NSWSs. The findings provide insight into the potential links between NSWSs and chronic disease and indicate the relevancy social disruption and daily health practices may play in the production of health and well-being outcomes among working populations. Keywords: United States, Work schedule tolerance, Health behavior, Mental health, Substance abuse, Obesity

Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.

Science.gov (United States)

Saidi, Lotfi; Ali, Jaouher Ben; Fnaiech, Farhat

2014-09-01

Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Non-stationary discharge patterns in motor cortex under subthalamic nucleus deep brain stimulation.

Science.gov (United States)

Santaniello, Sabato; Montgomery, Erwin B; Gale, John T; Sarma, Sridevi V

2012-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) directly modulates the basal ganglia (BG), but how such stimulation impacts the cortex upstream is largely unknown. There is evidence of cortical activation in 6-hydroxydopamine (OHDA)-lesioned rodents and facilitation of motor evoked potentials in Parkinson's disease (PD) patients, but the impact of the DBS settings on the cortical activity in normal vs. Parkinsonian conditions is still debated. We use point process models to analyze non-stationary activation patterns and inter-neuronal dependencies in the motor and sensory cortices of two non-human primates during STN DBS. These features are enhanced after treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which causes a consistent PD-like motor impairment, while high-frequency (HF) DBS (i.e., ≥100 Hz) strongly reduces the short-term patterns (period: 3-7 ms) both before and after MPTP treatment, and elicits a short-latency post-stimulus activation. Low-frequency DBS (i.e., ≤50 Hz), instead, has negligible effects on the non-stationary features. Finally, by using tools from the information theory [i.e., receiver operating characteristic (ROC) curve and information rate (IR)], we show that the predictive power of these models is dependent on the DBS settings, i.e., the probability of spiking of the cortical neurons (which is captured by the point process models) is significantly conditioned on the timely delivery of the DBS input. This dependency increases with the DBS frequency and is significantly larger for high- vs. low-frequency DBS. Overall, the selective suppression of non-stationary features and the increased modulation of the spike probability suggest that HF STN DBS enhances the neuronal activation in motor and sensory cortices, presumably because of reinforcement mechanisms, which perhaps involve the overlap between feedback antidromic and feed-forward orthodromic responses along the BG-thalamo-cortical loop.

A Monte Carlo simulation model for stationary non-Gaussian processes

DEFF Research Database (Denmark)

Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.

2003-01-01

includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...

Constraint-based job shop scheduling with ILOG SCHEDULER

NARCIS (Netherlands)

Nuijten, W.P.M.; Le Pape, C.

1998-01-01

We introduce constraint-based scheduling and discuss its main principles. An approximation algorithm based on tree search is developed for the job shop scheduling problem using ILOG SCHEDULER. A new way of calculating lower bounds on the makespan of the job shop scheduling problem is presented and

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Muhammad Kamal Amjad

2018-01-01

Full Text Available Flexible Job Shop Scheduling Problem (FJSSP is an extension of the classical Job Shop Scheduling Problem (JSSP. The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

On computation of C-stationary points for equilibrium problems with linear complementarity constraints via homotopy method

Czech Academy of Sciences Publication Activity Database

Červinka, Michal

2010-01-01

Roč. 2010, č. 4 (2010), s. 730-753 ISSN 0023-5954 Institutional research plan: CEZ:AV0Z10750506 Keywords : equilibrium problems with complementarity constraints * homotopy * C-stationarity Subject RIV: BC - Control Systems Theory Impact factor: 0.461, year: 2010 http://library.utia.cas.cz/separaty/2010/MTR/cervinka-on computation of c-stationary points for equilibrium problems with linear complementarity constraints via homotopy method.pdf

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

Science.gov (United States)

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

A survey of techniques applied to non-stationary waveforms in electrical power systems

NARCIS (Netherlands)

Rodrigues, R.P.; Silveira, P.M.; Ribeiro, P.F.

2010-01-01

The well-known and ever-present time-varying and non-stationary nature of waveforms in power systems requires a comprehensive and precise analytical basis that needs to be incorporated in the system studies and analyses. This time-varying behavior is due to continuous changes in system

A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

Science.gov (United States)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

MULTICRITERIA HYBRID FLOW SHOP SCHEDULING PROBLEM: LITERATURE REVIEW, ANALYSIS, AND FUTURE RESEARCH

Directory of Open Access Journals (Sweden)

Marcia de Fatima Morais

2014-12-01

Full Text Available This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future research on this topic, including the following: (i use uniform and dedicated parallel machines, (ii use exact and metaheuristics approaches, (iv develop lower and uppers bounds, relations of dominance and different search strategies to improve the computational time of the exact methods,  (v develop  other types of metaheuristic, (vi work with anticipatory setups, and (vii add constraints faced by the production systems itself.

Non preemptive soft real time scheduler: High deadline meeting rate on overload

Science.gov (United States)

Khalib, Zahereel Ishwar Abdul; Ahmad, R. Badlishah; El-Shaikh, Mohamed

2015-05-01

While preemptive scheduling has gain more attention among researchers, current work in non preemptive scheduling had shown promising result in soft real time jobs scheduling. In this paper we present a non preemptive scheduling algorithm meant for soft real time applications, which is capable of producing better performance during overload while maintaining excellent performance during normal load. The approach taken by this algorithm has shown more promising results compared to other algorithms including its immediate predecessor. We will present the analysis made prior to inception of the algorithm as well as simulation results comparing our algorithm named gutEDF with EDF and gEDF. We are convinced that grouping jobs utilizing pure dynamic parameters would produce better performance.

A Column Generation Approach for Solving the Patient Admission Scheduling Problem

DEFF Research Database (Denmark)

Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper

This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem deals with assigning elective patients to beds, satisfying a number of soft and hard constraints. The problem can be seen as part of the functions of hospital management at an operational level. There exists a sm...... to produce new best solutions for ve out of six instances from a publicly available repository....

A unique Fock quantization for fields in non-stationary spacetimes

International Nuclear Information System (INIS)

Cortez, Jerónimo; Marugán, Guillermo A. Mena; Olmedo, Javier; Velhinho, José M.

2010-01-01

In curved spacetimes, the lack of criteria for the construction of a unique quantization is a fundamental problem undermining the significance of the predictions of quantum field theory. Inequivalent quantizations lead to different physics. Recently, however, some uniqueness results have been obtained for fields in non-stationary settings. In particular, for vacua that are invariant under the background symmetries, a unitary implementation of the classical evolution suffices to pick up a unique Fock quantization in the case of Klein-Gordon fields with time-dependent mass, propagating in a static spacetime whose spatial sections are three-spheres. In fact, the field equation can be reinterpreted as describing the propagation in a Friedmann-Robertson-Walker spacetime after a suitable scaling of the field by a function of time. For this class of fields, we prove here an even stronger result about the Fock quantization: the uniqueness persists when one allows for linear time-dependent transformations of the field in order to account for a scaling by background functions. In total, paying attention to the dynamics, there exists a preferred choice of quantum field, and only one SO(4)-invariant Fock representation for it that respects the standard probabilistic interpretation along the evolution. The result has relevant implications e.g. in cosmology

Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

Science.gov (United States)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

Estimating exponential scheduling preferences

DEFF Research Database (Denmark)

Hjorth, Katrine; Börjesson, Maria; Engelson, Leonid

2015-01-01

of car drivers' route and mode choice under uncertain travel times. Our analysis exposes some important methodological issues related to complex non-linear scheduling models: One issue is identifying the point in time where the marginal utility of being at the destination becomes larger than the marginal......Different assumptions about travelers' scheduling preferences yield different measures of the cost of travel time variability. Only few forms of scheduling preferences provide non-trivial measures which are additive over links in transport networks where link travel times are arbitrarily...... utility of being at the origin. Another issue is that models with the exponential marginal utility formulation suffer from empirical identification problems. Though our results are not decisive, they partly support the constant-affine specification, in which the value of travel time variability...

Dynamics in stationary, non-globally hyperbolic spacetimes

Energy Technology Data Exchange (ETDEWEB)

Seggev, Itai [Enrico Fermi Institute and Department of Physics, University of Chicago, 5640 S Ellis Avenue, Chicago, IL 60637 (United States)

2004-06-07

Classically, the dynamics of a scalar field in a non-globally hyperbolic spacetime is ill-posed. Previously, a prescription was given for defining dynamics in static spacetimes in terms of a second-order operator acting on a Hilbert space defined on static slices. The present work extends this result by giving a similar prescription for defining dynamics in stationary spacetimes obeying certain mild assumptions. The prescription is defined in terms of a first-order operator acting on a different Hilbert space from that used in the static prescription. It preserves the important properties of the earlier prescription: the formal solution agrees with the Cauchy evolution within the domain of dependence, and smooth data of compact support always give rise to smooth solutions. In the static case, the first-order formalism agrees with the second-order formalism (using specifically the Friedrichs extension). Applications to field quantization are also discussed.

Effect of non-stationary climate on infectious gastroenteritis transmission in Japan

OpenAIRE

Onozuka, Daisuke

2014-01-01

Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Sou...

Constraint optimization model of a scheduling problem for a robotic arm in automatic systems

DEFF Research Database (Denmark)

Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten

2014-01-01

are characteristics of the painting process application itself. Unlike spot-welding, painting tasks require movement of the entire robot arm. In addition to minimizing intertask duration, the scheduler must strive to maximize painting quality and the problem is formulated as a multi-objective optimization problem....... The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...... of the entire software system for automatic generation of robot programs for painting....

A hybrid algorithm for flexible job-shop scheduling problem with setup times

Directory of Open Access Journals (Sweden)

Ameni Azzouz

2017-01-01

Full Text Available Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper addresses the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a hybrid algorithm based on genetic algorithm (GA and variable neighbourhood search (VNS to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our algorithm against the available ones in terms of solution quality.

Non-stationary vibrations of a thin viscoelastic orthotropic beam

Czech Academy of Sciences Publication Activity Database

Adámek, V.; Valeš, František; Tikal, B.

2009-01-01

Roč. 71, č. 12 (2009), e2569-e2576 ISSN 0362-546X R&D Projects: GA ČR(CZ) GA101/07/0946 Institutional research plan: CEZ:AV0Z20760514 Keywords : thin beam * non-stationary vibration * analytical solution Subject RIV: BI - Acoustics Impact factor: 1.487, year: 2009 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V0Y-4WB3N8S-4&_user=640952&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1156243286&_rerunOrigin= google &_acct=C000034318&_version=1&_urlVersion=0&_userid=640952&md5=ce096901a3382058455e822a20645820

Classification of Ship Routing and Scheduling Problems in Liner Shipping

DEFF Research Database (Denmark)

Kjeldsen, Karina Hjortshøj

2011-01-01

This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...

New Non-Stationary Gradient Model of Heat-Mass-Electric Charge Transfer in Thin Porous Media

Directory of Open Access Journals (Sweden)

V. Rogankov

2017-10-01

Full Text Available The well-known complicated system of non-equilibrium balance equations for a continuous fluid (f medium needs the new non-Gibbsian model of f-phase to be applicable for description of the heterogeneous porous media (PMs. It should be supplemented by the respective coupled thermal and caloric equations of state (EOS developed specially for PMs to become adequate and solvable for the irreversible transport f-processes. The set of standard assumptions adopted by the linear (or quasi-linear non-equilibrium thermodynamics are based on the empirical gradient-caused correlations between flows and forces. It leads, in particular, to the oversimplified stationary solutions for PMs. The most questionable but typical modeling suppositions of the stationary gradient (SG theory are: 1 the assumption of incompressibility accepted, as a rule, for f-flows; 2 the ignorance of distinctions between the hydrophilic and hydrophobic influence of a porous matrix on the properties; 3 the omission of effects arising due to the concomitant phase intra-porous transitions between the neighboring f-fragments with the sharp differences in densities; 4 the use of exclusively Gibbsian (i.e. homogeneous and everywhere differentiable description of any f-phase in PM; 5 the very restrictive reduction of the mechanical velocity field to its specific potential form in the balance equation of f-motion as well as of the heat velocity field in the balance equation of internal energy; 6 the neglect of the new specific peculiarities arising due to the study of any non-equilibrium PM in the meso- and nano-scales of a finite-size macroscopic (N,V-system of discrete particles. This work is an attempt to develop the alternative non-stationary gradient (NSG model of real irreversible processes in PM. Another aim is to apply it without the above restrictions 1-6 to the description of f-flows through the obviously non-Gibbsian thin porous medium (TPM. We will suppose that it is composed by two

Solving Boundary Value Problem for a Nonlinear Stationary Controllable System with Synthesizing Control

Directory of Open Access Journals (Sweden)

Alexander N. Kvitko

2017-01-01

Full Text Available An algorithm for constructing a control function that transfers a wide class of stationary nonlinear systems of ordinary differential equations from an initial state to a final state under certain control restrictions is proposed. The algorithm is designed to be convenient for numerical implementation. A constructive criterion of the desired transfer possibility is presented. The problem of an interorbital flight is considered as a test example and it is simulated numerically with the presented method.

Timing analysis for embedded systems using non-preemptive EDF scheduling under bounded error arrivals

Directory of Open Access Journals (Sweden)

Michael Short

2017-07-01

Full Text Available Embedded systems consist of one or more processing units which are completely encapsulated by the devices under their control, and they often have stringent timing constraints associated with their functional specification. Previous research has considered the performance of different types of task scheduling algorithm and developed associated timing analysis techniques for such systems. Although preemptive scheduling techniques have traditionally been favored, rapid increases in processor speeds combined with improved insights into the behavior of non-preemptive scheduling techniques have seen an increased interest in their use for real-time applications such as multimedia, automation and control. However when non-preemptive scheduling techniques are employed there is a potential lack of error confinement should any timing errors occur in individual software tasks. In this paper, the focus is upon adding fault tolerance in systems using non-preemptive deadline-driven scheduling. Schedulability conditions are derived for fault-tolerant periodic and sporadic task sets experiencing bounded error arrivals under non-preemptive deadline scheduling. A timing analysis algorithm is presented based upon these conditions and its run-time properties are studied. Computational experiments show it to be highly efficient in terms of run-time complexity and competitive ratio when compared to previous approaches.

Job shop scheduling model for non-identic machine with fixed delivery time to minimize tardiness

Science.gov (United States)

Kusuma, K. K.; Maruf, A.

2016-02-01

Scheduling non-identic machines problem with low utilization characteristic and fixed delivery time are frequent in manufacture industry. This paper propose a mathematical model to minimize total tardiness for non-identic machines in job shop environment. This model will be categorized as an integer linier programming model and using branch and bound algorithm as the solver method. We will use fixed delivery time as main constraint and different processing time to process a job. The result of this proposed model shows that the utilization of production machines can be increase with minimal tardiness using fixed delivery time as constraint.

A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing

Directory of Open Access Journals (Sweden)

Hadi Mokhtari

2015-11-01

Full Text Available In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexible job shop scheduling with controllable processing times (FJCPT, is formulated as an integer non-linear programming (INLP model and then it is converted into an integer linear programming (ILP model. Due to NP-hardness of FJCPT, conventional analytic optimization methods are not efficient. Hence, in order to solve the problem, a Scatter Search (SS, as an efficient metaheuristic method, is developed. To show the effectiveness of the proposed method, numerical experiments are conducted. The efficiency of the proposed algorithm is compared with that of a genetic algorithm (GA available in the literature for solving FJSP problem. The results showed that the proposed SS provide better solutions than the existing GA.

Refinery scheduling

Energy Technology Data Exchange (ETDEWEB)

Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)

2004-07-01

This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)

Time-frequency analysis of non-stationary fusion plasma signals using an improved Hilbert-Huang transform

International Nuclear Information System (INIS)

Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe

2014-01-01

An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas

Expanding the experience of using non-stationary waterflooding technology with changing direction of the filtration flow in the example of the Northern Buzachi field

Directory of Open Access Journals (Sweden)

E.M. Almukhametova

2018-06-01

Full Text Available Abstract. The last few years, work has been carried out to study the effectiveness of non-stationary exposure in the highly viscous oil field Northern Buzachi (Republic of Kazakhstan. It has been proved that this technology is quite effective in the development of highly viscous oil reservoirs, however, in order to constantly maintain high technological effect, a constant modification of this technology is required, since it has a characteristic feature of rapid «aging». Further search for the conditions of effective application of non-stationary exposure on highly-viscous oil deposits can be carried out in two directions: the implementation of non-stationary exposure in new areas with other reservoir parameters and the change in the parameters of non-stationary exposure technology (including combining with other technologies in areas where this technology is already in use. Both approaches are used on the Northern Buzachi field. Thus, the positive experience of using non-stationary waterflooding in combination with changing direction of the filtration flow in the section of the seventh block of the Northern Buzachi field allowed us to recommend new sites for the implementation of this technology. With the participation of the author of this work, a non-stationary waterflooding program was developed and implemented on the site of the sixth block (south of the first operational facility.

Non-Stationary Rician Noise Estimation in Parallel MRI Using a Single Image: A Variance-Stabilizing Approach.

Science.gov (United States)

Pieciak, Tomasz; Aja-Fernandez, Santiago; Vegas-Sanchez-Ferrero, Gonzalo

2017-10-01

Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e., it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.

Discrete harmony search algorithm for scheduling and rescheduling the reprocessing problems in remanufacturing: a case study

Science.gov (United States)

Gao, Kaizhou; Wang, Ling; Luo, Jianping; Jiang, Hua; Sadollah, Ali; Pan, Quanke

2018-06-01

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing reprocessing time and the new subassembly insertion. To optimize the scheduling and rescheduling objective, a discrete harmony search (DHS) algorithm is proposed. To speed up the convergence rate, a local search method is designed. The DHS is applied to two real-life cases for minimizing the maximum completion time and the mean of earliness and tardiness (E/T). These two objectives are also considered together as a bi-objective problem. Computational optimization results and comparisons show that the proposed DHS is able to solve the scheduling and rescheduling problems effectively and productively. Using the proposed approach, satisfactory optimization results can be achieved for scheduling and rescheduling on a real-life shop floor.

From non-preemptive to preemptive scheduling using synchronization synthesis.

Science.gov (United States)

Černý, Pavol; Clarke, Edmund M; Henzinger, Thomas A; Radhakrishna, Arjun; Ryzhyk, Leonid; Samanta, Roopsha; Tarrach, Thorsten

2017-01-01

We present a computer-aided programming approach to concurrency. The approach allows programmers to program assuming a friendly, non-preemptive scheduler, and our synthesis procedure inserts synchronization to ensure that the final program works even with a preemptive scheduler. The correctness specification is implicit, inferred from the non-preemptive behavior. Let us consider sequences of calls that the program makes to an external interface. The specification requires that any such sequence produced under a preemptive scheduler should be included in the set of sequences produced under a non-preemptive scheduler. We guarantee that our synthesis does not introduce deadlocks and that the synchronization inserted is optimal w.r.t. a given objective function. The solution is based on a finitary abstraction, an algorithm for bounded language inclusion modulo an independence relation, and generation of a set of global constraints over synchronization placements. Each model of the global constraints set corresponds to a correctness-ensuring synchronization placement. The placement that is optimal w.r.t. the given objective function is chosen as the synchronization solution. We apply the approach to device-driver programming, where the driver threads call the software interface of the device and the API provided by the operating system. Our experiments demonstrate that our synthesis method is precise and efficient. The implicit specification helped us find one concurrency bug previously missed when model-checking using an explicit, user-provided specification. We implemented objective functions for coarse-grained and fine-grained locking and observed that different synchronization placements are produced for our experiments, favoring a minimal number of synchronization operations or maximum concurrency, respectively.

Generalized Predictive Control for Non-Stationary Systems

DEFF Research Database (Denmark)

Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

1994-01-01

This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...

Scalability of Direct Solver for Non-stationary Cahn-Hilliard Simulations with Linearized time Integration Scheme

KAUST Repository

Woźniak, M.

2016-06-02

We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme with a linearized right-hand side operator. It was applied in solving the Cahn-Hilliard parabolic equation with a nonlinear, fourth-order elliptic part. The second order of the approximation along the time variable was proven. Moreover, the good scalability of the software based on this scheme was confirmed during simulations. We verify the proposed time integration scheme by monitoring the Ginzburg-Landau free energy. The numerical simulations are performed by using a parallel multi-frontal direct solver executed over STAMPEDE Linux cluster. Its scalability was compared to the results of the three direct solvers, including MUMPS, SuperLU and PaSTiX.

Separation of non-stationary multi-source sound field based on the interpolated time-domain equivalent source method

Science.gov (United States)

Bi, Chuan-Xing; Geng, Lin; Zhang, Xiao-Zheng

2016-05-01

In the sound field with multiple non-stationary sources, the measured pressure is the sum of the pressures generated by all sources, and thus cannot be used directly for studying the vibration and sound radiation characteristics of every source alone. This paper proposes a separation model based on the interpolated time-domain equivalent source method (ITDESM) to separate the pressure field belonging to every source from the non-stationary multi-source sound field. In the proposed method, ITDESM is first extended to establish the relationship between the mixed time-dependent pressure and all the equivalent sources distributed on every source with known location and geometry information, and all the equivalent source strengths at each time step are solved by an iterative solving process; then, the corresponding equivalent source strengths of one interested source are used to calculate the pressure field generated by that source alone. Numerical simulation of two baffled circular pistons demonstrates that the proposed method can be effective in separating the non-stationary pressure generated by every source alone in both time and space domains. An experiment with two speakers in a semi-anechoic chamber further evidences the effectiveness of the proposed method.

Self-adaptive change detection in streaming data with non-stationary distribution

KAUST Repository

Zhang, Xiangliang

2010-01-01

Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.

An adaptive large neighborhood search heuristic for the pickup and delivery problem with time Windows and scheduled lines

NARCIS (Netherlands)

Ghilas, V.; Demir, E.; van Woensel, T.

2016-01-01

The Pickup and Delivery Problem with Time Windows and Scheduled Lines (PDPTW-SL) concerns scheduling a set of vehicles to serve freight requests such that a part of the journey can be carried out on a scheduled public transportation line. Due to the complexity of the problem, which is NP-hard, we

On Several Fundamental Problems of Optimization, Estimation, and Scheduling in Wireless Communications

Science.gov (United States)

Gao, Qian

compared with the conventional decoupled system with the same spectrum efficiency to demonstrate the power efficiency. Crucial lighting requirements are included as optimization constraints. To control non-linear distortion, the optical peak-to-average-power ratio (PAPR) of LEDs can be individually constrained. With a SVD-based pre-equalizer designed and employed, our scheme can achieve lower BER than counterparts applying zero-forcing (ZF) or linear minimum-mean-squared-error (LMMSE) based post-equalizers. Besides, a binary switching algorithm (BSA) is applied to improve BER performance. The third part looks into a problem of two-phase channel estimation in a relayed wireless network. The channel estimates in every phase are obtained by the linear minimum mean squared error (LMMSE) method. Inaccurate estimate of the relay to destination (RtD) channel in phase 1 could affect estimate of the source to relay (StR) channel in phase 2, which is made erroneous. We first derive a close-form expression for the averaged Bayesian mean-square estimation error (ABMSE) for both phase estimates in terms of the length of source and relay training slots, based on which an iterative searching algorithm is then proposed that optimally allocates training slots to the two phases such that estimation errors are balanced. Analysis shows how the ABMSE of the StD channel estimation varies with the lengths of relay training and source training slots, the relay amplification gain, and the channel prior information respectively. The last part deals with a transmission scheduling problem in a uplink multiple-input-multiple-output (MIMO) wireless network. Code division multiple access (CDMA) is assumed as a multiple access scheme and pseudo-random codes are employed for different users. We consider a heavy traffic scenario, in which each user always has packets to transmit in the scheduled time slots. If the relay is scheduled for transmission together with users, then it operates in a full

The Simultaneous Vehicle Scheduling and Passenger Service Problem with Flexible Dwell Times

DEFF Research Database (Denmark)

Fonseca, Joao Filipe Paiva; Larsen, Allan; van der Hurk, Evelien

In this talk, we deal with a generalization of the well-known Vehicle Scheduling Problem(VSP) that we call Simultaneous Vehicle Scheduling and Passenger Service Problem with Flexible Dwell Times (SVSPSP-FDT). The SVSPSP-FDT generalizes the VSP because the original timetables of the trips can...... be changed (i.e., shifted and stretched) in order to minimize a new objective function that aims at minimizing the operational costs plus the waiting times of the passengers at transfer points. Contrary to most generalizations of the VSP, the SVSPSP-FDT establishes the possibility of changing trips' dwell...... times at important transfer points based on expected passenger ows. We introduce a compact mixed integer linear formulation of the SVSPSP-FDT able to address small instances. We also present a meta-heuristic approach to solve medium/large instances of the problem. The e ectiveness of the proposed...

Flexible Job Shop Scheduling Problem Using an Improved Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available As an extension of the classical job shop scheduling problem, the flexible job shop scheduling problem (FJSP plays an important role in real production systems. In FJSP, an operation is allowed to be processed on more than one alternative machine. It has been proven to be a strongly NP-hard problem. Ant colony optimization (ACO has been proven to be an efficient approach for dealing with FJSP. However, the basic ACO has two main disadvantages including low computational efficiency and local optimum. In order to overcome these two disadvantages, an improved ant colony optimization (IACO is proposed to optimize the makespan for FJSP. The following aspects are done on our improved ant colony optimization algorithm: select machine rule problems, initialize uniform distributed mechanism for ants, change pheromone’s guiding mechanism, select node method, and update pheromone’s mechanism. An actual production instance and two sets of well-known benchmark instances are tested and comparisons with some other approaches verify the effectiveness of the proposed IACO. The results reveal that our proposed IACO can provide better solution in a reasonable computational time.

Decomposition principles applied to the dynamic production and work-force scheduling problem

NARCIS (Netherlands)

Aardal, K.I.; Ari, A.

1987-01-01

One of the most important problems in the production and inventory planning field, is the scheduling of production and work force in a dynamic environment. Although this problem can be formulated as a linear program, it is often quite difficult to solve directly, due to its large scale. Instead, it

A Hybrid Differential Evolution and Tree Search Algorithm for the Job Shop Scheduling Problem

Directory of Open Access Journals (Sweden)

Rui Zhang

2011-01-01

Full Text Available The job shop scheduling problem (JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a hybrid differential evolution (DE algorithm is proposed for the problem. To enhance the overall search efficiency, a neighborhood property of the problem is discovered, and then a tree search procedure is designed and embedded into the DE framework. According to the extensive computational experiments, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness objective.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

Science.gov (United States)

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in

On the Integrated Job Scheduling and Constrained Network Routing Problem

DEFF Research Database (Denmark)

Gamst, Mette

This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...

Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Tao Ren

2012-01-01

Full Text Available This paper considers the m-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.

Radio-Oxidation in Polyolefins: Non-Stationary Kinetic Conditions

International Nuclear Information System (INIS)

Dely, N.

2006-01-01

In the last fifty years, many authors have been interested in the radio-oxidation processes occurring in polymers. The polymer degradation under ionising radiations in presence of dioxygen is well described by a radical chemistry. The radio-oxidation process occurs in three steps: the first one is the production of radicals P degree by interaction between the polymer and the ionising radiations; then radicals P degree react spontaneously with O 2 solved in the polymer giving a peroxy radical POO degree which attacks the polymer forming a hydroperoxide POOH and a new radical P degree (propagation). The third step corresponds to the termination step, that is bimolecular reactions between radicals. It is generally assumed that the stationary state is rapidly reached and consequently that the oxidation induced during the built-up period of the radical concentration can be neglected. However, to our best knowledge, the temporal evolution of radical concentrations before reaching the steady state regime has never been studied in details. We recently performed a complete study of oxygen consumption under electron irradiation for an EPDM elastomer. An analysis, as function of dose rate and oxygen pressure, and assuming steady state conditions, allowed extracting all the kinetic constants. Starting for these experimental data, we calculated the build-up of the radical concentration by solving numerically the differential equations with help of the Minichem code. We conclude that, in fact, the oxidation induced during the built-up period is negligible. In this paper we show that [P degree] could present a quasi-stationary plateau before reaching its stationary level. Consequently, the full radical time evolution is essentially determined by two characteristic times for reaching the quasi and stationary levels and three concentrations: [P degree] and [POO degree] at the stationary level and [P degree] at the quasi-stationary plateau. We show that realistic approximations can

Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method

Directory of Open Access Journals (Sweden)

Beata Palczynska

2017-05-01

Full Text Available The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.

Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

Science.gov (United States)

Santosa, B.; Siswanto, N.; Fiqihesa

2018-04-01

This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

Distinguishing Stationary/Nonstationary Scaling Processes Using Wavelet Tsallis q-Entropies

Directory of Open Access Journals (Sweden)

Julio Ramirez Pacheco

2012-01-01

Full Text Available Classification of processes as stationary or nonstationary has been recognized as an important and unresolved problem in the analysis of scaling signals. Stationarity or nonstationarity determines not only the form of autocorrelations and moments but also the selection of estimators. In this paper, a methodology for classifying scaling processes as stationary or nonstationary is proposed. The method is based on wavelet Tsallis q-entropies and particularly on the behaviour of these entropies for scaling signals. It is demonstrated that the observed wavelet Tsallis q-entropies of 1/f signals can be modeled by sum-cosh apodizing functions which allocates constant entropies to a set of scaling signals and varying entropies to the rest and that this allocation is controlled by q. The proposed methodology, therefore, differentiates stationary signals from non-stationary ones based on the observed wavelet Tsallis entropies for 1/f signals. Experimental studies using synthesized signals confirm that the proposed method not only achieves satisfactorily classifications but also outperforms current methods proposed in the literature.

Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

Directory of Open Access Journals (Sweden)

Hongtao Hu

2016-01-01

Full Text Available A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.

Job scheduling in a heterogenous grid environment

Energy Technology Data Exchange (ETDEWEB)

Oliker, Leonid; Biswas, Rupak; Shan, Hongzhang; Smith, Warren

2004-02-11

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.

Dynamic Appliances Scheduling in Collaborative MicroGrids System

Science.gov (United States)

Bilil, Hasnae; Aniba, Ghassane; Gharavi, Hamid

2017-01-01

In this paper a new approach which is based on a collaborative system of MicroGrids (MG’s), is proposed to enable household appliance scheduling. To achieve this, appliances are categorized into flexible and non-flexible Deferrable Loads (DL’s), according to their electrical components. We propose a dynamic scheduling algorithm where users can systematically manage the operation of their electric appliances. The main challenge is to develop a flattening function calculus (reshaping) for both flexible and non-flexible DL’s. In addition, implementation of the proposed algorithm would require dynamically analyzing two successive multi-objective optimization (MOO) problems. The first targets the activation schedule of non-flexible DL’s and the second deals with the power profiles of flexible DL’s. The MOO problems are resolved by using a fast and elitist multi-objective genetic algorithm (NSGA-II). Finally, in order to show the efficiency of the proposed approach, a case study of a collaborative system that consists of 40 MG’s registered in the load curve for the flattening program has been developed. The results verify that the load curve can indeed become very flat by applying the proposed scheduling approach. PMID:28824226

A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions

Science.gov (United States)

Feng, Ke; Wang, Kesheng; Ni, Qing; Zuo, Ming J.; Wei, Dongdong

2017-11-01

Planetary gearbox is a critical component for rotating machinery. It is widely used in wind turbines, aerospace and transmission systems in heavy industry. Thus, it is important to monitor planetary gearboxes, especially for fault diagnostics, during its operational conditions. However, in practice, operational conditions of planetary gearbox are often characterized by variations of rotational speeds and loads, which may bring difficulties for fault diagnosis through the measured vibrations. In this paper, phase angle data extracted from measured planetary gearbox vibrations is used for fault detection under non-stationary operational conditions. Together with sample entropy, fault diagnosis on planetary gearbox is implemented. The proposed scheme is explained and demonstrated in both simulation and experimental studies. The scheme proves to be effective and features advantages on fault diagnosis of planetary gearboxes under non-stationary operational conditions.

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

Science.gov (United States)

Tang, Dunbing; Dai, Min

2015-09-01

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

Direct estimation and correction of bias from temporally variable non-stationary noise in a channelized Hotelling model observer.

Science.gov (United States)

Fetterly, Kenneth A; Favazza, Christopher P

2016-08-07

Channelized Hotelling model observer (CHO) methods were developed to assess performance of an x-ray angiography system. The analytical methods included correction for known bias error due to finite sampling. Detectability indices ([Formula: see text]) corresponding to disk-shaped objects with diameters in the range 0.5-4 mm were calculated. Application of the CHO for variable detector target dose (DTD) in the range 6-240 nGy frame(-1) resulted in [Formula: see text] estimates which were as much as 2.9×  greater than expected of a quantum limited system. Over-estimation of [Formula: see text] was presumed to be a result of bias error due to temporally variable non-stationary noise. Statistical theory which allows for independent contributions of 'signal' from a test object (o) and temporally variable non-stationary noise (ns) was developed. The theory demonstrates that the biased [Formula: see text] is the sum of the detectability indices associated with the test object [Formula: see text] and non-stationary noise ([Formula: see text]). Given the nature of the imaging system and the experimental methods, [Formula: see text] cannot be directly determined independent of [Formula: see text]. However, methods to estimate [Formula: see text] independent of [Formula: see text] were developed. In accordance with the theory, [Formula: see text] was subtracted from experimental estimates of [Formula: see text], providing an unbiased estimate of [Formula: see text]. Estimates of [Formula: see text] exhibited trends consistent with expectations of an angiography system that is quantum limited for high DTD and compromised by detector electronic readout noise for low DTD conditions. Results suggest that these methods provide [Formula: see text] estimates which are accurate and precise for [Formula: see text]. Further, results demonstrated that the source of bias was detector electronic readout noise. In summary, this work presents theory and methods to test for the

Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion

DEFF Research Database (Denmark)

Skjærbæk, P. S.; Kirkegaard, Poul Henning; Fouskitakis, G. N.

1997-01-01

This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour...... by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network based one gives somewhat poorer simulation results....

Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion

DEFF Research Database (Denmark)

Skjærbæk, P. S.; Kirkegaard, Poul Henning; Fouskitakis, G. N.

This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modelling and simulation of this behaviour...... by an epicentral distance of 16 km and measured during the 1979 Imperial valley earthquake in California (USA). The results of the study indicate that while all three approaches can succesfully predict near-source ground motions, the Neural Network based one gives somewhat poorer simulation results....

Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

Directory of Open Access Journals (Sweden)

Yahong Zheng

2014-05-01

Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.

A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

Science.gov (United States)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.

Multi-objective optimization of short-term hydrothermal scheduling using non-dominated sorting gravitational search algorithm with chaotic mutation

International Nuclear Information System (INIS)

Tian, Hao; Yuan, Xiaohui; Ji, Bin; Chen, Zhihuan

2014-01-01

Highlights: • An improved non-dominated sorting gravitational search algorithm (NSGSA-CM) is proposed. • NSGSA-CM is used to solve the problem of short-term multi-objective hydrothermal scheduling. • We enhance the search capability of NSGSA-CM by chaotic mutation. • New strategies are devised to handle various constraints in NSGSA-CM. • We obtain better compromise solutions with less fuel cost and emissions. - Abstract: This paper proposes a non-dominated sorting gravitational search algorithm with chaotic mutation (NSGSA-CM) to solve short-term economic/environmental hydrothermal scheduling (SEEHTS) problem. The SEEHTS problem is formulated as a multi-objective optimization problem with many equality and inequality constraints. By introducing the concept of non-dominated sorting and crowding distance, NSGSA-CM can optimize two objectives of fuel cost and pollutant emission simultaneously and obtain a set of Pareto optimal solutions in one trial. In order to improve the performance of NSGSA-CM, the paper introduces particle memory character and population social information in velocity update process. And a chaotic mutation is adopted to prevent the premature convergence. Furthermore, NSGSA-CM utilizes an elitism strategy which selects better solutions in parent and offspring populations based on their non-domination rank and crowding distance to update new generations. When dealing with the constraints of the SEEHTS, new strategies without penalty factors are proposed. In order to handle the water dynamic balance and system load balance constraints, this paper uses a combined strategy which adjusts the violation averagely to each decision variable at first and adjusts the rest violation randomly later. Meanwhile, a new symmetrical adjustment strategy by modifying the discharges at current and later interval without breaking water dynamic balance is adopted to handle reservoir storage constraints. To test the performance of the proposed NSGSA

An Algorithm for the Weighted Earliness-Tardiness Unconstrained Project Scheduling Problem

Science.gov (United States)

Afshar Nadjafi, Behrouz; Shadrokh, Shahram

This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported.

Optimising the Slab Yard Planning and Crane Scheduling Problem using a two-stage heuristic

DEFF Research Database (Denmark)

Hansen, Anders Dohn; Clausen, Jens

2010-01-01

In this paper, we present the Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem...

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

Science.gov (United States)

Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

Science.gov (United States)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Non-stationary Condition Monitoring of large diesel engines with the AEWATT toolbox

DEFF Research Database (Denmark)

Pontoppidan, Niels Henrik; Larsen, Jan; Sigurdsson, Sigurdur

2005-01-01

We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this toolbox has so far been the utilization of adaptive linear models such as Principal and Independent Component Ana......, the inversion of those angular timing changes called “event alignment”, has allowed for condition monitoring across operation load settings, successfully enabling a single model to be used with realistic data under varying operational conditions-...

Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series

Science.gov (United States)

Vicente, Raul; Díaz-Pernas, Francisco J.; Wibral, Michael

2014-01-01

Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and

Two parameter-tuned metaheuristic algorithms for the multi-level lot sizing and scheduling problem

Directory of Open Access Journals (Sweden)

S.M.T. Fatemi Ghomi

2012-10-01

Full Text Available This paper addresses the problem of lot sizing and scheduling problem for n-products and m-machines in flow shop environment where setups among machines are sequence-dependent and can be carried over. Many products must be produced under capacity constraints and allowing backorders. Since lot sizing and scheduling problems are well-known strongly NP-hard, much attention has been given to heuristics and metaheuristics methods. This paper presents two metaheuristics algorithms namely, Genetic Algorithm (GA and Imperialist Competitive Algorithm (ICA. Moreover, Taguchi robust design methodology is employed to calibrate the parameters of the algorithms for different size problems. In addition, the parameter-tuned algorithms are compared against a presented lower bound on randomly generated problems. At the end, comprehensive numerical examples are presented to demonstrate the effectiveness of the proposed algorithms. The results showed that the performance of both GA and ICA are very promising and ICA outperforms GA statistically.

SU-F-I-80: Correction for Bias in a Channelized Hotelling Model Observer Caused by Temporally Variable Non-Stationary Noise

International Nuclear Information System (INIS)

Favazza, C; Fetterly, K

2016-01-01

Purpose: Application of a channelized Hotelling model observer (CHO) over a wide range of x-ray angiography detector target dose (DTD) levels demonstrated substantial bias for conditions yielding low detectability indices (d’), including low DTD and small test objects. The purpose of this work was to develop theory and methods to correct this bias. Methods: A hypothesis was developed wherein the measured detectability index (d’b) for a known test object is positively biased by temporally variable non-stationary noise in the images. Hotelling’s T2 test statistic provided the foundation for a mathematical theory which accounts for independent contributions to the measured d’b value from both the test object (d’o) and non-stationary noise (d’ns). Experimental methods were developed to directly estimate d’o by determining d’ns and subtracting it from d’b, in accordance with the theory. Specifically, d’ns was determined from two sets of images from which the traditional test object was withheld. This method was applied to angiography images with DTD levels in the range 0 to 240 nGy and for disk-shaped iodine-based contrast targets with diameters 0.5 to 4.0 mm. Results: Bias in d’ was evidenced by d’b values which exceeded values expected from a quantum limited imaging system and decreasing object size and DTD. d’ns increased with decreasing DTD, reaching a maximum of 2.6 for DTD = 0. Bias-corrected d’o estimates demonstrated sub-quantum limited performance of the x-ray angiography for low DTD. Findings demonstrated that the source of non-stationary noise was detector electronic readout noise. Conclusion: Theory and methods to estimate and correct bias in CHO measurements from temporally variable non-stationary noise were presented. The temporal non-stationary noise was shown to be due to electronic readout noise. This method facilitates accurate estimates of d’ values over a large range of object size and detector target dose.

SU-F-I-80: Correction for Bias in a Channelized Hotelling Model Observer Caused by Temporally Variable Non-Stationary Noise

Energy Technology Data Exchange (ETDEWEB)

Favazza, C; Fetterly, K [Mayo Clinic, Rochester, MN (United States)

2016-06-15

Purpose: Application of a channelized Hotelling model observer (CHO) over a wide range of x-ray angiography detector target dose (DTD) levels demonstrated substantial bias for conditions yielding low detectability indices (d’), including low DTD and small test objects. The purpose of this work was to develop theory and methods to correct this bias. Methods: A hypothesis was developed wherein the measured detectability index (d’b) for a known test object is positively biased by temporally variable non-stationary noise in the images. Hotelling’s T2 test statistic provided the foundation for a mathematical theory which accounts for independent contributions to the measured d’b value from both the test object (d’o) and non-stationary noise (d’ns). Experimental methods were developed to directly estimate d’o by determining d’ns and subtracting it from d’b, in accordance with the theory. Specifically, d’ns was determined from two sets of images from which the traditional test object was withheld. This method was applied to angiography images with DTD levels in the range 0 to 240 nGy and for disk-shaped iodine-based contrast targets with diameters 0.5 to 4.0 mm. Results: Bias in d’ was evidenced by d’b values which exceeded values expected from a quantum limited imaging system and decreasing object size and DTD. d’ns increased with decreasing DTD, reaching a maximum of 2.6 for DTD = 0. Bias-corrected d’o estimates demonstrated sub-quantum limited performance of the x-ray angiography for low DTD. Findings demonstrated that the source of non-stationary noise was detector electronic readout noise. Conclusion: Theory and methods to estimate and correct bias in CHO measurements from temporally variable non-stationary noise were presented. The temporal non-stationary noise was shown to be due to electronic readout noise. This method facilitates accurate estimates of d’ values over a large range of object size and detector target dose.

A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Hamed Piroozfard

2016-01-01

Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.

Heuristics methods for the flow shop scheduling problem with separated setup times

Directory of Open Access Journals (Sweden)

Marcelo Seido Nagano

2012-06-01

Full Text Available This paper deals with the permutation flow shop scheduling problem with separated machine setup times. As a result of an investigation on the problem characteristics, four heuristics methods are proposed with procedures of the construction sequencing solution by an analogy with the asymmetric traveling salesman problem with the objective of minimizing makespan. Experimental results show that one of the new heuristics methods proposed provide high quality solutions in comparisons with the evaluated methods considered in the literature.

Subroutine MLTGRD: a multigrid algorithm based on multiplicative correction and implicit non-stationary iteration

International Nuclear Information System (INIS)

Barry, J.M.; Pollard, J.P.

1986-11-01

A FORTRAN subroutine MLTGRD is provided to solve efficiently the large systems of linear equations arising from a five-point finite difference discretisation of some elliptic partial differential equations. MLTGRD is a multigrid algorithm which provides multiplicative correction to iterative solution estimates from successively reduced systems of linear equations. It uses the method of implicit non-stationary iteration for all grid levels

Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem

Directory of Open Access Journals (Sweden)

Cheng Chen

2014-01-01

Full Text Available Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.

Exact and heuristic solution approaches for the Integrated Job Scheduling and Constrained Network Routing Problem

DEFF Research Database (Denmark)

Gamst, M.

2014-01-01

problem. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results show that solving the integrated job scheduling and constrained network routing problem to optimality is very difficult. The exact solution approach performs......This paper examines the problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job has a certain demand, which must be sent to the executing machine via constrained paths. A job cannot start before all its demands have...... arrived at the machine. Furthermore, two resource demand transmissions cannot use the same edge in the same time period. The problem has application in grid computing, where a number of geographically distributed machines work together for solving large problems. The machines are connected through...

Comparison of postoperative surgical site infection after preoperative marking done with non-sterile stationary grade markers versus sterile surgical markers

International Nuclear Information System (INIS)

Mir, Z.A.

2015-01-01

Objectives: To compare the frequencies of post- operative surgical site infection after preoperative marking done with non-sterile stationary. grade markers versus sterile surgical markers in the same patient. Design: Randomized control trial. Place and Duration of Study: The department of Plastic surgery, Mayo hospital, Lahore from August 2013 to August 2014. Methods: This study was conducted after taking approval from the departmental ethical committee. Forty consecutive patients were included. A sterile surgical marker was used to mark one incision site while an alcohol based stationary grade marker was used to mark another incision site on the same patient. A standard preoperative, intraoperative and postoperative protocol was followed. Cultures were performed on swabs taken from the incision sites and surgical site infection was assessed for 30 days. Results: The study included 40 patients; 17 males and 23 females. The mean age of subjects was 25.32 ± 19.69 years with the minimum age being 2 years and the maximum being 63 years. No growth was seen in cultures taken from all the incision sites after skin preparation in the non sterile stationary grade marker group as well as the sterile surgical grade marker group. Also no surgical site infection appeared during the 30 day postoperative observation period in the non sterile stationary grade marker group as well as the sterile surgical grade marker group. (author)

A tabu-search heuristic for solving the multi-depot vehicle scheduling problem

Directory of Open Access Journals (Sweden)

Gilmar D'Agostini Oliveira Casalinho

2014-08-01

Full Text Available Currently the logistical problems are relying quite significantly on Operational Research in order to achieve greater efficiency in their operations. Among the problems related to the vehicles scheduling in a logistics system, the Multiple Depot Vehicle Scheduling Problem (MDVSP has been addressed in several studies. The MDVSP presupposes the existence of depots that affect the planning of sequences to which travel must be performed. Often, exact methods cannot solve large instances encountered in practice and in order to take them into account, several heuristic approaches are being developed. The aim of this study was thus to solve the MDVSP using a meta-heuristic based on tabu-search method. The main motivation for this work came from the indication that only recently the use of meta-heuristics is being applied to MDVSP context (Pepin et al. 2008 and, also, the limitations listed by Rohde (2008 in his study, which used the branch-and-bound in one of the steps of the heuristic presented to solve the problem, which has increased the time resolution. The research method for solving this problem was based on adaptations of traditional techniques of Operational Research, and provided resolutions presenting very competitive results for the MDVSP such as the cost of the objective function, number of vehicles used and computational time.

Preemptive and Non-Preemptive Real-Time UniProcessor Scheduling

OpenAIRE

George , Laurent; Rivierre , Nicolas; Spuri , Marco

1996-01-01

Projet REFLECS; Scheduling theory, as it applies to hard-real-time environment, has been widely studied in the last twenty years and it might be unclear to make it out within the plethora of results available. Our goal is first to collect in a single paper the results known for uniproces sor, non-idling, preemptive/non-preemptive, fixed/dynamic priority driven contexts, consid ering general task sets as a central figure for the description of possible processor loads. Second to establish new ...

Using Coevolution Genetic Algorithm with Pareto Principles to Solve Project Scheduling Problem under Duration and Cost Constraints

Directory of Open Access Journals (Sweden)

Alexandr Victorovich Budylskiy

2014-06-01

Full Text Available This article considers the multicriteria optimization approach using the modified genetic algorithm to solve the project-scheduling problem under duration and cost constraints. The work contains the list of choices for solving this problem. The multicriteria optimization approach is justified here. The study describes the Pareto principles, which are used in the modified genetic algorithm. We identify the mathematical model of the project-scheduling problem. We introduced the modified genetic algorithm, the ranking strategies, the elitism approaches. The article includes the example.

Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem

Directory of Open Access Journals (Sweden)

Biao Yuan

2017-11-01

Full Text Available The aggravating trend of the aging population, the miniaturization of the family structure, and the increase of families with empty nesters greatly affect the sustainable development of the national economy and social old-age security system of China. The emergence of home health care or home care (HHC/HC service mode provides an alternative for elderly care. How to develop and apply this new mobile service mode is crucial for the government. Therefore, the pertinent optimization problems regarding HHC/HC have constantly attracted the attention of researchers. Unexpected events, such as new requests of customers, cancellations of customers’ services, and changes of customers’ time windows, may occur during the process of executing an a priori visiting plan. These events may sometimes make the original plan non-optimal or even infeasible. To cope with this situation, we introduce disruption management to the real-time home caregiver scheduling and routing problem. The deviation measurements on customers, caregivers, and companies are first defined. A mathematical model that minimizes the weighted sum of deviation measurements is then constructed. Next, a tabu search (TS heuristic is developed to efficiently solve the problem, and a cost recorded mechanism is used to strengthen the performance. Finally, by performing computational experiments on three real-life instances, the effectiveness of the TS heuristic is tested, and the advantages of disruption management are analyzed.

On globally static and stationary cosmologies with or without a cosmological constant and the dark energy problem

International Nuclear Information System (INIS)

Buchert, Thomas

2006-01-01

In the framework of spatially averaged inhomogeneous cosmologies in classical general relativity, effective Einstein equations govern the regional and the global dynamics of averaged scalar variables of cosmological models. A particular solution may be characterized by a cosmic equation of state. In this paper, it is pointed out that a globally static averaged dust model is conceivable without employing a compensating cosmological constant. Much in the spirit of Einstein's original model we discuss consequences for the global, but also for the regional properties of this cosmology. We then consider the wider class of globally stationary cosmologies that are conceivable in the presented framework. All these models are based on exact solutions of the averaged Einstein equations and provide examples of cosmologies in an out-of-equilibrium state, which we characterize by an information-theoretical measure. It is shown that such cosmologies preserve high-magnitude kinematical fluctuations and so tend to maintain their global properties. The same is true for a Λ-driven cosmos in such a state despite exponential expansion. We outline relations to inflationary scenarios and put the dark energy problem into perspective. Here, it is argued, on the grounds of the discussed cosmologies, that a classical explanation of dark energy through backreaction effects is theoretically conceivable, if the matter-dominated universe emerged from a non-perturbative state in the vicinity of the stationary solution. We also discuss a number of caveats that furnish strong counter arguments in the framework of structure formation in a perturbed Friedmannian model

Estimating return levels from maxima of non-stationary random sequences using the Generalized PWM method

Directory of Open Access Journals (Sweden)

P. Ribereau

2008-12-01

Full Text Available Since the pioneering work of Landwehr et al. (1979, Hosking et al. (1985 and their collaborators, the Probability Weighted Moments (PWM method has been very popular, simple and efficient to estimate the parameters of the Generalized Extreme Value (GEV distribution when modeling the distribution of maxima (e.g., annual maxima of precipitations in the Identically and Independently Distributed (IID context. When the IID assumption is not satisfied, a flexible alternative, the Maximum Likelihood Estimation (MLE approach offers an elegant way to handle non-stationarities by letting the GEV parameters to be time dependent. Despite its qualities, the MLE applied to the GEV distribution does not always provide accurate return level estimates, especially for small sample sizes or heavy tails. These drawbacks are particularly true in some non-stationary situations. To reduce these negative effects, we propose to extend the PWM method to a more general framework that enables us to model temporal covariates and provide accurate GEV-based return levels. Theoretical properties of our estimators are discussed. Small and moderate sample sizes simulations in a non-stationary context are analyzed and two brief applications to annual maxima of CO₂ and seasonal maxima of cumulated daily precipitations are presented.

Automatically stable discontinuous Petrov-Galerkin methods for stationary transport problems: Quasi-optimal test space norm

KAUST Repository

Niemi, Antti H.

2013-12-01

We investigate the application of the discontinuous Petrov-Galerkin (DPG) finite element framework to stationary convection-diffusion problems. In particular, we demonstrate how the quasi-optimal test space norm improves the robustness of the DPG method with respect to vanishing diffusion. We numerically compare coarse-mesh accuracy of the approximation when using the quasi-optimal norm, the standard norm, and the weighted norm. Our results show that the quasi-optimal norm leads to more accurate results on three benchmark problems in two spatial dimensions. We address the problems associated to the resolution of the optimal test functions with respect to the quasi-optimal norm by studying their convergence numerically. In order to facilitate understanding of the method, we also include a detailed explanation of the methodology from the algorithmic point of view. © 2013 Elsevier Ltd. All rights reserved.

Automatically stable discontinuous Petrov-Galerkin methods for stationary transport problems: Quasi-optimal test space norm

KAUST Repository

Niemi, Antti H.; Collier, Nathan; Calo, Victor M.

2013-01-01

We investigate the application of the discontinuous Petrov-Galerkin (DPG) finite element framework to stationary convection-diffusion problems. In particular, we demonstrate how the quasi-optimal test space norm improves the robustness of the DPG method with respect to vanishing diffusion. We numerically compare coarse-mesh accuracy of the approximation when using the quasi-optimal norm, the standard norm, and the weighted norm. Our results show that the quasi-optimal norm leads to more accurate results on three benchmark problems in two spatial dimensions. We address the problems associated to the resolution of the optimal test functions with respect to the quasi-optimal norm by studying their convergence numerically. In order to facilitate understanding of the method, we also include a detailed explanation of the methodology from the algorithmic point of view. © 2013 Elsevier Ltd. All rights reserved.

Assessing the extent of non-stationary biases in GCMs

Science.gov (United States)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-06-01

General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

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Laxmi A. Bewoor

2017-10-01

Full Text Available The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.

Efficient bounding schemes for the two-center hybrid flow shop scheduling problem with removal times.

Science.gov (United States)

Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.

Uplink Packet-Data Scheduling in DS-CDMA Systems

Science.gov (United States)

Choi, Young Woo; Kim, Seong-Lyun

In this letter, we consider the uplink packet scheduling for non-real-time data users in a DS-CDMA system. As an effort to jointly optimize throughput and fairness, we formulate a time-span minimization problem incorporating the time-multiplexing of different simultaneous transmission schemes. Based on simple rules, we propose efficient scheduling algorithms and compare them with the optimal solution obtained by linear programming.

JIT single machine scheduling problem with periodic preventive maintenance

Science.gov (United States)

Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani

2016-09-01

This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms.

Meta-heuristic algorithms for parallel identical machines scheduling problem with weighted late work criterion and common due date.

Science.gov (United States)

Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie

2015-01-01

To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA.

Stability and instability of stationary solutions for sublinear parabolic equations

Science.gov (United States)

Kajikiya, Ryuji

2018-01-01

In the present paper, we study the initial boundary value problem of the sublinear parabolic equation. We prove the existence of solutions and investigate the stability and instability of stationary solutions. We show that a unique positive and a unique negative stationary solutions are exponentially stable and give the exact exponent. We prove that small stationary solutions are unstable. For one space dimensional autonomous equations, we elucidate the structure of stationary solutions and study the stability of all stationary solutions.

Reproductive autonomy, the non-identity problem, and the non-person problem.

Science.gov (United States)

DiSilvestro, Russell

2009-01-01

The Non-Identity Problem is the problem of explaining the apparent wrongness of a decision that does not harm people, especially since some of the people affected by the decision would not exist at all were it not for the decision. One approach to this problem, in the context of reproductive decisions, is to focus on wronging, rather than harming, one's offspring. But a Non-Person Problem emerges for any view that claims (1) that only persons can be wronged and (2) that the person-making properties allow for there to be human non-persons. Consider an individual human organism that is prevented from ever possessing the person-making properties. On person-only accounts of the victims of wronging, this organism cannot be wronged by anyone. Hence even individuals whose decisions prevent it from ever possessing the person-making properties cannot wrong it. But this is counter-intuitive. We can think of examples where a human organism is wronged by precisely those decisions that prevent it from possessing the person-making properties. The best solution to this problem, in the case where the person-making property is rational self-governance in pursuit of a meaningful life, is to adjust the concept of a person so that it refers, not merely to those with the immediate capacity for rational self-governance in pursuit of a meaningful life, but also to those with a higher-order capacity for such self-governance. Any solution to the Non-Identity Problem that focuses on wronging rather than harming should incorporate this sort of solution to the Non-Person Problem.

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Science.gov (United States)

Richards, Stephen F.

1991-01-01

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

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Tao Ren

2015-01-01

Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

Scaling Non-Regular Shared-Memory Codes by Reusing Custom Loop Schedules

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Dimitrios S. Nikolopoulos

2003-01-01

Full Text Available In this paper we explore the idea of customizing and reusing loop schedules to improve the scalability of non-regular numerical codes in shared-memory architectures with non-uniform memory access latency. The main objective is to implicitly setup affinity links between threads and data, by devising loop schedules that achieve balanced work distribution within irregular data spaces and reusing them as much as possible along the execution of the program for better memory access locality. This transformation provides a great deal of flexibility in optimizing locality, without compromising the simplicity of the shared-memory programming paradigm. In particular, the programmer does not need to explicitly distribute data between processors. The paper presents practical examples from real applications and experiments showing the efficiency of the approach.

Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.

Science.gov (United States)

Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan

2016-01-01

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.

Scheduling with Time Lags

NARCIS (Netherlands)

X. Zhang (Xiandong)

2010-01-01

textabstractScheduling is essential when activities need to be allocated to scarce resources over time. Motivated by the problem of scheduling barges along container terminals in the Port of Rotterdam, this thesis designs and analyzes algorithms for various on-line and off-line scheduling problems

Detection of unusual events and trends in complex non-stationary data streams

International Nuclear Information System (INIS)

Charlton-Perez, C.; Perez, R.B.; Protopopescu, V.; Worley, B.A.

2011-01-01

The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for diverse applications, ranging from power plant operation to homeland security. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden events inside intermittent signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method.

Exponentially Stable Stationary Solutions for Stochastic Evolution Equations and Their Perturbation

International Nuclear Information System (INIS)

Caraballo, Tomas; Kloeden, Peter E.; Schmalfuss, Bjoern

2004-01-01

We consider the exponential stability of stochastic evolution equations with Lipschitz continuous non-linearities when zero is not a solution for these equations. We prove the existence of anon-trivial stationary solution which is exponentially stable, where the stationary solution is generated by the composition of a random variable and the Wiener shift. We also construct stationary solutions with the stronger property of attracting bounded sets uniformly. The existence of these stationary solutions follows from the theory of random dynamical systems and their attractors. In addition, we prove some perturbation results and formulate conditions for the existence of stationary solutions for semilinear stochastic partial differential equations with Lipschitz continuous non-linearities

Variable Neighbourhood Search and Mathematical Programming for Just-in-Time Job-Shop Scheduling Problem

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Sunxin Wang

2014-01-01

Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.

A Priority Rule-Based Heuristic for Resource Investment Project Scheduling Problem with Discounted Cash Flows and Tardiness Penalties

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Amir Abbas Najafi

2009-01-01

Full Text Available Resource investment problem with discounted cash flows (RIPDCFs is a class of project scheduling problem. In RIPDCF, the availability levels of the resources are considered decision variables, and the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, we consider a new RIPDCF in which tardiness of project is permitted with defined penalty. We mathematically formulated the problem and developed a heuristic method to solve it. The results of the performance analysis of the proposed method show an effective solution approach to the problem.

Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

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H Kazemipoor

2012-04-01

Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.

Internal and external moisture transport resistance during non-stationary adsorption of moisture into wood

OpenAIRE

Bučar, Bojan

2007-01-01

The assumption that non-stationary sorption processes associated with wood canbe evaluated by analysis of their transient system response to the disturbance developed is undoubtedly correct. In general it is, in fact, possible to obtain by time analysis of the transient phenomenon - involving the transition into an arbitrary new state of equilibrium - all data required for a credible evaluation of the observed system. Evaluation of moisture movement during drying or moistening requires determ...

Generalized boundary conditions in an existence and uniqueness proof for the solution of the non-stationary electron Boltzmann equation by means of operator-semigroups

International Nuclear Information System (INIS)

Bartolomaeus, G.; Wilhelm, J.

1983-01-01

Recently, based on the semigroup approach a new proof was presented of the existence of a unique solution of the non-stationary Boltzmann equation for the electron component of a collision dominated plasma. The proof underlies some restriction which should be overcome to extend the validity range to other problems of physical interest. One of the restrictions is the boundary condition applied. The choice of the boundary condition is essential for the proof because it determines the range of definition of the infinitesimal generator and thus the operator semigroup itself. The paper proves the existence of a unique solution for generalized boundary conditions, this solution takes non-negative values, which is necessary for a distribution function from the physical point of view. (author)

Dynamic Vehicle Scheduling for Working Service Network with Dual Demands

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Bing Li

2017-01-01

Full Text Available This study aims to develop some models to aid in making decisions on the combined fleet size and vehicle assignment in working service network where the demands include two types (minimum demands and maximum demands, and vehicles themselves can act like a facility to provide services when they are stationary at one location. This type of problem is named as the dynamic working vehicle scheduling with dual demands (DWVS-DD and formulated as a mixed integer programming (MIP. Instead of a large integer program, the problem is decomposed into small local problems that are guided by preset control parameters. The approach for preset control parameters is given. By introducing them into the MIP formulation, the model is reformulated as a piecewise form. Further, a piecewise method by updating preset control parameters is proposed for solving the reformulated model. Numerical experiments show that the proposed method produces better solution within reasonable computing time.

A Hybrid Metaheuristic Approach for Minimizing the Total Flow Time in A Flow Shop Sequence Dependent Group Scheduling Problem

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Antonio Costa

2014-07-01

Full Text Available Production processes in Cellular Manufacturing Systems (CMS often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs and Biased Random Sampling (BRS search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.

Modeling Nurse Scheduling Problem Using 0-1 Goal Programming A Case Study Of Tafo Government Hospital Kumasi-Ghana

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Wallace Agyei

2015-03-01

Full Text Available Abstract The problem of scheduling nurses at the Out-Patient Department OPD at Tafo Government Hospital Kumasi Ghana is presented. Currently the schedules are prepared by head nurse who performs this difficult and time consuming task by hand. Due to the existence of many constraints the resulting schedule usually does not guarantee the fairness of distribution of work. The problem was formulated as 0-1goal programming model with the of objective of evenly balancing the workload among nurses and satisfying their preferences as much as possible while complying with the legal and working regulations.. The developed model was then solved using LINGO14.0 software. The resulting schedules based on 0-1goal programming model balanced the workload in terms of the distribution of shift duties fairness in terms of the number of consecutive night duties and satisfied the preferences of the nurses. This is an improvement over the schedules done manually.

A Bee Colony Optimization Approach for Mixed Blocking Constraints Flow Shop Scheduling Problems

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Mostafa Khorramizadeh

2015-01-01

Full Text Available The flow shop scheduling problems with mixed blocking constraints with minimization of makespan are investigated. The Taguchi orthogonal arrays and path relinking along with some efficient local search methods are used to develop a metaheuristic algorithm based on bee colony optimization. In order to compare the performance of the proposed algorithm, two well-known test problems are considered. Computational results show that the presented algorithm has comparative performance with well-known algorithms of the literature, especially for the large sized problems.

The Green Ship Routing and Scheduling Problem (GSRSP): A conceptual approach

DEFF Research Database (Denmark)

Kontovas, Christos A.

2014-01-01

Recent reviews of the literature on ship routing and scheduling note the increased attention to environmental issues. This is an area of paramount importance for international shipping and will be even more so in the future. This short communication is motivated by the increasing attention......) based on existing formulations and highlights all the important parameters of the problem. (C) 2014 Elsevier Ltd. All rights reserved....

Multi-objective group scheduling with learning effect in the cellular manufacturing system

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Mohammad Taghi Taghavi-fard

2011-01-01

Full Text Available Group scheduling problem in cellular manufacturing systems consists of two major steps. Sequence of parts in each part-family and the sequence of part-family to enter the cell to be processed. This paper presents a new method for group scheduling problems in flow shop systems where it minimizes makespan (Cmax and total tardiness. In this paper, a position-based learning model in cellular manufacturing system is utilized where processing time for each part-family depends on the entrance sequence of that part. The problem of group scheduling is modeled by minimizing two objectives of position-based learning effect as well as the assumption of setup time depending on the sequence of parts-family. Since the proposed problem is NP-hard, two meta heuristic algorithms are presented based on genetic algorithm, namely: Non-dominated sorting genetic algorithm (NSGA-II and non-dominated rank genetic algorithm (NRGA. The algorithms are tested using randomly generated problems. The results include a set of Pareto solutions and three different evaluation criteria are used to compare the results. The results indicate that the proposed algorithms are quite efficient to solve the problem in a short computational time.

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems

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Renata Melo e Silva de Oliveira

2015-03-01

Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests.  With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs.  The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.

Generating unit maintenance scheduling under competitive market environments

International Nuclear Information System (INIS)

Jin Ho Kim; Jong Bae Park; Jong Keun Park; Yeung Han Chun

2005-01-01

A novel approach to a generating unit maintenance scheduling problem in competitive electricity markets is presented in this paper. The objective is to develop a game-theoretic framework for analyzing strategic behaviors of generating companies (Gencos) from the standpoint of the generating unit maintenance scheduling (GMS) game and for obtaining the equilibrium solution for the GMS game. The GMS problem is formulated as a dynamic non-cooperative game with complete information. The players correspond to profit maximizing individual Gencos, and the payoff of each player is defined as the profits from the energy market. The optimal schedule is defined by Nash equilibrium (equilibriums) of the game. Numerical results for two-Genco system are used to demonstrate that the proposed framework can be successfully applied to analyzing the strategic behaviors of each Genco and to obtaining the corresponding Nash equilibrium. The result indicates that generating unit maintenance schedule is one of the major strategic behaviors whereby Genco maximize their profits in a competitive market environment. (author)

Future aircraft networks and schedules

Science.gov (United States)

Shu, Yan

2011-07-01

Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

Science.gov (United States)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

Dynamic scheduling and analysis of real time systems with multiprocessors

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M.D. Nashid Anjum

2016-08-01

Full Text Available This research work considers a scenario of cloud computing job-shop scheduling problems. We consider m realtime jobs with various lengths and n machines with different computational speeds and costs. Each job has a deadline to be met, and the profit of processing a packet of a job differs from other jobs. Moreover, considered deadlines are either hard or soft and a penalty is applied if a deadline is missed where the penalty is considered as an exponential function of time. The scheduling problem has been formulated as a mixed integer non-linear programming problem whose objective is to maximize net-profit. The formulated problem is computationally hard and not solvable in deterministic polynomial time. This research work proposes an algorithm named the Tube-tap algorithm as a solution to this scheduling optimization problem. Extensive simulation shows that the proposed algorithm outperforms existing solutions in terms of maximizing net-profit and preserving deadlines.

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

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S. Molla-Alizadeh-Zavardehi

2014-01-01

Full Text Available This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA, variable neighborhood search (VNS, and simulated annealing (SA frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.

A hybrid flow shop model for an ice cream production scheduling problem

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Imma Ribas Vila

2009-07-01

Full Text Available Normal 0 21 false false false ES X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Taula normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} In this paper we address the scheduling problem that comes from an ice cream manufacturing company. This production system can be modelled as a three stage nowait hybrid flow shop with batch dependent setup costs. To contribute reducing the gap between theory and practice we have considered the real constraints and the criteria used by planners. The problem considered has been formulated as a mixed integer programming. Further, two competitive heuristic procedures have been developed and one of them will be proposed to schedule in the ice cream factory.

Estimation of reproduction number and non stationary spectral analysis of dengue epidemic.

Science.gov (United States)

Enduri, Murali Krishna; Jolad, Shivakumar

2017-06-01

In this work we analyze the post monsoon Dengue outbreaks by analyzing the transient and long term dynamics of Dengue incidences and its environmental correlates in Ahmedabad city in western India from 2005 to 2012. We calculate the reproduction number R p using the growth rate of post monsoon Dengue outbreaks and biological parameters like host and vector incubation periods and vector mortality rate, and its uncertainties are estimated through Monte-Carlo simulations by sampling parameters from their respective probability distributions. Reduction in Female Aedes mosquito density required for an effective prevention of Dengue outbreaks is also calculated. The non stationary pattern of Dengue incidences and its climatic correlates like rainfall temperature is analyzed through Wavelet based methods. We find that the mean time lag between peak of monsoon and Dengue is 9 weeks. Monsoon and Dengue cases are phase locked from 2008 to 2012 in the 16 to maintain consistency make it "16 to 32" 32 weeks band. The duration of post monsoon outbreak has been increasing every year, especially post 2008, even though the intensity and duration of monsoon has been decreasing. Temperature and Dengue incidences show correlations in the same band, but phase lock is not stationary. Copyright © 2017 Elsevier Inc. All rights reserved.

Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach

International Nuclear Information System (INIS)

Zakariazadeh, Alireza; Jadid, Shahram; Siano, Pierluigi

2014-01-01

Highlights: • Environmental/economical scheduling of energy and reserve. • Simultaneous participation of loads in both energy and reserve scheduling. • Aggregate wind generation and demand uncertainties in a stochastic model. • Stochastic scheduling of energy and reserve in a distribution system. • Demand response providers’ participation in energy and reserve scheduling. - Abstract: In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented ε-constraint method, is used to minimize the total operational costs and emissions and to generate Pareto-optimal solutions for the energy and reserve scheduling problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise non-dominated solution. The wind power and demand forecast errors are considered in this approach and the reserve can be furnished by the main grid as well as distributed generators and responsive loads. The consumers participate in both energy and reserve markets using various demand response programs. In order to facilitate small and medium loads participation in demand response programs, a Demand Response Provider (DRP) aggregates offers for load reduction. In order to solve the proposed optimization model, the Benders decomposition technique is used to convert the large scale mixed integer non-linear problem into mixed-integer linear programming and non-linear programming problems. The effectiveness of the proposed scheduling approach is verified on a 41-bus distribution test system over a 24-h period

An approximate stationary solution for multi-allele neutral diffusion with low mutation rates.

Science.gov (United States)

Burden, Conrad J; Tang, Yurong

2016-12-01

We address the problem of determining the stationary distribution of the multi-allelic, neutral-evolution Wright-Fisher model in the diffusion limit. A full solution to this problem for an arbitrary K×K mutation rate matrix involves solving for the stationary solution of a forward Kolmogorov equation over a (K-1)-dimensional simplex, and remains intractable. In most practical situations mutations rates are slow on the scale of the diffusion limit and the solution is heavily concentrated on the corners and edges of the simplex. In this paper we present a practical approximate solution for slow mutation rates in the form of a set of line densities along the edges of the simplex. The method of solution relies on parameterising the general non-reversible rate matrix as the sum of a reversible part and a set of (K-1)(K-2)/2 independent terms corresponding to fluxes of probability along closed paths around faces of the simplex. The solution is potentially a first step in estimating non-reversible evolutionary rate matrices from observed allele frequency spectra. Copyright © 2016 Elsevier Inc. All rights reserved.

Calculations of stationary solutions for the non linear viscous resistive MHD equations in slab geometry

International Nuclear Information System (INIS)

Edery, D.

1983-11-01

The reduced system of the non linear resistive MHD equations is used in the 2-D one helicity approximation in the numerical computations of stationary tearing modes. The critical magnetic Raynolds number S (S=tausub(r)/tausub(H) where tausub(R) and tausub(H) are respectively the characteristic resistive and hydro magnetic times) and the corresponding linear solution are computed as a starting approximation for the full non linear equations. These equations are then treated numerically by an iterative procedure which is shown to be rapidly convergent. A numerical application is given in the last part of this paper

A novel modeling approach for job shop scheduling problem under uncertainty

Directory of Open Access Journals (Sweden)

Behnam Beheshti Pur

2013-11-01

Full Text Available When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.

Constraint-based scheduling

Science.gov (United States)

Zweben, Monte

1993-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

A Review On Job Shop Scheduling Using Non-Conventional Optimization Algorithm

OpenAIRE

K.Mallikarjuna; Venkatesh.G

2014-01-01

A great deal of research has been focused on solving job shop scheduling problem (∫J), over the last four decades, resulting in a wide variety of approaches. Recently much effort has been concentrated on hybrid methods to solve ∫J, as a single technique cannot solve this stubborn problem. As a result much effort has recently been concentrated on techniques that lead to combinatorial optimization methods and a meta-strategy which guides the search out of local optima. In this p...

Scheduling by positional completion times: analysis of a two-stage flow shop problem with a batching machine

NARCIS (Netherlands)

Hoogeveen, J.A.; Velde, van de S.L.

1998-01-01

We consider a scheduling problem introduced by Ahmadi et al., Batching and scheduling jobs on batch and discrete processors, Operation Research 40 (1992) 750–763, in which each job has to be prepared before it can be processed. The preparation is performed by a batching machine; it can prepare at

Forecasting non-stationary diarrhea, acute respiratory infection, and malaria time-series in Niono, Mali.

Science.gov (United States)

Medina, Daniel C; Findley, Sally E; Guindo, Boubacar; Doumbia, Seydou

2007-11-21

Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods. In this longitudinal retrospective (01/1996-06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%. The multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions

Image quality in the anteroposterior cervical spine radiograph: Comparison between moving, stationary and non-grid techniques in a lamb neck

Energy Technology Data Exchange (ETDEWEB)

Keating, Michelle [School of Health and Social Care, Faculty of Health and Life Sciences, University of the West of England, Stapleton, Bristol BS16 1DD (United Kingdom); Grange, Stuart, E-mail: Stuart2.Grange@uwe.ac.u [School of Health and Social Care, Faculty of Health and Life Sciences, University of the West of England, Stapleton, Bristol BS16 1DD (United Kingdom)

2011-05-15

Background: Cervical spine radiography is a commonly employed examination for degenerative disease and trauma in the cervical spine. Traditionally, the anteroposterior projection is undertaken with the use of an anti-scatter grid. Some practitioners appear to have rejected this practice in favour of a non-grid technique, possibly because of the dose saving it affords. It is necessary to determine if image quality in the cervical spine is significantly degraded and whether the omission of the grid is justified. Method: Using a slaughtered lamb neck as a model of the human neck triplicate radiographs were obtained using a non-grid, a stationary grid and a moving grid technique. Entrance surface dose and dose area product was measured for these techniques. Image quality in terms of contrast, sharpness and overall acceptability was evaluated by 9 independent and blinded observers. Results: A significant reduction in measured dose was observed when the non-grid technique was compared to stationary or moving grid techniques. A statistically significant reduction in image contrast, sharpness and acceptability was also seen in the non-grid compared to grid techniques. Conclusion: These results show evidence of significantly greater image quality in the presence of either a moving or stationary grid in the lamb model. As such they support the continued use of scatter rejection methods such as the anti-scatter grid in AP radiography of the human cervical spine, to optimise radiographic image quality in this critical structure.

Image quality in the anteroposterior cervical spine radiograph: Comparison between moving, stationary and non-grid techniques in a lamb neck

International Nuclear Information System (INIS)

Keating, Michelle; Grange, Stuart

2011-01-01

Background: Cervical spine radiography is a commonly employed examination for degenerative disease and trauma in the cervical spine. Traditionally, the anteroposterior projection is undertaken with the use of an anti-scatter grid. Some practitioners appear to have rejected this practice in favour of a non-grid technique, possibly because of the dose saving it affords. It is necessary to determine if image quality in the cervical spine is significantly degraded and whether the omission of the grid is justified. Method: Using a slaughtered lamb neck as a model of the human neck triplicate radiographs were obtained using a non-grid, a stationary grid and a moving grid technique. Entrance surface dose and dose area product was measured for these techniques. Image quality in terms of contrast, sharpness and overall acceptability was evaluated by 9 independent and blinded observers. Results: A significant reduction in measured dose was observed when the non-grid technique was compared to stationary or moving grid techniques. A statistically significant reduction in image contrast, sharpness and acceptability was also seen in the non-grid compared to grid techniques. Conclusion: These results show evidence of significantly greater image quality in the presence of either a moving or stationary grid in the lamb model. As such they support the continued use of scatter rejection methods such as the anti-scatter grid in AP radiography of the human cervical spine, to optimise radiographic image quality in this critical structure.

A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem

Science.gov (United States)

Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao

A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.

Momentum-energy of the non-radiating electromagnetic field: open problems?

International Nuclear Information System (INIS)

Kholmetskii, Alexander L

2006-01-01

This paper inspects more closely the problem of the momentum and energy of a bound (non-radiative) electromagnetic (EM) field. It has been shown that for an isolating system of non-radiative non-relativistic mechanically free charged particles, a transformation of mechanical to EM momentum and vice versa occurs in accordance with the requirement P-vector G =const, where P-vector G = P-vector M + Σ i N q i A-vector i is the canonical momentum (N>1 is the number of particles, q is the charge, A-vector is the vector potential, P-vector M is the mechanical momentum of the system). Then dP-vector M /dt = -(d/dt)Σq i A-vector i represents the self-force, acting on this isolating system due to violation of Newton's third law in EM interaction. This equation is not applicable to an isolated charged particle, and the problems of its self-action and its own EM momentum have been examined. Analysing the systems of non-radiative particles, where the retardation is not negligible ('dynamical' systems in our definition) it has been found that the total momentum is the same at the initial and final stationary states of such systems, but it varies with time during the dynamical processes. It means a violation of continuous conservation of the total momentum, if the bound EM field spreads at the light velocity c. Finally, the compatibility of the energy conservation law and the Lentz rule for retarded non-radiative EM field has been examined. It has been shown that for dynamical systems the energy conservation law comes into a certain contradiction with the finite (light) spread velocity for the bound EM field

Nuclear Power Plant Preventive Maintenance Scheduling Problem with Fuzziness

International Nuclear Information System (INIS)

Abass, S.A.; Abdallah, A.S.

2013-01-01

Maintenance activity is regarded as the most important key factor for the safety, reliability and economy of a nuclear power plant. Preventive maintenance refers to set of planned activities which include nondestructive testing and periodic inspection as well as maintenance. In this paper, we address the problem of nuclear power plant preventive maintenance scheduling with uncertainty. The uncertainty will be represented by fuzzy parameters. The problem is how to determine the period for which generating units of an electric system should be taken off line for planned preventive maintenance over specific time horizon. Preventive maintenance activity of a nuclear power plant is an important issue as it designed to extend the plant life . It is more required to review the maintenance not only from the view point of safety and reliability but also economy. Preventive maintenance program exists to ensure that nuclear safety significant equipment will function when it is supposed to. Also this problem is extremely important because a failure in a power plant may cause a general breakdown in an electric network. In this paper a mixed integer programming model is used to express this problem. In proposed model power demand is taken as fuzzy parameters. A case study is provided to demonstrate the efficiency of the proposed model.

Stationary states of two-level open quantum systems

International Nuclear Information System (INIS)

Gardas, Bartlomiej; Puchala, Zbigniew

2011-01-01

A problem of finding stationary states of open quantum systems is addressed. We focus our attention on a generic type of open system: a qubit coupled to its environment. We apply the theory of block operator matrices and find stationary states of two-level open quantum systems under certain conditions applied on both the qubit and the surrounding.

Poisson-Nernst-Planck equations with steric effects - non-convexity and multiple stationary solutions

Science.gov (United States)

Gavish, Nir

2018-04-01

We study the existence and stability of stationary solutions of Poisson-Nernst-Planck equations with steric effects (PNP-steric equations) with two counter-charged species. We show that within a range of parameters, steric effects give rise to multiple solutions of the corresponding stationary equation that are smooth. The PNP-steric equation, however, is found to be ill-posed at the parameter regime where multiple solutions arise. Following these findings, we introduce a novel PNP-Cahn-Hilliard model, show that it is well-posed and that it admits multiple stationary solutions that are smooth and stable. The various branches of stationary solutions and their stability are mapped utilizing bifurcation analysis and numerical continuation methods.

Evaluation of a weather generator-based method for statistically downscaling non-stationary climate scenarios for impact assessment at a point scale

Science.gov (United States)

The non-stationarity is a major concern for statistically downscaling climate change scenarios for impact assessment. This study is to evaluate whether a statistical downscaling method is fully applicable to generate daily precipitation under non-stationary conditions in a wide range of climatic zo...

Greedy and metaheuristics for the offline scheduling problem in grid computing

DEFF Research Database (Denmark)

Gamst, Mette

In grid computing a number of geographically distributed resources connected through a wide area network, are utilized as one computations unit. The NP-hard offline scheduling problem in grid computing consists of assigning jobs to resources in advance. In this paper, five greedy heuristics and two....... All heuristics solve instances with up to 2000 jobs and 1000 resources, thus the results are useful both with respect to running times and to solution values....

Stationary solution of the compressible magnetohydrodynamic equation and its stability with respect to initial disturbance

Directory of Open Access Journals (Sweden)

WU Renchao

2016-06-01

Full Text Available In this paper, we consider three dimensional compressible viscous magnetohydro dynamic equations(MHD with external potentialforce. We first derive the corresponding non-constantstationary solutions. Then we show global well-posedness of the initial value problem for the three dimensional compressible viscous magnetohydrodynamic equations, provided that rescribed initial data is close to the stationary solution.

Mathematical modeling of non-stationary gas flow in gas pipeline

Science.gov (United States)

Fetisov, V. G.; Nikolaev, A. K.; Lykov, Y. V.; Duchnevich, L. N.

2018-03-01

An analysis of the operation of the gas transportation system shows that for a considerable part of time pipelines operate in an unsettled regime of gas movement. Its pressure and flow rate vary along the length of pipeline and over time as a result of uneven consumption and selection, switching on and off compressor units, shutting off stop valves, emergence of emergency leaks. The operational management of such regimes is associated with difficulty of reconciling the operating modes of individual sections of gas pipeline with each other, as well as with compressor stations. Determining the grounds that cause change in the operating mode of the pipeline system and revealing patterns of these changes determine the choice of its parameters. Therefore, knowledge of the laws of changing the main technological parameters of gas pumping through pipelines in conditions of non-stationary motion is of great importance for practice.

METHOD OF CALCULATION OF THE NON-STATIONARY TEMPERATURE FIELD INSIDE OF THERMAL PACKED BED ENERGY STORAGE

Directory of Open Access Journals (Sweden)

Ermuratschii V.V.

2014-04-01

Full Text Available e paper presents a method of the approximate calculation of the non-stationary temperature field inside of thermal packed bed energy storages with feasible and latent heat. Applying thermoelectric models and computational methods in electrical engineering, the task of computing non-stationary heat transfer is resolved with respect to third type boundary conditions without applying differential equations of the heat transfer. For sub-volumes of the energy storage the method is executed iteratively in spatiotemporal domain. Single-body heating is modeled for each sub-volume, and modeling conditions are assumed to be identical for remained bod-ies, located in the same sub-volume. For each iteration step the boundary conditions will be represented by re-sults at the previous step. The fulfillment of the first law of thermodynamics for system “energy storage - body” is obtained by the iterative search of the mean temperature of the energy storage. Under variable boundary con-ditions the proposed method maybe applied to calculating temperature field inside of energy storages with packed beds consisted of solid material, liquid and phase-change material. The method may also be employed to compute transient, power and performance characteristics of packed bed energy storages.

Development of the Contiguous-cells Transportation Problem

Directory of Open Access Journals (Sweden)

O. E. Charles-Owaba

2015-08-01

Full Text Available The issue of scheduling a long string of multi-period activities which have to be completed without interruption has always been an industrial challenge. The existing production/maintenance scheduling algorithms can only handle situations where activities can be split into two or more sets of activities carried out in non-contiguous sets of work periods. This study proposes a contiguous-periods production/maintenance scheduling approach using the Transportation Model. Relevant variables and parameters of contiguous-cells scheduling problem were taken from the literature. A scheduling optimization problem was defined and solved using a contiguous-cells transportation algorithm (CCTA which was applied in order to determine the optimal maintenance schedule of a fleet of ships at a dockyard in South-Western Nigeria. Fifteen different problems were solved. It is concluded that the contiguous-cells transportation approach to production/ maintenance scheduling is feasible. The model will be a useful decision support tool for scheduling maintenance operations.

A matheuristic approach for solving the Integrated Timetabling and Vehicle Scheduling Problem

DEFF Research Database (Denmark)

Fonseca, Joao Filipe Paiva; Larsen, Allan; van der Hurk, Evelien

between different trips. We consider transfers between bus trips scheduled by the model, but also transfers to other fixed lines that intersect the lines considered in the IT-VSP. We present a MIP formulation of the IT-VSP able to solve small instances of the problem, and a matheuristic approach that uses...... the compact MIP to solve larger instances of the problem. The idea is to iteratively solve restricted versions of the MIP selecting at each step a subset of trips where modifications are allowed, while all other trips remain fixed. The performance of the proposed matheuristic is shown on a case study...

Solving scheduling problems by untimed model checking. The clinical chemical analyser case study

NARCIS (Netherlands)

Margaria, T.; Wijs, Anton J.; Massink, M.; van de Pol, Jan Cornelis; Bortnik, Elena M.

2009-01-01

In this article, we show how scheduling problems can be modelled in untimed process algebra, by using special tick actions. A minimal-cost trace leading to a particular action, is one that minimises the number of tick steps. As a result, we can use any (timed or untimed) model checking tool to find

A fast method for the unit scheduling problem with significant renewable power generation

International Nuclear Information System (INIS)

Osório, G.J.; Lujano-Rojas, J.M.; Matias, J.C.O.; Catalão, J.P.S.

2015-01-01

Highlights: • A model to the scheduling of power systems with significant renewable power generation is provided. • A new methodology that takes information from the analysis of each scenario separately is proposed. • Based on a probabilistic analysis, unit scheduling and corresponding economic dispatch are estimated. • A comparison with others methodologies is in favour of the proposed approach. - Abstract: Optimal operation of power systems with high integration of renewable power sources has become difficult as a consequence of the random nature of some sources like wind energy and photovoltaic energy. Nowadays, this problem is solved using Monte Carlo Simulation (MCS) approach, which allows considering important statistical characteristics of wind and solar power production such as the correlation between consecutive observations, the diurnal profile of the forecasted power production, and the forecasting error. However, MCS method requires the analysis of a representative amount of trials, which is an intensive calculation task that increases considerably with the number of scenarios considered. In this paper, a model to the scheduling of power systems with significant renewable power generation based on scenario generation/reduction method, which establishes a proportional relationship between the number of scenarios and the computational time required to analyse them, is proposed. The methodology takes information from the analysis of each scenario separately to determine the probabilistic behaviour of each generator at each hour in the scheduling problem. Then, considering a determined significance level, the units to be committed are selected and the load dispatch is determined. The proposed technique was illustrated through a case study and the comparison with stochastic programming approach was carried out, concluding that the proposed methodology can provide an acceptable solution in a reduced computational time

Automated scheduling and planning from theory to practice

CERN Document Server

Ozcan, Ender; Urquhart, Neil

2013-01-01

  Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling.  Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives...

Morphology of silver deposits produced by non-stationary steady regimes

International Nuclear Information System (INIS)

Popovski, Orce

2002-01-01

Morphology of silver electro deposits produced by periodical reversing of d.c. pulses was studied. Employing usual electrorefining conditions it is not possible to deposit compact silver layers from Ag non-complexing salts. This is due, mainly, to the high value of silver exchange current density and to the silver crystallographic peculiarity. In order to counteract this phenomenon, instead of usual, (stationer) potential-current regimes, non-stationary one was applied in this study. The effect of phosphate ions in the electrolyte was further clarified. A set of experimental conditions was applied so that silver was electrodeposited under mixed electrochemical and diffusion control. The primar cathodic pulse causes silver to nucleate with high density and nuclei to start to grow. The subsequent anodic pulse (current reversal) lowers the gradient of silver ion concentration and dissolves the most active growth centers as well. The combination of cathodic and anodic pulses diminishes the dendritic growth and helps smoothing of deposit surface to occur. Fine-grained and more compact deposits are produced, as compared to the ones grown in purely potentiostatic conditions. It was found that the addition of phosphate ions as well as the application of intensive electrolyte stirring change the Ag- grain morphology in favor of poli crystal whisker structure. (Author)

Robust and Flexible Scheduling with Evolutionary Computation

DEFF Research Database (Denmark)

Jensen, Mikkel T.

Over the last ten years, there have been numerous applications of evolutionary algorithms to a variety of scheduling problems. Like most other research on heuristic scheduling, the primary aim of the research has been on deterministic formulations of the problems. This is in contrast to real world...... scheduling problems which are usually not deterministic. Usually at the time the schedule is made some information about the problem and processing environment is available, but this information is uncertain and likely to change during schedule execution. Changes frequently encountered in scheduling...... environments include machine breakdowns, uncertain processing times, workers getting sick, materials being delayed and the appearance of new jobs. These possible environmental changes mean that a schedule which was optimal for the information available at the time of scheduling can end up being highly...

An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times

Directory of Open Access Journals (Sweden)

Rui Zhang

2011-09-01

Full Text Available Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the stochastic job shop scheduling problem (SJSSP has not received sufficient attention. In this paper, we propose an artificial bee colony (ABC algorithm for SJSSP with the objective of minimizing the maximum lateness (which is an index of service quality. First, we propose a performance estimate for preliminary screening of the candidate solutions. Then, the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation (through Monte Carlo simulation process. Finally, the computational results on different-scale test problems validate the effectiveness and efficiency of the proposed approach.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...

Kinetic features and non-stationary electron trapping in paraxial magnetic nozzles

Science.gov (United States)

Sánchez-Arriaga, G.; Zhou, J.; Ahedo, E.; Martínez-Sánchez, M.; Ramos, J. J.

2018-03-01

The paraxial expansion of a collisionless plasma jet into vacuum, guided by a magnetic nozzle, is studied with an Eulerian and non-stationary Vlasov-Poisson solver. Parametric analyzes varying the magnetic field expansion rate, the size of the simulation box, and the electrostatic potential fall are presented. After choosing the potential fall leading to a zero net current beam, the steady states of the simulations exhibit a quasi-neutral region followed by a downstream sheath. The latter, an unavoidable consequence of the finite size of the computational domain, does not affect the quasi-neutral region if the box size is chosen appropriately. The steady state presents a strong decay of the perpendicular temperature of the electrons, whose profile versus the inverse of the magnetic field does not depend on the expansion rate within the quasi-neutral region. As a consequence, the electron distribution function is highly anisotropic downstream. The simulations revealed that the ions reach a higher velocity during the transient than in the steady state and their distribution functions are not far from mono-energetic. The density percentage of the population of electrons trapped during the transient, which is computed self-consistently by the code, is up to 25% of the total electron density in the quasi-neutral region. It is demonstrated that the exact amount depends on the history of the system and the steady state is not unique. Nevertheless, the amount of trapped electrons is smaller than the one assumed heuristically by kinetic stationary theories.

A basic period approach to the economic lot scheduling problem with shelf life considerations

NARCIS (Netherlands)

Soman, C.A.; van Donk, D.P.; Gaalman, G.J.C.

2004-01-01

Almost all the research on the economic lot scheduling problem (ELSP) considering limited shelf life of products has assumed a common cycle approach and an unrealistic assumption of possibility of deliberately reducing the production rate. In many cases, like in food processing industry where

One-machine job-scheduling with non-constant capacity - Minimizing weighted completion times

NARCIS (Netherlands)

Amaddeo, H.F.; Amaddeo, H.F.; Nawijn, W.M.; van Harten, Aart

1997-01-01

In this paper an n-job one-machine scheduling problem is considered, in which the machine capacity is time-dependent and jobs are characterized by their work content. The objective is to minimize the sum of weighted completion times. A necessary optimality condition is presented and we discuss some

Fluctuation relations in non-equilibrium stationary states of Ising models

Energy Technology Data Exchange (ETDEWEB)

Piscitelli, A; Gonnella, G [Dipartimento di Fisica, Universita di Bari and Istituto Nazionale di Fisica Nucleare, Sezione di Bari, via Amendola 173, 70126 Bari (Italy); Corberi, F [Dipartimento di Matematica ed Informatica, via Ponte don Melillo, Universita di Salerno, 84084 Fisciano (Italy); Pelizzola, A [Dipartimento di Fisica and Istituto Nazionale di Fisica Nucleare, Sezione di Torino, and CNISM, Politecnico di Torino, c. Duca degli Abruzzi 24, 10129 Torino (Italy)

2009-01-15

Fluctuation relations for the entropy production in non-equilibrium stationary states of Ising models are investigated by means of Monte Carlo simulations. Systems in contact with heat baths at two different temperatures or subject to external driving will be studied. In the first case, considering different kinetic rules and couplings with the baths, the behaviors of the probability distributions of the heat exchanged in time {tau} with the thermostats, both in the disordered phase and in the low temperature phase, are discussed. The fluctuation relation is always followed in the large {tau} limit and deviations from linear response theory are observed. Finite {tau} corrections are shown to obey a scaling behavior. In the other case the system is in contact with a single heat bath, but work is done by shearing it. Also for this system, using the statistics collected for the mechanical work we show the validity of the fluctuation relation and the preasymptotic corrections behave analogously to those for the case with two baths.

Scheduling theory, algorithms, and systems

CERN Document Server

Pinedo, Michael L

2016-01-01

This new edition of the well-established text Scheduling: Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as important scheduling problems that appear in the real world. The accompanying website includes supplementary material in the form of slide-shows from industry as well as movies that show actual implementations of scheduling systems. The main structure of the book, as per previous editions, consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped, streamlined, and extended. The reference...

The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies

DEFF Research Database (Denmark)

Rasmussen, Matias Sevel; Justesen, Tor Fog; Dohn, Anders Høeg

2012-01-01

In the Home Care Crew Scheduling Problem a staff of home carers has to be assigned a number of visits to patients’ homes, such that the overall service level is maximised. The problem is a generalisation of the vehicle routing problem with time windows. Required travel time between visits and time...... preference constraints. The algorithm is tested both on real-life problem instances and on generated test instances inspired by realistic settings. The use of the specialised branching scheme on real-life problems is novel. The visit clustering decreases run times significantly, and only gives a loss...... windows of the visits must be respected. The challenge when assigning visits to home carers lies in the existence of soft preference constraints and in temporal dependencies between the start times of visits.We model the problem as a set partitioning problem with side constraints and develop an exact...

An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem

Science.gov (United States)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2017-11-01

This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

OpenAIRE

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through c...

Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem

Directory of Open Access Journals (Sweden)

Julien Maheut

2013-07-01

Full Text Available Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system

Concurrent processes scheduling with scarce resources in small and medium enterprises

Institute of Scientific and Technical Information of China (English)

马嵩华

2016-01-01

Scarce resources , precedence and non-determined time-lag are three constraints commonly found in small and medium manufacturing enterprises (SMEs), which are deemed to block the ap-plication of workflow management system ( WfMS ) .To tackle this problem , a workflow scheduling approach is proposed based on timing workflow net (TWF-net) and genetic algorithm (GA).The workflow is modelled in a form of TWF-net in favour of process simulation and resource conflict checking .After simplifying and reconstructing the set of workflow instance , the conflict resolution problem is transformed into a resource-constrained project scheduling problem ( RCPSP ) , which could be efficiently solved by a heuristic method , such as GA.Finally, problems of various sizes are utilized to test the performance of the proposed algorithm and to compare it with first-come-first-served ( FCFS) strategy.The evaluation demonstrates that the proposed method is an overwhelming and effective approach for scheduling the concurrent processes with precedence and resource con -straints .

A Pareto archive floating search procedure for solving multi-objective flexible job shop scheduling problem

Directory of Open Access Journals (Sweden)

J. S. Sadaghiani

2014-04-01

Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.

Treating Non-Retentive Encopresis with Rewarded Scheduled Toilet Visits

Science.gov (United States)

Boles, Richard E; Roberts, Michael C; Vernberg, Eric M

2008-01-01

We evaluated the effects of rewarded scheduled toilet sits on non-retentive encopretic behavior of an elementary-school student receiving services for serious emotional disturbance. A multidisciplinary team implemented the 8-week intervention using a multiple baseline across settings design. The results showed an increase in sitting on the toilet and a decline in encopretic episodes in both school and home settings. These findings support the use of a behavioral intervention for children with significant behavioral disorders within a classroom setting. PMID:22477690

A Three-Stage Optimization Algorithm for the Stochastic Parallel Machine Scheduling Problem with Adjustable Production Rates

Directory of Open Access Journals (Sweden)

Rui Zhang

2013-01-01

Full Text Available We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. The objective functions to be minimized consist of two parts; the first part is related with the due date performance (i.e., the tardiness of the jobs, while the second part is related with the setting of machine speeds. Therefore, the decision variables include both the production schedule (sequences of jobs and the production rate of each machine. The optimization process, however, is significantly complicated by the stochastic factors in the manufacturing system. To address the difficulty, a simulation-based three-stage optimization framework is presented in this paper for high-quality robust solutions to the integrated scheduling problem. The first stage (crude optimization is featured by the ordinal optimization theory, the second stage (finer optimization is implemented with a metaheuristic called differential evolution, and the third stage (fine-tuning is characterized by a perturbation-based local search. Finally, computational experiments are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also discussed.

Cosmological red shift in the Seeliger-Einstein stationary Universe

International Nuclear Information System (INIS)

Kropotkin, P.N.

1988-01-01

A problem of Seeliger-Einstein stationary Universe is considered. Simple empirical relations between cosmological and physical constants to which attention was paid by Stanukovich K., Dikke R., Dirac P. testify to the supposition on stationary Universe. The Universe expansion being absent, a hypothesis of ''photon aging'' suggested in 1929 by Belopolskij A. and Zwicky F. must be accepted for explanation of Hubble effect. It is stated that abandon the Seeliger-Einstein stationary cosmological model would be premature. Study and comparison of different mechanisms suggested for validation of photon aging hypothesis is necessary

The stationary non-equilibrium plasma of cosmic-ray electrons and positrons

Science.gov (United States)

Tomaschitz, Roman

2016-06-01

The statistical properties of the two-component plasma of cosmic-ray electrons and positrons measured by the AMS-02 experiment on the International Space Station and the HESS array of imaging atmospheric Cherenkov telescopes are analyzed. Stationary non-equilibrium distributions defining the relativistic electron-positron plasma are derived semi-empirically by performing spectral fits to the flux data and reconstructing the spectral number densities of the electronic and positronic components in phase space. These distributions are relativistic power-law densities with exponential cutoff, admitting an extensive entropy variable and converging to the Maxwell-Boltzmann or Fermi-Dirac distributions in the non-relativistic limit. Cosmic-ray electrons and positrons constitute a classical (low-density high-temperature) plasma due to the low fugacity in the quantized partition function. The positron fraction is assembled from the flux densities inferred from least-squares fits to the electron and positron spectra and is subjected to test by comparing with the AMS-02 flux ratio measured in the GeV interval. The calculated positron fraction extends to TeV energies, predicting a broad spectral peak at about 1 TeV followed by exponential decay.

Flow shop scheduling with heterogeneous workers

OpenAIRE

Benavides, Alexander J.; Ritt, Marcus; Miralles Insa, Cristóbal Javier

2014-01-01

We propose an extension to the flow shop scheduling problem named Heterogeneous Flow Shop Scheduling Problem (Het-FSSP), where two simultaneous issues have to be resolved: finding the best worker assignment to the workstations, and solving the corresponding scheduling problem. This problem is motivated by Sheltered Work centers for Disabled, whose main objective is the labor integration of persons with disabilities, an important aim not only for these centers but for any company d...

Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states

CERN Document Server

Dewar, R

2003-01-01

Jaynes' information theory formalism of statistical mechanics is applied to the stationary states of open, non-equilibrium systems. First, it is shown that the probability distribution p subGAMMA of the underlying microscopic phase space trajectories GAMMA over a time interval of length tau satisfies p subGAMMA propor to exp(tau sigma subGAMMA/2k sub B) where sigma subGAMMA is the time-averaged rate of entropy production of GAMMA. Three consequences of this result are then derived: (1) the fluctuation theorem, which describes the exponentially declining probability of deviations from the second law of thermodynamics as tau -> infinity; (2) the selection principle of maximum entropy production for non-equilibrium stationary states, empirical support for which has been found in studies of phenomena as diverse as the Earth's climate and crystal growth morphology; and (3) the emergence of self-organized criticality for flux-driven systems in the slowly-driven limit. The explanation of these results on general inf...

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

Science.gov (United States)

Rash, James

2014-01-01

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial

Scheduling and control strategies for the departure problem in air traffic control

Science.gov (United States)

Bolender, Michael Alan

Two problems relating to the departure problem in air traffic control automation are examined. The first problem that is addressed is the scheduling of aircraft for departure. The departure operations at a major US hub airport are analyzed, and a discrete event simulation of the departure operations is constructed. Specifically, the case where there is a single departure runway is considered. The runway is fed by two queues of aircraft. Each queue, in turn, is fed by a single taxiway. Two salient areas regarding scheduling are addressed. The first is the construction of optimal departure sequences for the aircraft that are queued. Several greedy search algorithms are designed to minimize the total time to depart a set of queued aircraft. Each algorithm has a different set of heuristic rules to resolve situations within the search space whenever two branches of the search tree with equal edge costs are encountered. These algorithms are then compared and contrasted with a genetic search algorithm in order to assess the performance of the heuristics. This is done in the context of a static departure problem where the length of the departure queue is fixed. A greedy algorithm which deepens the search whenever two branches of the search tree with non-unique costs are encountered is shown to outperform the other heuristic algorithms. This search strategy is then implemented in the discrete event simulation. A baseline performance level is established, and a sensitivity analysis is performed by implementing changes in traffic mix, routing, and miles-in-trail restrictions for comparison. It is concluded that to minimize the average time spent in the queue for different traffic conditions, a queue assignment algorithm is needed to maintain an even balance of aircraft in the queues. A necessary consideration is to base queue assignment upon traffic management restrictions such as miles-in-trail constraints. The second problem addresses the technical challenges associated

Analyzing scheduling in the food-processing industry

DEFF Research Database (Denmark)

Akkerman, Renzo; van Donk, Dirk Pieter

2009-01-01

Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry......-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production...... process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures...

The application of unattended ground sensors to stationary targets

International Nuclear Information System (INIS)

Sleefe, G.E.; Peglow, S.; Hamrick, R.

1997-01-01

The unattended sensing of stationary (i.e. non-mobile) targets is important in applications ranging from counter-proliferation to law enforcement. With stationary targets, sources of seismic, acoustic, and electro-magnetic emissions can potentially be used to detect, identify, and locate the target. Stationary targets have considerably different sensing requirements than the traditional mobile-target unattended ground sensor applications. This paper presents the novel features and requirements of a system for sensing stationary targets. In particular, issues associated with long-listen time signal processing for signal detection, and array processing techniques for signal localization are presented. Example data and signal processing outputs from a stationary target will be used to illustrate these issues. The impact on sensor, electronic signal processing, battery subsystem, and communication requirements will also be discussed. The paper will conclude with a detailed comparison between mobile-target and stationary-target unattended ground sensor architectures

SOFIA's Choice: Automating the Scheduling of Airborne Observations

Science.gov (United States)

Frank, Jeremy; Norvig, Peter (Technical Monitor)

1999-01-01

This paper describes the problem of scheduling observations for an airborne telescope. Given a set of prioritized observations to choose from, and a wide range of complex constraints governing legitimate choices and orderings, how can we efficiently and effectively create a valid flight plan which supports high priority observations? This problem is quite different from scheduling problems which are routinely solved automatically in industry. For instance, the problem requires making choices which lead to other choices later, and contains many interacting complex constraints over both discrete and continuous variables. Furthermore, new types of constraints may be added as the fundamental problem changes. As a result of these features, this problem cannot be solved by traditional scheduling techniques. The problem resembles other problems in NASA and industry, from observation scheduling for rovers and other science instruments to vehicle routing. The remainder of the paper is organized as follows. In 2 we describe the observatory in order to provide some background. In 3 we describe the problem of scheduling a single flight. In 4 we compare flight planning and other scheduling problems and argue that traditional techniques are not sufficient to solve this problem. We also mention similar complex scheduling problems which may benefit from efforts to solve this problem. In 5 we describe an approach for solving this problem based on research into a similar problem, that of scheduling observations for a space-borne probe. In 6 we discuss extensions of the flight planning problem as well as other problems which are similar to flight planning. In 7 we conclude and discuss future work.

Stationary stochastic processes theory and applications

CERN Document Server

Lindgren, Georg

2012-01-01

Some Probability and Process BackgroundSample space, sample function, and observablesRandom variables and stochastic processesStationary processes and fieldsGaussian processesFour historical landmarksSample Function PropertiesQuadratic mean propertiesSample function continuityDerivatives, tangents, and other characteristicsStochastic integrationAn ergodic resultExercisesSpectral RepresentationsComplex-valued stochastic processesBochner's theorem and the spectral distributionSpectral representation of a stationary processGaussian processesStationary counting processesExercisesLinear Filters - General PropertiesLinear time invariant filtersLinear filters and differential equationsWhite noise in linear systemsLong range dependence, non-integrable spectra, and unstable systemsThe ARMA-familyLinear Filters - Special TopicsThe Hilbert transform and the envelopeThe sampling theoremKarhunen-Loève expansionClassical Ergodic Theory and MixingThe basic ergodic theorem in L2Stationarity and transformationsThe ergodic th...

A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem

DEFF Research Database (Denmark)

Rahmati, Seyed Habib A.; Ahmadi, Abbas; Govindan, Kannan

2018-01-01

the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied......Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing...... production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing...

Hawking radiation temperatures in non-stationary Kerr black holes with different tortoise coordinate transformations

Energy Technology Data Exchange (ETDEWEB)

Lan, X.G. [Southwest Jiaotong University, Quantum Optoelectronics Laboratory, Chengdu (China); China West Normal University, Institute of Theoretical Physics, Nanchong (China); Jiang, Q.Q. [China West Normal University, Institute of Theoretical Physics, Nanchong (China); Wei, L.F. [Southwest Jiaotong University, Quantum Optoelectronics Laboratory, Chengdu (China); Sun Yat-Sen University, State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics and Engineering, Guangzhou (China)

2012-04-15

We apply the Damour-Ruffini-Sannan method to study the Hawking radiations of scalar and Dirac particles in non-stationary Kerr black holes under different tortoise coordinate transformations. We found that all the relevant Hawking radiation spectra show still the blackbody ones, while the Hawking temperatures are strongly related to the used tortoise coordinate transformations. The properties of these dependences are discussed analytically and numerically. Our results imply that proper selections of tortoise coordinate transformations should be important in the studies of Hawking radiations and the correct selection would be given by the experimental observations in the future. (orig.)

Planning and Scheduling of Airline Operations

Directory of Open Access Journals (Sweden)

İlkay ORHAN

2010-02-01

Full Text Available The Turkish Civil Aviation sector has grown at a rate of 53 % between the years 2002-2008 owing to countrywide economical developments and some removed restrictions in the aviation field. Successful international companies in the sector use advanced computer-supported solution methods for their planning and scheduling problems. These methods have been providing significant competitive advantages to those companies. There are four major scheduling and planning problems in the airline sector: flight scheduling, aircraft scheduling, crew scheduling and disruptions management. These aforementioned scheduling and planning problems faced by all airline companies in the airline sector were examined in detail. Studies reveal that companies using the advanced methods might gain significant cost reductions. However, even then, the time required for solving large scale problems may not satisfy the decision quality desired by decision makers. In such cases, using modern decision methods integrated with advanced technologies offer companies an opportunity for significant cost-advantages.

Application of Operational Research Techniques in Operating Room Scheduling Problems: Literature Overview

Directory of Open Access Journals (Sweden)

Şeyda Gür

2018-01-01

Full Text Available Increased healthcare costs are pushing hospitals to reduce costs and increase the quality of care. Operating rooms are the most important source of income and expense for hospitals. Therefore, the hospital management focuses on the effectiveness of schedules and plans. This study includes analyses of recent research on operating room scheduling and planning. Most studies in the literature, from 2000 to the present day, were evaluated according to patient characteristics, performance measures, solution techniques used in the research, the uncertainty of the problem, applicability of the research, and the planning strategy to be dealt within the solution. One hundred seventy studies were examined in detail, after scanning the Emerald, Science Direct, JSTOR, Springer, Taylor and Francis, and Google Scholar databases. To facilitate the identification of these studies, they are grouped according to the different criteria of concern and then, a detailed overview is presented.

Skipping Strategy (SS) for Initial Population of Job-Shop Scheduling Problem

Science.gov (United States)

Abdolrazzagh-Nezhad, M.; Nababan, E. B.; Sarim, H. M.

2018-03-01

Initial population in job-shop scheduling problem (JSSP) is an essential step to obtain near optimal solution. Techniques used to solve JSSP are computationally demanding. Skipping strategy (SS) is employed to acquire initial population after sequence of job on machine and sequence of operations (expressed in Plates-jobs and mPlates-jobs) are determined. The proposed technique is applied to benchmark datasets and the results are compared to that of other initialization techniques. It is shown that the initial population obtained from the SS approach could generate optimal solution.

Maximizing Total Profit in Two-agent Problem of Order Acceptance and Scheduling

Directory of Open Access Journals (Sweden)

Mohammad Reisi-Nafchi

2017-03-01

Full Text Available In competitive markets, attracting potential customers and keeping current customers is a survival condition for each company. So, paying attention to the requests of customers is important and vital. In this paper, the problem of order acceptance and scheduling has been studied, in which two types of customers or agents compete in a single machine environment. The objective is maximizing sum of the total profit of first agent's accepted orders and the total revenue of second agent. Therefore, only the first agent has penalty and its penalty function is lateness and the second agent's orders have a common due date and this agent does not accept any tardy order. To solve the problem, a mathematical programming, a heuristic algorithm and a pseudo-polynomial dynamic programming algorithm are proposed. Computational results confirm the ability of solving all problem instances up to 70 orders size optimally and also 93.12% of problem instances up to 150 orders size by dynamic programming.

A Literature Survey for Earliness/Tardiness Scheduling Problems with Learning Effect

Directory of Open Access Journals (Sweden)

Mesut Cemil İŞLER

2009-02-01

Full Text Available When a task or work is done continuously, there will be an experience so following times needs of required resources (manpower, materials, etc. will be reduced. This learning curve described first by Wright. Wright determined how workmanship costs decreased while proceed plain increasing. This investigations correctness found consistent by plain producers. Learning effect is an effect that, works can be done in shorter time in the rate of repeat of work with repeating same or similar works in production process. Nowadays classical production systems adapted more acceptable systems with new approaches. Just in time production system (JIT philosophy is one of the most important production system philosophies. JIT which is known production without stock stands on using all product resources optimum. Minimization problem of Earliness/Tardiness finishing penalty, which we can describe Just in time scheduling, appeared by inspired from JIT philosophy. In this study, there is literature survey which directed to earliness/tardiness performance criteria and learning effect processing in scheduling and as a result of this it is obtained some establishing for literature.

Using Improved Ant Colony Algorithm to Investigate EMU Circulation Scheduling Problem

Directory of Open Access Journals (Sweden)

Yu Zhou

2014-01-01

Full Text Available High-speed railway is one of the most important ways to solve the long-standing travel difficulty problem in China. However, due to the high acquisition and maintenance cost, it is impossible for decision-making departments to purchase enough EMUs to satisfy the explosive travel demand. Therefore, there is an urgent need to study how to utilize EMU more efficiently and reduce costs in the case of completing a given task in train diagram. In this paper, an EMU circulation scheduling model is built based on train diagram constraints, maintenance constraints, and so forth; in the model solving process, an improved ACA algorithm has been designed. A case study is conducted to verify the feasibility of the model. Moreover, contrast tests have been carried out to compare the efficiency between the improved ACA and the traditional approaches. The results reveal that improved ACA method can solve the model with less time and the quality of each representative index is much better, which means that efficiency of the improved ACA method is higher and better scheduling scheme can be obtained.

A branch and cut approach to the multiproduct pipeline scheduling problem

Energy Technology Data Exchange (ETDEWEB)

Souza Filho, Erito Marques de; Bahiense, Laura; Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2009-07-01

Pipelines are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. We address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. The major difficulties faced in these operations are related to the satisfaction of product demands by the various consumer markets, and operational constraints such as the maximum sizes of contiguous pumping packs, and the immiscible products. Several researchers have developed models and techniques for this short-term pipeline scheduling problem. Two different methodologies have been proposed in the literature: heuristic search techniques and exact methods. In this paper, we use a branch-and cut algorithm, performed in Xpress-MP{sup T}M, and compare the solutions obtained with that ones obtained before using the Variable Neighborhood Search metaheuristic. The computational results showed a significant improvement of performance in relation to previous algorithm. (author)

Entropy production of stationary diffusions on non-compact Riemannian manifolds

Institute of Scientific and Technical Information of China (English)

龚光鲁; 钱敏平

1997-01-01

The closed form of the entropy production of stationary diffusion processes with bounded Nelson’s current velocity is given.The limit of the entropy productions of a sequence of reflecting diffusions is also discussed.

Solving and Interpreting Large-scale Harvest Scheduling Problems by Duality and Decomposition

OpenAIRE

Berck, Peter; Bible, Thomas

1982-01-01

This paper presents a solution to the forest planning problem that takes advantage of both the duality of linear programming formulations currently being used for harvest scheduling and the characteristics of decomposition inherent in the forest land class-relationship. The subproblems of decomposition, defined as the dual, can be solved in a simple, recursive fashion. In effect, such a technique reduces the computational burden in terms of time and computer storage as compared to the traditi...

Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

Science.gov (United States)

Forootan, Ehsan; Kusche, Jürgen

2016-04-01

Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i

The simulation of stationary and non-stationary regime operation of heavy water production facilities

International Nuclear Information System (INIS)

Peculea, M.; Beca, T.; Constantinescu, D.M.; Dumitrescu, M.; Dimulescu, A.; Isbasescu, G.; Stefanescu, I.; Mihai, M.; Dogaru, C.; Marinescu, M.; Olariu, S.; Constantin, T.; Necula, A.

1995-01-01

This paper refers to testing procedures of the production capacity of heavy water production pilot, industrial scale plants and of heavy water reconcentration facilities. Simulation codes taking into account the mass and heat transfers inside the exchange columns were developed. These codes provided valuable insight about the isotope build-up of the installation which allowed estimating the time of reaching the stationary regime. Also transient regimes following perturbations in the operating parameters (i.e. temperature, pressure, fluid rates) of the installation were simulated and an optimal rate of routine inspections and adjustments was thus established

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....

Integrated Job Scheduling and Network Routing

DEFF Research Database (Denmark)

Gamst, Mette; Pisinger, David

2013-01-01

We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number of resou...... indicate that the algorithm can be used as an actual scheduling algorithm in the Grid or as a tool for analyzing Grid performance when adding extra machines or jobs. © 2012 Wiley Periodicals, Inc.......We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...

Non-stationary analysis of the frequency and intensity of heavy precipitation over Canada and their relations to large-scale climate patterns

Science.gov (United States)

Tan, Xuezhi; Gan, Thian Yew

2017-05-01

In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavy precipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavy precipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavy precipitation with non-stationary GP distributions, it is evident that AMP and heavy precipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavy precipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada.

A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Jian Xiong

2012-01-01

Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

Scheduling stochastic two-machine flow shop problems to minimize expected makespan

Directory of Open Access Journals (Sweden)

Mehdi Heydari

2013-07-01

Full Text Available During the past few years, despite tremendous contribution on deterministic flow shop problem, there are only limited number of works dedicated on stochastic cases. This paper examines stochastic scheduling problems in two-machine flow shop environment for expected makespan minimization where processing times of jobs are normally distributed. Since jobs have stochastic processing times, to minimize the expected makespan, the expected sum of the second machine’s free times is minimized. In other words, by minimization waiting times for the second machine, it is possible to reach the minimum of the objective function. A mathematical method is proposed which utilizes the properties of the normal distributions. Furthermore, this method can be used as a heuristic method for other distributions, as long as the means and variances are available. The performance of the proposed method is explored using some numerical examples.

Single machine scheduling with slack due dates assignment

Science.gov (United States)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, H.; Skutella, M.; Woeginger, Gerhard

2003-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, J.A.; Skutella, M.; Woeginger, G.J.; Paterson, M.

2000-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Stationary theory of scattering

International Nuclear Information System (INIS)

Kato, T.

1977-01-01

A variant of the stationary methods is described, and it is shown that it is useful in a wide range of problems, including scattering, by long-range potentials, two-space scattering, and multichannel scattering. The method is based on the notion of spectral forms. The paper is restricted to the simplest case of continuous spectral forms defined on a Banach space embedded in the basic Hilbert space. (P.D.)

Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines

Directory of Open Access Journals (Sweden)

Eliana Marcela Peña Tibaduiza

2017-01-01

Full Text Available Context: The flow shop hybrid problem with unrelated parallel machines has been less studied in the academia compared to the flow shop hybrid with identical processors. For this reason, there are few reports about the kind of application of this problem in industries. Method: A literature review of the state of the art on flow-shop scheduling problem was conducted by collecting and analyzing academic papers on several scientific databases. For this aim, a search query was constructed using keywords defining the problem and checking the inclusion of unrelated parallel machines in such definition; as a result, 50 papers were finally selected for this study. Results: A classification of the problem according to the characteristics of the production system was performed, also solution methods, constraints and objective functions commonly used are presented. Conclusions: An increasing trend is observed in studies of flow shop with multiple stages, but few are based on industry case-studies.

Artificial intelligence approaches to astronomical observation scheduling

Science.gov (United States)

Johnston, Mark D.; Miller, Glenn

1988-01-01

Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

Science.gov (United States)

Wang, Chun; Ji, Zhicheng; Wang, Yan

2017-07-01

In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.

Step-by-step cyclic processes scheduling

DEFF Research Database (Denmark)

Bocewicz, G.; Nielsen, Izabela Ewa; Banaszak, Z.

2013-01-01

Automated Guided Vehicles (AGVs) fleet scheduling is one of the big problems in Flexible Manufacturing System (FMS) control. The problem is more complicated when concurrent multi-product manufacturing and resource deadlock avoidance policies are considered. The objective of the research is to pro......Automated Guided Vehicles (AGVs) fleet scheduling is one of the big problems in Flexible Manufacturing System (FMS) control. The problem is more complicated when concurrent multi-product manufacturing and resource deadlock avoidance policies are considered. The objective of the research...... is to provide a declarative model enabling to state a constraint satisfaction problem aimed at AGVs fleet scheduling subject to assumed itineraries of concurrently manufactured product types. In other words, assuming a given layout of FMS’s material handling and production routes of simultaneously manufactured...... orders, the main objective is to provide the declarative framework aimed at conditions allowing one to calculate the AGVs fleet schedule in online mode. An illustrative example of the relevant algebra-like driven step-by-stem cyclic scheduling is provided....

Maximizing the nurses' preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm

Science.gov (United States)

Jafari, Hamed; Salmasi, Nasser

2015-09-01

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.

Identifying and tracking switching, non-stationary opponents: a Bayesian approach

CSIR Research Space (South Africa)

Hernandez-Leal, P

2016-02-01

Full Text Available extend BPR to adversarial settings, in particular, to opponents that switch from one stationary strategy to another. Our proposed extension enables learning new models in an online fashion when the learning agent detects that the current policies...

ENSO's non-stationary and non-Gaussian character: the role of climate shifts

Science.gov (United States)

Boucharel, J.; Dewitte, B.; Garel, B.; Du Penhoat, Y.

2009-07-01

El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation. Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all

Modeling the Hybrid Flow Shop Scheduling Problem Followed by an Assembly Stage Considering Aging Effects and Preventive Maintenance Activities

Directory of Open Access Journals (Sweden)

Seyyed Mohammad Hassan Hosseini

2016-05-01

Full Text Available Scheduling problem for the hybrid flow shop scheduling problem (HFSP followed by an assembly stage considering aging effects additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at the same time. The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan. A mathematical modeling is presented and its validation is shown by solving an example in small scale. Since this problem has been proved strongly NP-hard, in order to solve the problem in medium and large scale, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms.

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

Science.gov (United States)

Gay-Balmaz, François; Holm, Darryl D.

2018-01-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

Science.gov (United States)

Gay-Balmaz, François; Holm, Darryl D.

2018-06-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

The role of the dynamic pressure in stationary heat conduction of a rarefied polyatomic gas

Energy Technology Data Exchange (ETDEWEB)

Arima, Takashi, E-mail: arima@kanagawa-u.ac.jp [Department of Mechanical Engineering, Faculty of Engineering, Kanagawa University, Yokohama 221-8686 (Japan); Barbera, Elvira, E-mail: ebarbera@unime.it [Department of Mathematics and Computer Science, University of Messina, V.le F. D' Alcontres 31, 98166 Messina (Italy); Brini, Francesca, E-mail: francesca.brini@unibo.it [Department of Mathematics, University of Bologna, via Saragozza 8, 40123 Bologna (Italy); Sugiyama, Masaru, E-mail: sugiyama@nitech.ac.jp [Graduate School of Engineering, Nagoya Institute of Technology, Nagoya 466-8555 (Japan)

2014-07-18

The effect of the dynamic pressure (non-equilibrium pressure) on stationary heat conduction in a rarefied polyatomic gas at rest is elucidated by the theory of extended thermodynamics. It is shown that this effect is observable in a non-polytropic gas. Numerical studies are presented for a para-hydrogen gas as a typical example. - Highlights: • Heat transfer problem in polyatomic rarefied gases is studied in different domains. • Non-zero dynamic pressure is predicted in non-polytropic gases. • The effect of dynamic pressure can be observed indirectly in an experiment. • The case of para-hydrogen is analyzed as an example. • Navier–Stokes, Fourier, and Extended Thermodynamics predictions are compared.

An influence diagram for urban flood risk assessment through pluvial flood hazards under non-stationary conditions

DEFF Research Database (Denmark)

Åström, Helena Lisa Alexandra; Friis Hansen, P.; Garrè, Luca

2014-01-01

Urban flooding introduces significant risk to society. Non-stationarity leads to increased uncertainty and this is challenging to include in actual decision-making. The primary objective of this study was to develop a risk assessment and decision support framework for pluvial urban flood risk under...... non-stationary conditions using an influence diagram (ID) which is a Bayesian network (BN) extended with decision and utility nodes. Non-stationarity is considered to be the influence of climate change where extreme precipitation patterns change over time. The overall risk is quantified in monetary...... terms expressed as expected annual damage. The network is dynamic in as much as it assesses risk at different points in time. The framework provides means for decision-makers to assess how different decisions on flood adaptation affect the risk now and in the future. The result from the ID was extended...

Schedule Analytics

Science.gov (United States)

2016-04-30

Warfare, Naval Sea Systems Command Acquisition Cycle Time : Defining the Problem David Tate, Institute for Defense Analyses Schedule Analytics Jennifer...research was comprised of the following high- level steps :  Identify and review primary data sources 1...research. However, detailed reviews of the OMB IT Dashboard data revealed that schedule data is highly aggregated. Program start date and program end date

New Mathematical Model and Algorithm for Economic Lot Scheduling Problem in Flexible Flow Shop

Directory of Open Access Journals (Sweden)

H. Zohali

2018-03-01

Full Text Available This paper addresses the lot sizing and scheduling problem for a number of products in flexible flow shop with identical parallel machines. The production stages are in series, while separated by finite intermediate buffers. The objective is to minimize the sum of setup and inventory holding costs per unit of time. The available mathematical model of this problem in the literature suffers from huge complexity in terms of size and computation. In this paper, a new mixed integer linear program is developed for delay with the huge dimentions of the problem. Also, a new meta heuristic algorithm is developed for the problem. The results of the numerical experiments represent a significant advantage of the proposed model and algorithm compared with the available models and algorithms in the literature.

Terminal Appointment System Design by Non-stationary M(t)/Ek/c(t) Queueing Model and Genetic Algorithm

DEFF Research Database (Denmark)

Chen, Gang; Govindan, Kannan; Yang, Zhong-Zhen

2013-01-01

Long truck queue is a common problem at big marine container terminals, where the resources and equipment are usually scheduled to serve ships prior to trucks. To reduce truck queues, some container terminals adopt terminal appointment system (TAS) to manage truck arrivals. This paper addresses two...

Stationary measure in the multiverse

International Nuclear Information System (INIS)

Linde, Andrei; Vanchurin, Vitaly; Winitzki, Sergei

2009-01-01

We study the recently proposed ''stationary measure'' in the context of the string landscape scenario. We show that it suffers neither from the ''Boltzmann brain'' problem nor from the ''youngness'' paradox that makes some other measures predict a high CMB temperature at present. We also demonstrate a good performance of this measure in predicting the results of local experiments, such as proton decay

Non-Stationary Single-Channel Queuing System Features Research in Context of Number of Served Queries

Directory of Open Access Journals (Sweden)

Porshnev Sergey

2017-01-01

Full Text Available This work devoted to researching of mathematical model of non-stationary queuing system (NQS. Arrival rate in studied NQS λ(t is similar to rate which observed in practice in a real access control system of objects of mass events. Dependence of number of serviced requests from time was calculated. It is proven that the ratio value of served requests at the beginning of event to all served requests described by a deterministic function, depending on the average service rate μ¯$\\bar \\mu $ and the maximum value of the arrival rate function λ(t.

Modeling fire spatial non-stationary in Portugal using GWR and GAMLSS

Science.gov (United States)

Sá, Ana C. L.; Amaral Turkman, Maria A.; Bistinas, Ioannis; Pereira, José M. C.

2014-05-01

Portuguese wildfires are responsible for large environmental, ecological and socio-economic impacts and, in the last decade, vegetation fires consumed on average 140.000ha/year. Portugal has a unique fires-atlas of burnt scar perimeters covering the 1975-2009 period, which allows the assessment of the fire most affected areas. It's crucial to understand the influence of the main drivers of forest fires and its spatial distribution in order to set new management strategies to reduce its impacts. Thus, this study aims at evaluating the spatial stationarity of the fire-environment relationship using two statistical approaches: Geographically Weighted Regression (GWR) and Generalized Additive Models for Location, Scale and Shape (GAMLSS). Analysis was performed using a regular 2kmx2km cell size grid, a total of 21293 observations overlaying the mainland of Portugal. Fire incidence was determined as the number of times each grid cell burned in the 35 years period. For the GWR analysis the group of environmental variables selected as predictors are: ignition source (population density (PD)); vegetation (proportion of forest and shrubland (FORSHR)); and weather (total precipitation of the coldest quarter (PCQ). Results showed that the fire-environment relationship is non-stationary, thus the coefficient estimates of all the predictors vary spatially, both in magnitude and sign. The most statistically significant predictor is FORSHR, followed by the PCQ. Despite the relationship between fire incidence and PD is non-stationary, only 9% of the observations are statistically significant at a 95% level of confidence. When compared with the Ordinary Least Squares (OLS) global model, 53% of the R2 statistic is above the 26% global estimated value, meaning a better explanation of the fire incidence variance with the local model approach. Using the same environmental variables, fire incidence was also modeled using GAMLSS to characterize nonstationarities in fire incidence. It is

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

Science.gov (United States)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem

Directory of Open Access Journals (Sweden)

S Sarathambekai

2017-03-01

Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.

Automated Scheduling Via Artificial Intelligence

Science.gov (United States)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

Science.gov (United States)

Li, Jun-qing; Pan, Quan-ke; Mao, Kun

2014-01-01

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

Directory of Open Access Journals (Sweden)

Jun-qing Li

2014-01-01

Full Text Available A hybrid algorithm which combines particle swarm optimization (PSO and iterated local search (ILS is proposed for solving the hybrid flowshop scheduling (HFS problem with preventive maintenance (PM activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.

Hybrid particle swarm optimization for hybrid flowshop scheduling problem with maintenance activities.

Science.gov (United States)

Li, Jun-qing; Pan, Quan-ke; Mao, Kun

2014-01-01

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.

Towards Gravitating Discs around Stationary Black Holes

Science.gov (United States)

Semerák, Oldřich

This article outlines the search for an exact general relativistic description of the exterior(vacuum) gravitational field of a rotating spheroidal black hole surrounded by a realistic axially symmetric disc of matter. The problem of multi-body stationary spacetimes is first exposed from the perspective of the relativity theory (section 1) and astrophysics (section 2), listing the basic methods employed and results obtained. Then (in section 3) basic formulas for stationary axisymmetric solutions are summarized. Sections 4 and 5 review what we have learnt with Miroslav Žáček and Tomáš Zellerin about certain static and stationary situations recently. Concluding remarks are given in section 6. Although the survey part is quite general, the list of references cannot be complete.Our main desideratum was the informative value rather than originality — novelties have been preferred, mainly reviews and those with detailed introductions.

A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem

DEFF Research Database (Denmark)

Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher

2017-01-01

A railway signaling system is a complex and interdependent system which should ensure the safe operation of trains. We introduce and address a mixed integer optimisation model for the preventive signal maintenance crew scheduling problem in the Danish railway system. The problem contains many...... to feed as ‘warm start’ solutions to a Mixed Integer Programming (MIP) solver for further optimisation. We apply the CP/MIP framework to a section of the Danish rail network and benchmark our results against both direct application of a MIP solver and modelling the problem as a Constraint Optimisation...

Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates