Abstraction and control techniques for non-stationary scheduling problems
Innocenti, Giacomo
2009-01-01
The paper faces the problem of scheduling from a new perspective, trying to bridge the gap between classical heuristic approaches and system identification and control strategies. To this aim, a complete mathematical formulation of a general scheduling process is derived, beginning from very broad assumptions. This allows a greater freedom of manipulation and guarantee the resolution of the identification (and control) techniques. Both an adaptive and a switching strategies are presented in relation to the performances of a simple Round Robin algorithm.
Adsuara, J E; Cerdá-Durán, P; Mewes, V; Aloy, M A
2016-01-01
The Scheduled Relaxation Jacobi (SRJ) method is an extension of the classical Jacobi iterative method to solve linear systems of equations ($Au=b$) associated with elliptic problems. It inherits its robustness and accelerates its convergence rate computing a set of $P$ relaxation factors that result from a minimization problem. In a typical SRJ scheme, the former set of factors is employed in cycles of $M$ consecutive iterations until a prescribed tolerance is reached. We present the analytic form for the optimal set of relaxation factors for the case in which all of them are different, and find that the resulting algorithm is equivalent to a non-stationary generalized Richardson's method. Our method to estimate the weights has the advantage that the explicit computation of the maximum and minimum eigenvalues of the matrix $A$ is replaced by the (much easier) calculation of the maximum and minimum frequencies derived from a von Neumann analysis. This set of weights is also optimal for the general problem, res...
Adsuara, J. E.; Cordero-Carrión, I.; Cerdá-Durán, P.; Mewes, V.; Aloy, M. A.
2017-03-01
The Scheduled Relaxation Jacobi (SRJ) method is an extension of the classical Jacobi iterative method to solve linear systems of equations (Au = b) associated with elliptic problems. It inherits its robustness and accelerates its convergence rate computing a set of P relaxation factors that result from a minimization problem. In a typical SRJ scheme, the former set of factors is employed in cycles of M consecutive iterations until a prescribed tolerance is reached. We present the analytic form for the optimal set of relaxation factors for the case in which all of them are strictly different, and find that the resulting algorithm is equivalent to a non-stationary generalized Richardson's method where the matrix of the system of equations is preconditioned multiplying it by D = diag (A). Our method to estimate the weights has the advantage that the explicit computation of the maximum and minimum eigenvalues of the matrix A (or the corresponding iteration matrix of the underlying weighted Jacobi scheme) is replaced by the (much easier) calculation of the maximum and minimum frequencies derived from a von Neumann analysis of the continuous elliptic operator. This set of weights is also the optimal one for the general problem, resulting in the fastest convergence of all possible SRJ schemes for a given grid structure. The amplification factor of the method can be found analytically and allows for the exact estimation of the number of iterations needed to achieve a desired tolerance. We also show that with the set of weights computed for the optimal SRJ scheme for a fixed cycle size it is possible to estimate numerically the optimal value of the parameter ω in the Successive Overrelaxation (SOR) method in some cases. Finally, we demonstrate with practical examples that our method also works very well for Poisson-like problems in which a high-order discretization of the Laplacian operator is employed (e.g., a 9- or 17-points discretization). This is of interest since the
A REDUCED MFE FORMULATION BASED ON POD FOR THE NON-STATIONARY CONDUCTION-CONVECTION PROBLEMS
Institute of Scientific and Technical Information of China (English)
Luo Zhendong; Xie Zhenghui; Chen Jing
2011-01-01
In this article,a reduced mixed finite element (MFE) formulation based on proper orthogonal decomposition (POD) for the non-stationary conduction-convection problems is presented.Also the error estimates between the reduced MFE solutions based on POD and usual MFE solutions are derived.It is shown by numerical examples that the results of numerical computation are consistent with theoretical conclusions.Moreover,it is shown that the reduced MFE formulation based on POD is feasible and efficient in finding numerical solutions for the non-stationary conduction-convection problems.
Numerical Solution of Problem for Non-Stationary Heat Conduction in Multi-Layer Bodies
Directory of Open Access Journals (Sweden)
R. I. Еsman
2007-01-01
Full Text Available A mathematical model for non-stationary heat conduction of multi-layer bodies has been developed. Dirac’s δ-function is used to take into account phase and chemical transformations in one of the wall layers. While formulating a problem non-linear heat conduction equations have been used with due account of dependence of thermal and physical characteristics on temperature. Solution of the problem is realized with the help of methods of a numerical experiment and computer modeling.
Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device
Ayriyan, Alexander; Donets, Eugeny E; Grigorian, Hovik; Pribis, Jan
2016-01-01
A model of a multilayer device with non-trivial geometrical and material structure and its working process is suggested. The thermal behavior of the device as one principle characteristic is simulated. The algorithm for solving the non-stationary heat conduction problem with a time-dependent periodical heating source is suggested. The algorithm is based on finite difference explicit--implicit method. The OpenCL realization of the algorithm is discussed. The results show that the chosen characteristics of the device configuration are suitable for the working requirements for application.
Scheduling Non-stationary Bursts of Real-time and Non-real-time Traffic in ATM Networks
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The problem of scheduling real-time and non-real-time traffic in an ATM switch multiplexor when bursts of either type of traffic occur is studied. The scheduling algorithms studied are: Queue Length Threshold (QLT) and Minimum Laxity Threshold (MLT). Analytic results based on Markov Chains are used. In addition the results are compared with an optimal (but impractical) scheduling determined via dynamic programming. Dynamic programming is used in this paper to show that MLT gives a near optimal performance trade-off between real-time and non-real-time traffic for constant arrival rates. The trade-off QLT allows is not close to optimal. For non-real-time bursts MLT still gives a close to optimal trade-off. For real-time bursts the trade-off MLT allows between real-time and non-real-time traffic is not as close to optimal, but even where the MLT trade-off is not near optimal, the QLT trade-off is much worse than the MLT trade-off.
Ashirbayev, Nurgali; Ashirbayeva, Zhansaya; Sultanbek, Turlybek; Bekmoldayeva, Raina
2016-08-01
In this work we consider the problem of the propagation of non stationary stress waves in an elastic body with a rectangular hole in the linear formulation. The wave process is caused by applying an external dynamic load on the front boundary of the rectangular region and the lateral boundaries are free of the stress. The lower boundary of the rectangular region is rigidly fixed, and the contour of the rectangular hole is free from the stress. The problem is solved by using the difference method of the spatial characteristics. On the basis of the developed numerical methods it is obtained the computational finite - difference relations of the dynamic problems at the corner points of the rectangular hole, where the first and second derivatives of the unknown functions have a discontinuity of the first kind. We analyze the dynamic stress fields in an elastic body with a rectangular hole and we studied the concentration of dynamic stresses in the vicinity of the corner points of the rectangular opening.
Routing and scheduling problems
DEFF Research Database (Denmark)
Reinhardt, Line Blander
be that the objects routed have an availability time window and a delivery time window or that locations on the path have a service time window. When routing moving transportation objects such as vehicles and vessels schedules are made in connection with the routing. Such schedules represent the time for the presence...... to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...... of a connection between two locations. This could be an urban bus schedule where busses are routed and this routing creates a bus schedule which the passengers between locations use. In this thesis various routing and scheduling problems will be presented. The topics covered will be routing from an origin...
SCHEDULING PROBLEMS-AN OVERVIEW
Institute of Scientific and Technical Information of China (English)
Asmuliardi MULUK; Hasan AKPOLAT; Jichao XU
2003-01-01
There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days.These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition, other approaches to solving scheduling problems, for instance approaches based on human factors, prefer the scheduling system to be more flexible in both design and implementation. After discussion of these factors, the authors propose the integration of a different set of criteria for the development of scheduling systems which not only appears to have a better flexibility but also increased customer-focus.
Routing and scheduling problems
DEFF Research Database (Denmark)
Reinhardt, Line Blander
In today’s globalized society, transport contributes to our daily life in many different ways. The production of the parts for a shelf ready product may take place on several continents and our travel between home and work, vacation travel and business trips has increased in distance the last......, the effectiveness of the network is of importance aiming at satisfying as many costumer demands as possible at a low cost. Routing represent a path between locations such as an origin and destination for the object routed. Sometimes routing has a time dimension as well as the physical paths. This may...... to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...
Shiryaeva, E V; Zhukov, M Yu
2013-01-01
The mathematical model describing the non-stationary natural pH-gradient arising under the action of an electric field in an aqueous solution of ampholytes (amino acids) is constructed and investigated. The model is part of a more general model of the isoelectrofocusing (IEF) process. To numerical study of the model we use the finite elements method that allows to significantly reduce the computation time. We also examine the influence of the different effects (taking into account the water ions, the various forms of Ohm's law, the difference between isoelectric and isoionic points of the substances) on the process IEF.
Yankovskii, A. P.
2017-03-01
The nonlinear problem of non-stationary heat conductivity of the layered anisotropic heat-sensitive shells was formulated taking into account the linear dependence of thermal-physical characteristics of the materials of phase compositions on the temperature. The initial-boundary-value problem is formulated in the dimensionless form, and four small parameters are identified: thermal-physical, characterizing the degree of heat sensitivity of the layer material; geometric, characterizing the relative thickness of the thin-walled structure, and two small Biot numbers on the front surfaces of shells. A sequential recursion of dimensionless equations is carried out, at first, using the thermalphysical small parameter, then, small Biot numbers and, finally, geometrical small parameter. The first type of recursion allowed us to linearize the problem of heat conductivity, and on the basis of two latter types of recursion, the outer asymptotic expansion of solution to the problem of non-stationary heat conductivity of the layered anisotropic non-uniform shells and plates under boundary conditions of the II and III kind and small Biot numbers on the facial surfaces was built, taking into account heat sensitivity of the layer materials. The resulting two-dimensional boundary problems were analyzed, and asymptotic properties of solutions to the heat conductivity problem were studied. The physical explanation was given to some aspects of asymptotic temperature decomposition.
A Scheduling Problem for Hospital Operating Theatre
Sufahani, Suliadi F; Ismail, Zuhaimy
2012-01-01
This paper provides a classification of real scheduling problems. Various ways have been examined and described on the problem. Scheduling problem faces a tremendous challenges and difficulties in order to meet the preferences of the consumer. Dealing with scheduling problem is complicated, inefficient and time-consuming. This study aims to develop a mathematical model for scheduling the operating theatre during peak and off peak time. Scheduling problem is a well known optimization problem and the goal is to find the best possible optimal solution. In this paper, we used integer linear programming technique for scheduling problem in a high level of synthesis. In addition, time and resource constrained scheduling was used. An optimal result was fully obtained by using the software GLPK/AMPL. This model can be adopted to solve other scheduling problems, such as the Lecture Theatre, Cinemas and Work Shift.
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....
Constraint-based scheduling applying constraint programming to scheduling problems
Baptiste, Philippe; Nuijten, Wim
2001-01-01
Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...
Fusing Heterogeneous Data for Detection Under Non-stationary Dependence
2012-07-01
In this paper, we consider the problem of detection for dependent, non-stationary signals where the non-stationarity is encoded in the dependence ...allows for a more general description of inter-sensor dependence . We design a copula-based detector using the Neyman-Pearson framework. Our approach
Slow Sphering to Suppress Non-Stationaries in the EEG
Reuderink, Boris; Farquhar, Jason; Poel, Mannes
2011-01-01
Non-stationary signals are ubiquitous in electroencephalogram (EEG) signals and pose a problem for robust application of brain-computer interfaces (BCIs). These non-stationarities can be caused by changes in neural background activity. We present a dynamic spatial filter based on time local whitenin
On green routing and scheduling problem
Touati, Nora
2012-01-01
The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools.
On green routing and scheduling problem
Touati, Nora; Jost, Vincent
2011-01-01
The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools.
Learning in Non-Stationary Environments Methods and Applications
Lughofer, Edwin
2012-01-01
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...
Institute of Scientific and Technical Information of China (English)
常晓蓉; 冯民富
2011-01-01
本文将近年来基于协调有限元逼近提出的涡旋粘性法推广应用到非协调有限元逼近,对非定常的对流占优扩散问题,空间采用非协调Crouzeix-Raviart元逼近,时间用Crank-Nicolson差分离散格式,提出了Crank-Nicolson差分-局部投影法稳定化有限元格式,我们对稳定性和误差估计给出了详细的分析,得出了最优的估计.%This paper is concerned with the extension of the conforming element approximations based on eddy viscosity to the nonconforming element approximation. For the non-stationary convection diffusion problem, where the Crouzeix-Raviart element is employed. A fully discretized formulation with a Crank-Nicholson scheme for the time variable, and a Crank-Nicholson difference - local projection method finite element scheme is prensented.We prove stability and convergence, then an optimal error estimate is obtained.
On non-stationary threshold autoregressive models
Liu, Weidong; Shao, Qi-Man; 10.3150/10-BEJ306
2011-01-01
In this paper we study the limiting distributions of the least-squares estimators for the non-stationary first-order threshold autoregressive (TAR(1)) model. It is proved that the limiting behaviors of the TAR(1) process are very different from those of the classical unit root model and the explosive AR(1).
An Augmented Lagrangian Approach for Scheduling Problems
Nishi, Tatsushi; Konishi, Masami
The paper describes an augmented Lagrangian decomposition and coordination approach for solving single machine scheduling problems to minimize the total weighted tardiness. The problem belongs to the class of NP-hard combinatorial optimization problem. We propose an augmented Lagrangian decomposition and coordination approach, which is commonly used for continuous optimization problems, for solving scheduling problems despite the fact that the problem is nonconvex and non-differentiable. The proposed method shows a good convergence to a feasible solution without heuristically constructing a feasible solution. The performance of the proposed method is compared with that of an ordinary Lagrangian relaxation.
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaël
2016-03-03
Max-stable processes are natural models for spatial extremes because they provide suitable asymptotic approximations to the distribution of maxima of random fields. In the recent past, several parametric families of stationary max-stable models have been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference is performed using pairwise likelihoods, and its performance is assessed by an extensive simulation study based on a non-stationary locally isotropic extremal t model. Evidence that unknown parameters are well estimated is provided, and estimation of spatial return level curves is discussed. The methodology is demonstrated with temperature maxima recorded over a complex topography. Models are shown to satisfactorily capture extremal dependence.
On-line blind separation of non-stationary signals
Directory of Open Access Journals (Sweden)
Todorović-Zarkula Slavica
2005-01-01
Full Text Available This paper addresses the problem of blind separation of non-stationary signals. We introduce an on-line separating algorithm for estimation of independent source signals using the assumption of non-stationary of sources. As a separating model, we apply a self-organizing neural network with lateral connections, and define a contrast function based on correlation of the network outputs. A separating algorithm for adaptation of the network weights is derived using the state-space model of the network dynamics, and the extended Kalman filter. Simulation results obtained in blind separation of artificial and real-world signals from their artificial mixtures have shown that separating algorithm based on the extended Kalman filter outperforms stochastic gradient based algorithm both in convergence speed and estimation accuracy.
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.
EDITORIAL: CAMOP: Quantum Non-Stationary Systems CAMOP: Quantum Non-Stationary Systems
Dodonov, Victor V.; Man'ko, Margarita A.
2010-09-01
QED. Another rapidly growing research field (although its origin can be traced to the beginning of the 1980s) is the quantum control of evolution at the microscopic level. These examples show that quantum non-stationary systems continue to be a living and very interesting part of quantum physics, uniting researchers from many different areas. Thus it is no mere chance that several special scientific meetings devoted to these topics have been organized recently. One was the international seminar 'Time-Dependent Phenomena in Quantum Mechanics' organized by Manfred Kleber and Tobias Kramer in 2007 at Blaubeuren, Germany. The proceedings of that event were published in 2008 as volume 99 of Journal of Physics: Conference Series. Another recent meeting was the International Workshop on Quantum Non-Stationary Systems, held on 19-23 October 2009 at the International Center for Condensed Matter Physics (ICCMP) in Brasilia, Brazil. It was organized and directed by Victor Dodonov (Institute of Physics, University of Brasilia, Brazil), Vladimir Man'ko (P N Lebedev Physical Institute, Moscow, Russia) and Salomon Mizrahi (Physics Department, Federal University of Sao Carlos, Brazil). This event was accompanied by a satellite workshop 'Quantum Dynamics in Optics and Matter', organized by Salomon Mizrahi and Victor Dodonov on 25-26 October 2009 at the Physics Department of the Federal University of Sao Carlos, Brazil. These two workshops, supported by the Brazilian federal agencies CAPES and CNPq and the local agencies FAP-DF and FAPESP, were attended by more than 120 participants from 16 countries. Almost 50 invited talks and 20 poster presentations covered a wide area of research in quantum mechanics, quantum optics and quantum information. This special issue of CAMOP/Physica Scripta contains contributions presented by some invited speakers and participants of the workshop in Brasilia. Although they do not cover all of the wide spectrum of problems related to quantum non-stationary
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...... 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....
ALGORITHM FOR SOLVING EXTREME SCHEDULING PROBLEMS
Gennady A. Berketov
2015-01-01
The article considers the original algorithmfor solving the generalized problem ofscheduling theory, based on the branch and bound method. Task schedulingperform works (operations) and restrictions on resources used often occur with scheduling discrete manufacturing operations, optimizing network implementationschedules of scientific, economic or technical projects. Tools to solve suchproblems are included in the decisionsupport system ACS in many businesses.The effectiveness of the proposed ...
Genetic Algorithms for Satellite Scheduling Problems
Directory of Open Access Journals (Sweden)
Fatos Xhafa
2012-01-01
Full Text Available Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.
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...... 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...... branch-and-price solution algorithm, as this method has previously given solid results for classical vehicle routing problems. Temporal dependencies are modelled as generalised precedence constraints and enforced through the branching. We introduce a novel visit clustering approach based on the soft...
An Entropy Measure of Non-Stationary Processes
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Ling Feng Liu
2014-03-01
Full Text Available Shannon’s source entropy formula is not appropriate to measure the uncertainty of non-stationary processes. In this paper, we propose a new entropy measure for non-stationary processes, which is greater than or equal to Shannon’s source entropy. The maximum entropy of the non-stationary process has been considered, and it can be used as a design guideline in cryptography.
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.
Algorithms for Assembly-Type Flowshop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
An assembly-type flowshop scheduling problem with minimizing makespan is considered in this paper. The problem of scheduling for minimizing makespan is first addressed, and then a new heuristic algorithm is proposed for it.
Model of non-stationary, inhomogeneous turbulence
Bragg, Andrew D.; Kurien, Susan; Clark, Timothy T.
2017-02-01
We compare results from a spectral model for non-stationary, inhomogeneous turbulence (Besnard et al. in Theor Comp Fluid Dyn 8:1-35, 1996) with direct numerical simulation (DNS) data of a shear-free mixing layer (SFML) (Tordella et al. in Phys Rev E 77:016309, 2008). The SFML is used as a test case in which the efficacy of the model closure for the physical-space transport of the fluid velocity field can be tested in a flow with inhomogeneity, without the additional complexity of mean-flow coupling. The model is able to capture certain features of the SFML quite well for intermediate to long times, including the evolution of the mixing-layer width and turbulent kinetic energy. At short-times, and for more sensitive statistics such as the generation of the velocity field anisotropy, the model is less accurate. We propose two possible causes for the discrepancies. The first is the local approximation to the pressure-transport and the second is the a priori spherical averaging used to reduce the dimensionality of the solution space of the model, from wavevector to wavenumber space. DNS data are then used to gauge the relative importance of both possible deficiencies in the model.
A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
Gonçalves, José Fernando; Mendes, J. J. M.; Resende, Maurício G. C.
2005-01-01
This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set o...
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.
Non-stationary Effects In Space-charge Dominated Electron Beams
Agafonov, A V; Tarakanov, V P
2004-01-01
Problems of non-linear dynamics of space charge dominated electron beams in plane and in coaxial electron guns are discussed from the point of view of non-stationary behaviour of beams. The results of computer simulations of beam formation are presented for several simple plane diode geometries and for the gun with large compression of annular beam. Emphasised is non-stationary behaviour combined with edge and hysteresis effects. Non-stationary effects in crossed electron and magnetic field are considered from the point of view a development of schemes of intense electron beam formation for compact accelerators and RF-devices. The results of computer simulation of beam formation inside coaxial guns are described under condition of secondary self-sustaining emission. Possibilities of electron storage and capture due to transient processes are discussed. Work supported by RFBR under grant 03-02-17301.
Distributing Flexibility to Enhance Robustness in Task Scheduling Problems
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
Inventory control for a perishable product with non-stationary demand and service level constraints
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 lo
Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.
2010-01-01
In this paper we address the general multi-period production/inventory problem with non-stationary stochastic demand and supplier lead-time under service level constraints. A replenishment cycle policy (Rn,Sn) is modeled, where Rn is the nth replenishment cycle length and Sn is the respective order-
Minimizing the Makespan for Scheduling Problems with General Deterioration Effects
Directory of Open Access Journals (Sweden)
Xianyu Yu
2013-01-01
Full Text Available This paper investigates the scheduling problems with general deterioration models. By the deterioration models, the actual processing time functions of jobs depend not only on the scheduled position in the job sequence but also on the total weighted normal processing times of the jobs already processed. In this paper, the objective is to minimize the makespan. For the single-machine scheduling problems with general deterioration effects, we show that the considered problems are polynomially solvable. For the flow shop scheduling problems with general deterioration effects, we also show that the problems can be optimally solved in polynomial time under the proposed conditions.
Thermal Radiation of a General Non-stationary Black Hole
Institute of Scientific and Technical Information of China (English)
杨成全; 任秦安; 赵峥
1994-01-01
The thermal radiation of the most general non-stationary black holes is discussed in this paper.The universal representatives determining the location of an event horizon and the temperature function are given.
Tunnelling effect of the non-stationary Kerr black hole
Institute of Scientific and Technical Information of China (English)
Yang Shu-Zheng; Chen De-You
2008-01-01
Extending Parikh and Wilezek's work to the non-stationary black hole, we study the Hawking radiation of the non-stationary Kerr black hole by the Hamilton-Jacobi method. The result shows that the radiation spectrum is not purely thermal and the tunnelling probability is related to the change of Bekenstein-Hawking entropy, which gives a correction to the Hawking thermal radiation of the black hole.
Gaussian semiparametric estimation of non-stationary time series
Velasco, Carlos
1998-01-01
Generalizing the definition of the memory parameter d in terms of the differentiated series, we showed in Velasco (Non-stationary log-periodogram regression, Forthcoming J. Economet., 1997) that it is possible to estimate consistently the memory of non-stationary processes using methods designed for stationary long-range-dependent time series. In this paper we consider the Gaussian semiparametric estimate analysed by Robinson (Gaussian semiparametric estimation of long range dependence. Ann. ...
Solving project scheduling problems by minimum cut computations
Möhring, R.H.; Schulz, A.S.; Stork, F.; Uetz, M.J.
2003-01-01
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 manufactur
Job shop scheduling problem based on DNA computing
Institute of Scientific and Technical Information of China (English)
Yin Zhixiang; Cui Jianzhong; Yang Yan; Ma Ying
2006-01-01
To solve job shop scheduling problem, a new approach-DNA computing is used in solving job shop scheduling problem. The approach using DNA computing to solve job shop scheduling is divided into three stands. Finally, optimum solutions are obtained by sequencing. A small job shop scheduling problem is solved in DNA computing, and the "operations" of the computation were performed with standard protocols, as ligation, synthesis, electrophoresis etc. This work represents further evidence for the ability of DNA computing to solve NP-complete search problems.
Robust H∞ control of active vehicle suspension under non-stationary running
Guo, Li-Xin; Zhang, Li-Ping
2012-12-01
Due to complexity of the controlled objects, the selection of control strategies and algorithms in vehicle control system designs is an important task. Moreover, the control problem of automobile active suspensions has been become one of the important relevant investigations due to the constrained peculiarity and parameter uncertainty of mathematical models. In this study, after establishing the non-stationary road surface excitation model, a study on the active suspension control for non-stationary running condition was conducted using robust H∞ control and linear matrix inequality optimization. The dynamic equation of a two-degree-of-freedom quarter car model with parameter uncertainty was derived. The H∞ state feedback control strategy with time-domain hard constraints was proposed, and then was used to design the active suspension control system of the quarter car model. Time-domain analysis and parameter robustness analysis were carried out to evaluate the proposed controller stability. Simulation results show that the proposed control strategy has high systemic stability on the condition of non-stationary running and parameter uncertainty (including suspension mass, suspension stiffness and tire stiffness). The proposed control strategy can achieve a promising improvement on ride comfort and satisfy the requirements of dynamic suspension deflection, dynamic tire loads and required control forces within given constraints, as well as non-stationary running condition.
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.
An Iterated Local Search Algorithm for a Place Scheduling Problem
Directory of Open Access Journals (Sweden)
Shicheng Hu
2013-01-01
Full Text Available We study the place scheduling problem which has many application backgrounds in realities. For the block manufacturing project with special manufacturing platform requirements, we propose a place resource schedule problem. First, the mathematical model for the place resource schedule problem is given. On the basis of resource-constrained project scheduling problem and packing problem, we develop a hybrid heuristic method which combines priority rules and three-dimensional best fit algorithm, in which the priority rules determine the scheduling order and the three-dimensional best fit algorithm solves the placement. After this method is used to get an initial solution, the iterated local search is employed to get an improvement. Finally, we use a set of simulation data to demonstrate the steps of the proposed method and verify its feasibility.
Time reversibility from visibility graphs of non-stationary processes
Lacasa, Lucas
2015-01-01
Visibility algorithms are a family of methods to map time series into networks, with the aim of describing the structure of time series and their underlying dynamical properties in graph-theoretical terms. Here we explore some properties of both natural and horizontal visibility graphs associated to several non-stationary processes, and we pay particular attention to their capacity to assess time irreversibility. Non-stationary signals are (infinitely) irreversible by definition (independently of whether the process is Markovian or producing entropy at a positive rate), and thus the link between entropy production and time series irreversibility has only been explored in non-equilibrium stationary states. Here we show that the visibility formalism naturally induces a new working definition of time irreversibility, which allows to quantify several degrees of irreversibility for stationary and non-stationary series, yielding finite values that can be used to efficiently assess the presence of memory and off-equ...
Simulation of non-stationary ground motion processes (II)
Institute of Scientific and Technical Information of China (English)
LIANG Jian-wen
2005-01-01
This paper proposes a method for simulation of non-stationary ground motion processes having the identical statistical feature, time-dependent power spectrum, with a given ground motion record, on the basis of review of simulation of non-stationary ground motion processes. The method has the following advantages: the sample processes are non-stationary both in amplitude and frequency, and both the amplitude and frequency non-stationarity depend on the target power spectrum; the power spectrum of any sample process does not necessarily accord with the target power spectrum, but statistically, it strictly accords with the target power spectrum. Finally, the method is verified by simulation of one acceleration record in Landers earthquake.
Job shop scheduling problem with late work criterion
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.
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.
The Novel Heuristic for Data Transmission Dynamic Scheduling Problems
Directory of Open Access Journals (Sweden)
Hao Xu
2013-01-01
Full Text Available The data transmission dynamic scheduling is a process that allocates the ground stations and available time windows to the data transmission tasks dynamically for improving the resource utilization. A novel heuristic is proposed to solve the data transmission dynamic scheduling problem. The characteristic of this heuristic is the dynamic hybridization of simple rules. Experimental results suggest that the proposed algorithm is correct, feasible, and available. The dynamic hybridization of simple rules can largely improve the efficiency of scheduling.
METHODS FOR THE SHIFT DESIGN AND PERSONNEL TASK SCHEDULING PROBLEM
Lapègue, Tanguy; Bellenguez-Morineau, Odile; Prot, Damien
2014-01-01
Colloque avec actes et comité de lecture. internationale.; International audience; This paper introduces an overview of the methods that have been used in the literature to solve the Shift Design and Personnel Task Scheduling Problem with Equity. Basically, this problem aims at designing a schedule while assigning fixed tasks, that cannot be preempted, to an heterogeneous workforce. Such problem may occur in several contexts, where industrial activity requires a sharp and efficient management...
Non-stationary blind deconvolution of medical ultrasound scans
Michailovich, Oleg V.
2017-03-01
In linear approximation, the formation of a radio-frequency (RF) ultrasound image can be described based on a standard convolution model in which the image is obtained as a result of convolution of the point spread function (PSF) of the ultrasound scanner in use with a tissue reflectivity function (TRF). Due to the band-limited nature of the PSF, the RF images can only be acquired at a finite spatial resolution, which is often insufficient for proper representation of the diagnostic information contained in the TRF. One particular way to alleviate this problem is by means of image deconvolution, which is usually performed in a "blind" mode, when both PSF and TRF are estimated at the same time. Despite its proven effectiveness, blind deconvolution (BD) still suffers from a number of drawbacks, chief among which stems from its dependence on a stationary convolution model, which is incapable of accounting for the spatial variability of the PSF. As a result, virtually all existing BD algorithms are applied to localized segments of RF images. In this work, we introduce a novel method for non-stationary BD, which is capable of recovering the TRF concurrently with the spatially variable PSF. Particularly, our approach is based on semigroup theory which allows one to describe the effect of such a PSF in terms of the action of a properly defined linear semigroup. The approach leads to a tractable optimization problem, which can be solved using standard numerical methods. The effectiveness of the proposed solution is supported by experiments with in vivo ultrasound data.
Periodic review for a perishable item under non stationary stochastic demand
Rossi, Roberto
2013-01-01
We consider the periodic-review, single-location, single-product, production/inventory control problem under non stationary demand and service-level constraints. The product is perishable and has a fixed shelf life. Costs comprise fixed ordering costs and inventory holding costs. For this inventory system we discuss a number of control policies that may be adopted. For one of these policies, we assess the quality of an approximate Constraint Programming (CP) model for computing near optimum p...
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.
Handling Deafness Problem of Scheduled Multi-Channel Polling MACs
Jiang, Fulong; Liu, Hao; Shi, Longxing
Combining scheduled channel polling with channel diversity is a promising way for a MAC protocol to achieve high energy efficiency and performance under both light and heavy traffic conditions. However, the deafness problem may cancel out the benefit of channel diversity. In this paper, we first investigate the deafness problem of scheduled multi-channel polling MACs with experiments. Then we propose and evaluate two schemes to handle the deafness problem. Our experiment shows that deafness is a significant reason for performance degradation in scheduled multi-channel polling MACs. A proper scheme should be chosen depending on the traffic pattern and the design objective.
Robust Forecasting of Non-Stationary Time Series
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 foreca
Non-stationary condition monitoring through event alignment
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan
2004-01-01
. 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...
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...
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...... on the angular location of residual energy. Also, the framework can be extended, for instance by post modeling of repeated faults. Furthermore, we have investigated the problem of non-stationary condition monitoring when operational changes induce angular timing changes in the observed signals. Our contribution......, 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-...
Evaluation of the Methods for Response Analysis under Non-Stationary Excitation
Directory of Open Access Journals (Sweden)
R.S. Jangid
1999-01-01
Full Text Available Response of structures to non-stationary ground motion can be obtained either by the evolutionary spectral analysis or by the Markov approach. In certain conditions, a quasi-stationary analysis can also be performed. The first two methods of analysis are difficult to apply for complex situations such as problems involving soil-structure interaction, non-classical damping and primary-secondary structure interaction. The quasi-stationary analysis, on the other hand, provides an easier solution procedure for such cases. Here-in, the effectiveness of the quasi-stationary analysis is examined with the help of the analysis of a single degree-of-freedom (SDOF system under a set of parametric variations. For this purpose, responses of the SDOF system to uniformly modulated non-stationary random ground excitation are obtained by the three methods and they are compared. In addition, the relative computational efforts for different methods are also investigated.
Classification of routing and scheduling problems in liner shipping
DEFF Research Database (Denmark)
Hjortshøj Kjeldsen, Karina
A classification scheme for routing and scheduling problems in liner shipping is developed and subsequently used to classify existing literature on the subject. Based on the classification the articles are grouped, and the main characteristics of each group and article are described. The grouping...... may serve as a catalyst towards developing a model or a group of models that covers the main problems within routing and scheduling in liner shipping....
Resolution enhancement of non-stationary seismic data using amplitude-frequency partition
Xie, Yujiang; Liu, Gao
2015-02-01
As the Earth's inhomogeneous and viscoelastic properties, seismic signal attenuation we are trying to mitigate is a long-standing problem facing with high-resolution techniques. For addressing such a problem in the fields of time-frequency transform, Gabor transform methods such as atom-window method (AWM) and molecular window method (MWM) have been reported recently. However, we observed that these methods might be much better if we partition the non-stationary seismic data into adaptive stationary segments based on the amplitude and frequency information of the seismic signal. In this study, we present a new method called amplitude-frequency partition (AFP) to implement this process in the time-frequency domain. Cases of a synthetic and field seismic data indicated that the AFP method could partition the non-stationary seismic data into stationary segments approximately, and significantly, a high-resolution result would be achieved by combining the AFP method with conventional spectral-whitening method, which could be considered superior to previous resolution-enhancement methods like time-variant spectral whitening method, the AWM and the MWM as well. This AFP method presented in this study would be an effective resolution-enhancement tool for the non-stationary seismic data in the fields of an adaptive time-frequency transform.
Anticipation versus adaptation in Evolutionary Algorithms: The case of Non-Stationary Clustering
González, A. I.; Graña, M.; D'Anjou, A.; Torrealdea, F. J.
1998-07-01
From the technological point of view is usually more important to ensure the ability to react promptly to changing environmental conditions than to try to forecast them. Evolution Algorithms were proposed initially to drive the adaptation of complex systems to varying or uncertain environments. In the general setting, the adaptive-anticipatory dilemma reduces itself to the placement of the interaction with the environment in the computational schema. Adaptation consists of the estimation of the proper parameters from present data in order to react to a present environment situation. Anticipation consists of the estimation from present data in order to react to a future environment situation. This duality is expressed in the Evolutionary Computation paradigm by the precise location of the consideration of present data in the computation of the individuals fitness function. In this paper we consider several instances of Evolutionary Algorithms applied to precise problem and perform an experiment that test their response as anticipative and adaptive mechanisms. The non stationary problem considered is that of Non Stationary Clustering, more precisely the adaptive Color Quantization of image sequences. The experiment illustrates our ideas and gives some quantitative results that may support the proposition of the Evolutionary Computation paradigm for other tasks that require the interaction with a Non-Stationary environment.
Solving University Scheduling Problem Using Hybrid Approach
Directory of Open Access Journals (Sweden)
Aftab Ahmed Shaikh
2011-10-01
Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.
Aheuristic Algorithm for Berth Scheduling Problem in Container Ports
Institute of Scientific and Technical Information of China (English)
张海滨
2011-01-01
In this paper,the berth scheduling problem is transformed into a special two-dimensional packing problem with some constraints.A nonlinear programming model for the problem is established,and a heuristic algorithm is proposed to solve the model.Simulation
Re-scheduling in railways: the rolling stock balancing problem
G. Budai-Balke (Gabriella); G. Maróti (Gábor); R. Dekker (Rommert); D. Huisman (Dennis); L.G. Kroon (Leo)
2007-01-01
textabstractThis paper addresses the Rolling Stock Balancing Problem (RSBP). This problem arises at a passenger railway operator when the rolling stock has to be re-scheduled due to changing circumstances. These problems arise both in the planning process and during operations. The RSBP has as inpu
Solving very large vehicle scheduling problems in public mass transit
Energy Technology Data Exchange (ETDEWEB)
Loebel, A.; Groetschel, M.
1994-12-31
In public mass transit the problem of scheduling vehicles belonging to different depots such that a set of given timetabled trips is operated by exactly one vehicle arises. This Multiple-Depot-Vehicle-Scheduling-Problem (MDVSP) is a special case of a multi-commodity-flow-problem and is NP-hard. We discuss the polyhedron associated with the MDVSP, determine its dimension and give various classes of facet defining inequalities. These polyhedral results can be used in a branch and cut algorithm and have proven to be successful on very large scale real-world problems from Hamburger Hochbahn AG with up to 27 million variables.
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.
Single machine stochastic JIT scheduling problem subject to machine breakdowns
Institute of Scientific and Technical Information of China (English)
2008-01-01
In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat.The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date.For preemptive-resume,we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem,and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions.For preemptive-repeat,the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed.We replace the ESSD problem by the SSDE problem.We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times.And a dynamic programming algorithm with the pseudopolynomial time complexity is given.A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.
Single machine stochastic JIT scheduling problem subject to machine breakdowns
Institute of Scientific and Technical Information of China (English)
TANG HengYong; ZHAO ChuanLi; CHENG CongDian
2008-01-01
In this paper we research the single machine stochastic JIT scheduling problem subject to the machine breakdowns for preemptive-resume and preemptive-repeat. The objective function of the problem is the sum of squared deviations of the job-expected completion times from the due date. For preemptive-resume, we show that the optimal sequence of the SSDE problem is V-shaped with respect to expected processing times. And a dynamic programming algorithm with the pseudopolynomial time complexity is, given. We discuss the difference between the SSDE problem and the ESSD problem and show that the optimal solution of the SSDE problem is a good approximate optimal solution of the ESSD problem, and the optimal solution of the SSDE problem is an optimal solution of the ESSD problem under some conditions. For preemptive-repeat, the stochastic JIT scheduling problem has not been solved since the variances of the completion times cannot be computed. We replace the ESSD problem by the SSDE problem. We show that the optimal sequence of the SSDE problem is V-shaped with respect to the expected occupying times. And a dynamic programming algorithm with the pseudopolynomial time complexity is given. A new thought is advanced for the research of the preemptive-repeat stochastic JIT scheduling problem.
Dynamic Scheduling for Cloud Reliability using Transportation Problem
Directory of Open Access Journals (Sweden)
P. Balasubramanie
2012-01-01
Full Text Available 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 scheduling algorithm that can improve the availability and reliability in cloud environment. Approach: We propose a new algorithm using modified linear programming problem transportation based task scheduling and resource allocation for decentralized dynamic cloud computing. The Main objective is to improve the reliability of cloud computing environment by considering the resources available and itâs working status of each Cluster periodically and maximizes the profit for the cloud providers by minimizing the total cost for scheduling, allocation and execution cost and minimizing total turn-around, total waiting time and total execution time. Our proposed algorithm also utilizes task historical values such as past success rate, failure rate of task in each Cluster and previous execution time and total cost for various Clusters for each task from Task Info Container (TFC for tasks scheduling resource allocation for near future. Results: Our approach TP Scheduling (Transpotation Problem based responded for various tasks assigned by clients in poisson arrival pattern and achieved the improved reliability in dynamic decentralized cloud environment. Conclusion: With our proposed TP Scheduling algorithn we improve the Reliability of the decentralized dynamic cloud computing.
Climate variance influence on the non-stationary plankton dynamics.
Molinero, Juan Carlos; Reygondeau, Gabriel; Bonnet, Delphine
2013-08-01
We examined plankton responses to climate variance by using high temporal resolution data from 1988 to 2007 in the Western English Channel. Climate variability modified both the magnitude and length of the seasonal signal of sea surface temperature, as well as the timing and depth of the thermocline. These changes permeated the pelagic system yielding conspicuous modifications in the phenology of autotroph communities and zooplankton. The climate variance envelope, thus far little considered in climate-plankton studies, is closely coupled with the non-stationary dynamics of plankton, and sheds light on impending ecological shifts and plankton structural changes. Our study calls for the integration of the non-stationary relationship between climate and plankton in prognostic models on the productivity of marine ecosystems.
Simulation of non-stationary ground motion processes (I)
Institute of Scientific and Technical Information of China (English)
LIANG Jian-wen
2005-01-01
This paper presents a spectral representation method for simulation of non-stationary ground motion processes on the basis of Priestley's evolutionary spectral theory. Following this method, sample processes can be generated using a cosine series formula. It is shown that, these sample processes accurately reflect the prescribed characteristics of the evolutionary power spectral density function when the number of the terms in the cosine series is large enough; and the ensemble expected value and the ensemble autocorrelation function approach the corresponding target functions, respectively, as the sample size increases; and these sample processes are asymptotically normal as the number of the terms in the series tends to infinity. Finally, a few special cases of the formula are discussed, one of which is non-stationary white noise process, and other one is reduced to the formula for simulation of stationary stochastic processes.
Local polynomial Whittle estimation covering non-stationary fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank
This paper extends the local polynomial Whittle estimator of Andrews & Sun (2004) to fractionally integrated processes covering stationary and non-stationary regions. We utilize the notion of the extended discrete Fourier transform and periodogram to extend the local polynomial Whittle estimator ...... 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....
SOLVABLE CASES OF THE NO-WAIT FLOWSHOP SCHEDULING PROBLEM
VANDERVEEN, JAA; VANDAL, R
1991-01-01
The no-wait flow-shop scheduling problem (NWFSSP) with a makespan objective function is considered. As is well known, this problem is NP-hard for three or more machines. Therefore, it is interesting to consider special cases, i.e. special structured processing time matrices, that allow polynomial
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...
NON-STATIONARY STOKES FLOWS UNDER LEAK BOUNDARY CONDITIONS OF FRICTION TYPE
Institute of Scientific and Technical Information of China (English)
Hiroshi Fujita
2001-01-01
This paper is concerned with the initial value problem for non-stationary Stokes flows,under a certain non-linear boundary condition which can be called the leak boundarycondition of friction type. Theoretically, our main purpose is to show the strong solvability(i.e.,the unique existence of the L2-strong solution) of this initial value problem by meansof the non-linear semi-group theory originated with Y. Komura. The method of analysiscan be applied to other boundary or interface conditions of friction type. It should benoted that the result yields a sound basis of simulation methods for evolution problemsinvolving these conditions.
Algorithms for semi on-line multiprocessor scheduling problems
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In the classical multiprocessor scheduling problems, it is assumed that the problems are considered in off-line or on-line environment. But in practice, problems are often not really off-line or on-line but somehow in between. This means that, with respect to the on-line problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi on-line ones. The authors studied two semi on-line multiprocessor scheduling problems, in which, the total processing time of all tasks is known in advance, or all processing times lie in a given interval. They proposed approximation algorithms for minimizing the makespan and analyzed their performance guarantee. The algorithms improve the known results for 3 or more processor cases in the literature.
A Solution Methodology for the Variable-Level Scheduling Problem
1991-03-01
distribution unlimited 13. ABSTRACT (Maxtmum 200 words) This study looked at a specific scheduling problem for a Department of Defense agency. A heuristic algorithm was...the DoD problem in this research. Bala Shetty’s article, " A Heuristic Algorithm for a Network Problem with Variable Upper Bounds", also uses a...could be used, but this would undoubtably have long comrt ational times. The research, then, involving a heuristic algorithm to generate an effective
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...
Scheduling and order acceptance for the customised stochastic lot scheduling problem
van Foreest, Nicky D.; Wijngaard, Jacob; van der Vaart, Taco
2010-01-01
This paper develops and analyses several customer order acceptance policies to achieve high bottleneck utilisation for the customised stochastic lot scheduling problem (CSLSP) with large setups and strict order due dates. To compare the policies, simulation is used as the main tool, due to the compl
Grain Emergency Vehicle Scheduling Problem with Time and Demand Uncertainty
Directory of Open Access Journals (Sweden)
Jiang DongQing
2014-01-01
Full Text Available Grain transportation plays an important role in many relief and emergency supply chains. In this paper, we take the grain emergency vehicle scheduling model between multiwarehouses as the research object. Under the emergency environment, the aim of the problem is to maximize the utilization of vehicles and minimize the delay time. The randomness of the key parameters in grain emergency vehicle scheduling, such as time and demand, is determined through statistical analysis and the model is solved through robust optimization method. Besides, we apply the numerical examples for experimental analysis. We compare the robust optimization model with classic model to illustrate the differences and similarities between them. The results show that the uncertainty of both time and demand has great influence on the efficiency of grain emergency vehicle scheduling problem.
The cost of using stationary inventory policies when demand is non-stationary
Tunc, Huseyin; Kilic, Onur A.; Tarim, S. Armagan; Eksioglu, Burak
Non-stationary stochastic demands are very common in industrial settings with seasonal patterns, trends, business cycles, and limited-life items. In such cases, the optimal inventory control policies are also non-stationary. However, due to high computational complexity, non-stationary inventory
Non-stationary probabilistic characterization of drought events
Bonaccorso, Brunella; Cancelliere, Antonino
2016-04-01
Probabilistic characterization of droughts is an essential step for designing and implementing appropriate mitigation strategies. Traditionally, probabilistic characterization of droughts has been carried out assuming stationarity for the underlying hydrological series. In particular, under the stationary framework, probability distributions and moments of hydrological processes are assumed to be invariant with time. However many studies in the past decades have highlighted the presence of non-stationary patterns (such as trends or shifts) in hydrological records, leading to question the stationarity paradigm. Regardless of the causes (either anthropogenic or natural), the need arises to develop new statistical concepts and tools able to deal with such non-stationarity. In the present work, an analytical framework for deriving probabilities and return periods of droughts, assuming non-stationarity in the underlying hydrological series, is developed. In particular, exact and approximate analytical expressions for the moments and probability distributions of drought characteristics (i.e. length and accumulated deficit), are derived as a function of the non-stationary probability distribution of the hydrological process under investigation, as well as of the threshold level. Furthermore, capitalizing on previous developments suggested in the statistical and climate change literature, the concept of return period is revisited to take into account non-stationarity, as well as the multivariate nature of droughts which requires to consider different characteristics simultaneously. The derived expressions are applied to several precipitation series in Sicily Italy, exhibiting trends. Results indicate the feasibility of the proposed methodology to compute probabilities and return periods of drought characteristics in a non-stationary context.
APPLYING PARTICLE SWARM OPTIMIZATION TO JOB-SHOP SCHEDULING PROBLEM
Institute of Scientific and Technical Information of China (English)
Xia Weijun; Wu Zhiming; Zhang Wei; Yang Genke
2004-01-01
A new heuristic algorithm is proposed for the problem of finding the minimum makespan in the job-shop scheduling problem. The new algorithm is based on the principles of particle swarm optimization (PSO). PSO employs a collaborative population-based search, which is inspired by the social behavior of bird flocking. It combines local search (by self experience) and global search (by neighboring experience), possessing high search efficiency. Simulated annealing (SA) employs certain probability to avoid becoming trapped in a local optimum and the search process can be controlled by the cooling schedule. By reasonably combining these two different search algorithms, a general, fast and easily implemented hybrid optimization algorithm, named HPSO, is developed. The effectiveness and efficiency of the proposed PSO-based algorithm are demonstrated by applying it to some benchmark job-shop scheduling problems and comparing results with other algorithms in literature. Comparing results indicate that PSO-based algorithm is a viable and effective approach for the job-shop scheduling problem.
A new polynomial algorithm for a parallel identical scheduling problem
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A precedence order is defined based on the release dates of jobs'direct successors.Using the defined precedence order and Heap Sort,a new polynomial algorithm is provided which aims tO solve the parallel scheduling problem P|pj=1,Tj,outtree|∑ Cj.The new algorithm is shown to be more compact and easier to implement.
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...
Supervised and unsupervised condition monitoring of non-stationary acoustic emission signals
DEFF Research Database (Denmark)
Sigurdsson, Sigurdur; Pontoppidan, Niels Henrik; Larsen, Jan
2005-01-01
We are pursuing a system that monitors the engine condition under multiple load settings, i.e. under non-stationary operating conditions. The running speed when data acquired under simulated marine conditions (different load settings on the propeller curve) was in the range from approximately 70...... approaches perform well, which indicates that unsupervised models, modelled without faulty data, may be used for accurate condition monitoring....... condition changes across load changes. In this paper we approach this load interpolation problem with supervised and unsupervised learning, i.e. model with normal and fault examples and normal examples only, respectively. We apply non-linear methods for the learning of engine condition changes. Both...
Identification of the structure parameters using short-time non-stationary stochastic excitation
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.
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.
Application of genetic algorithm to the technological operations scheduling problem
Directory of Open Access Journals (Sweden)
Lujić, R.
2008-04-01
Full Text Available The basic enterprise task is to satisfy customer requirements: due date, price and quality. Based on experiences from engineers practice of work in Croatian enterprises it could be concluded that enterprises are not able to fulfil obligations to the customer in a way of due dates. One of the basic reasons lies in inappropriate scheduling model that has not had possibility to make plan variants. The paper shows how genetic algorithm could be successfully applied in scheduling model to solve the problem of plan variant. As a basic selection in the paper 3-tournament steady-state selection has been applied.
Non-stationary Operation Regimes of the Gas Bearings
Directory of Open Access Journals (Sweden)
Ilina Tamara Evgenevna
2014-07-01
Full Text Available This review provides of basic information on non-stationary operation regimes of the gas bearings. The causes and mechanisms of maintaining the oscillation of the rotor’s gas suspensions are discussed. A brief review of linear, nonlinear and resonant vibrational effect is given. The questions on the oscillations in the layer of gas and liquid lubrication in the bearings are elaborated. A classification of non-stationary processes in gas bearings is given. Brief information on issues such as "frequency capture", "Sommerfeld effect", "a half-speed and fraction-speed vortex", "pneumatic hammer", "consumption oscillations in nozzles". The main tasks for the gas-static bearing’s control system are formulated. The results of calculations of the reaction in gas-static rotor bearings on a single external influence. It is shown that when the external load, the impact of external forces and the gas pressure in the lubricating gap rotor motion seeks to limit discrete trajectories. Thus, the radius is changed stepwise precession and not continuously. Increasing supply pressure in the lubricating gap fluctuations can be suppressed by decreasing the diameter of the precession.
Scaling in Non-stationary time series I
Ignaccolo, M; Grigolini, P; Hamilton, P; West, B J
2003-01-01
Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non stationary and the use of techniques of analysis resting on the stationary assumption can produce a wrong information on the scaling, and so on the complexity of the process under study. Herein, we test and compare two techniques for removing the non-stationary influences from computer generated time series, consisting of the superposition of a slow signal and a random fluctuation. The former is based on the method of wavelet decomposition, and the latter is a proposal of this paper, denoted by us as step detrending technique. We focus our attention on two cases, when the slow signal is a periodic function mimicking the influence of seasons, and when it is an aperiodic signal mimicking the influence of a population change (increase or decrease). For the purpose of computational simplicity the random fluctuation is taken...
Extended precedence preservative crossover for job shop scheduling problems
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.
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...
A Heuristic Approach for International Crude Oil Transportation Scheduling Problems
Yin, Sisi; Nishi, Tatsushi; Izuno, Tsukasa
In this paper, we propose a heuristic algorithm to solve a practical ship scheduling problem for international crude oil transportation. The problem is considered as a vehicle routing problem with split deliveries. The objective of this paper is to find an optimal assignment of tankers, a sequence of visiting and loading volume simultaneously in order to minimize the total distance satisfying the capacity of tankers. A savings-based meta-heuristic algorithm with lot sizing parameters and volume assignment heuristic is developed. The proposed method is applied to solve a case study with real data. Computational results demonstrate the effectiveness of the heuristic algorithm compared with that of human operators.
Global Optimization of Nonlinear Blend-Scheduling Problems
Directory of Open Access Journals (Sweden)
Pedro A. Castillo Castillo
2017-04-01
Full Text Available The scheduling of gasoline-blending operations is an important problem in the oil refining industry. This problem not only exhibits the combinatorial nature that is intrinsic to scheduling problems, but also non-convex nonlinear behavior, due to the blending of various materials with different quality properties. In this work, a global optimization algorithm is proposed to solve a previously published continuous-time mixed-integer nonlinear scheduling model for gasoline blending. The model includes blend recipe optimization, the distribution problem, and several important operational features and constraints. The algorithm employs piecewise McCormick relaxation (PMCR and normalized multiparametric disaggregation technique (NMDT to compute estimates of the global optimum. These techniques partition the domain of one of the variables in a bilinear term and generate convex relaxations for each partition. By increasing the number of partitions and reducing the domain of the variables, the algorithm is able to refine the estimates of the global solution. The algorithm is compared to two commercial global solvers and two heuristic methods by solving four examples from the literature. Results show that the proposed global optimization algorithm performs on par with commercial solvers but is not as fast as heuristic approaches.
A canned food scheduling problem with batch due date
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.
An Indirect Genetic Algorithm for a Nurse Scheduling Problem
Aickelin, Uwe
2008-01-01
This paper describes a Genetic Algorithms approach to a manpower-scheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in handling the conflict between objectives and constraints. The approach taken here is to use an indirect coding based on permutations of the nurses, and a heuristic decoder that builds schedules from these permutations. Computational experiments based on 52 weeks of live data are used to evaluate three different decoders with varying levels of intelligence, and four well-known crossover operators. Results are further enhanced by introducing a hybrid crossover operator and by making use of simple bounds to reduce the size of the solution space. The results reveal that the proposed algorithm is able to find high quality solutions and is both faster and more flexible than a recently published Tabu Search approach.
Non-Stationary Random Response of MDOF Duffing Systems
Directory of Open Access Journals (Sweden)
J.H. Lin
2004-01-01
Full Text Available This paper presents a method to solve non-stationary random responses of nonlinear multi-degrees-of-freedom (MDOF Duffing systems subjected to evolutionary random excitations. Specific phase-lags between the excitations can also be taken into account. The power spectral density (PSD of the input excitations is not confined to simple white noise or filtered white noise, in fact it can also take more complicated forms. The MDOF nonlinear random differential equations are iteratively solved by means of the Equivalent Linearization Method (ELM combined with the Pseudo Excitation Method (PEM. This combined method is easy and efficient. Two examples are given in which this method is well justified by the Monte-Carlo numerical simulations. Although only a Duffing model is dealt with in this paper for computational simplicity, the proposed method is in fact quite general, e.g. it can also deal with nonlinear hysteretic structures that will be dealt with in a separate paper.
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...
Segmentation algorithm for non-stationary compound Poisson processes
Toth, Bence; Farmer, J Doyne
2010-01-01
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of the time series. The process is composed of consecutive patches of variable length, each patch being described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated to a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galvan, et al., Phys. Rev. Lett., 87, 168105 (2001). We show that the new algorithm outperforms the original one for regime switching compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.
Non-stationary Rayleigh-Taylor instability in supernovae ejecta
Ribeyre, X; Tikhonchuk, V T; Bouquet, S; Sanz, J; Ribeyre, Xavier; Hallo, Ludovic; Tikhonchuk, Vladimir; Bouquet, Serge; Sanz, Javier
2005-01-01
The Rayleigh-Taylor instability plays an important role in the dynamics of several astronomical objects, in particular, in supernovae (SN) evolution. In this paper we develop an analytical approach to study the stability analysis of spherical expansion of the SN ejecta by using a special transformation in the co-moving coordinate frame. We first study a non-stationary spherical expansion of a gas shell under the pressure of a central source. Then we analyze its stability with respect to a no radial, non spherically symmetric perturbation of the of the shell. We consider the case where the polytropic constant of the SN shell is $\\gamma=5/3$ and we examine the evolution of a arbitrary shell perturbation. The dispersion relation is derived. The growth rate of the perturbation is found and its temporal and spatial evolution is discussed. The stability domain depends on the ejecta shell thickness, its acceleration, and the perturbation wavelength.
Rare switching events in non-stationary systems.
Becker, Nils B; ten Wolde, Pieter Rein
2012-05-07
Physical systems with many degrees of freedom can often be understood in terms of transitions between a small number of metastable states. For time-homogeneous systems with short-term memory these transitions are fully characterized by a set of rate constants. We consider the question how to extend such a coarse-grained description to non-stationary systems and to systems with finite memory. We identify the physical regimes in which time-dependent rates are meaningful, and state microscopic expressions that can be used to measure both externally time-dependent and history-dependent rates in microscopic simulations. Our description can be used to generalize Markov state models to time-dependent Markovian or non-Markovian systems.
Scaling in non-stationary time series. (I)
Ignaccolo, M.; Allegrini, P.; Grigolini, P.; Hamilton, P.; West, B. J.
2004-05-01
Most data processing techniques, applied to biomedical and sociological time series, are only valid for random fluctuations that are stationary in time. Unfortunately, these data are often non-stationary and the use of techniques of analysis resting on the stationary assumption can produce a wrong information on the scaling, and so on the complexity of the process under study. Herein, we test and compare two techniques for removing the non-stationary influences from computer generated time series, consisting of the superposition of a slow signal and a random fluctuation. The former is based on the method of wavelet decomposition, and the latter is a proposal of this paper, denoted by us as step detrending technique. We focus our attention on two cases, when the slow signal is a periodic function mimicking the influence of seasons, and when it is an aperiodic signal mimicking the influence of a population change (increase or decrease). For the purpose of computational simplicity the random fluctuation is taken to be uncorrelated. However, the detrending techniques here illustrated work also in the case when the random component is correlated. This expectation is fully confirmed by the sociological applications made in the companion paper. We also illustrate a new procedure to assess the existence of a genuine scaling, based on the adoption of diffusion entropy, multiscaling analysis and the direct assessment of scaling. Using artificial sequences, we show that the joint use of all these techniques yield the detection of the real scaling, and that this is independent of the technique used to detrend the original signal.
Non-stationary (13)C-metabolic flux ratio analysis.
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.
The Nonpermutation Flowshop Scheduling Problem: Adjustment and Bounding Procedures
Directory of Open Access Journals (Sweden)
Anis Gharbi
2014-01-01
Full Text Available We consider the makespan minimization in a flowshop environment where the job sequence does not have to be the same for all the machines. Contrarily to the classical permutation flowshop scheduling problem, this strongly NP-hard problem received very scant attention in the literature. In this paper, some improved single-machine-based adjustment procedures are proposed, and a new two-machine-based one is introduced. Based on these adjustments, new lower and upper bounding schemes are derived. Our experimental analysis shows that the proposed procedures provide promising results.
Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems
Institute of Scientific and Technical Information of China (English)
Jin-hui Yang; Liang Sun; Heow Pueh Lee; Yun Qian; Yan-chun Liang
2008-01-01
A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki's neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.
Analytical Reduced Models for the Non-stationary Diabatic Atmospheric Boundary Layer
Momen, Mostafa; Bou-Zeid, Elie
2017-09-01
Geophysical boundary-layer flows feature complex dynamics that often evolve with time; however, most current knowledge centres on the steady-state problem. In these atmospheric and oceanic boundary layers, the pressure gradient, buoyancy, Coriolis, and frictional forces interact to determine the statistical moments of the flow. The resulting equations for the non-stationary mean variables, even when succinctly closed, remain challenging to handle mathematically. Here, we derive a simpler physical model that reduces these governing unsteady Reynolds-averaged Navier-Stokes partial differential equations into a single first-order ordinary differential equation with non-constant coefficients. The reduced model is straightforward to solve under arbitrary forcing, even when the statistical moments are non-stationary and the viscosity varies in time and space. The model is successfully validated against large-eddy simulation for, (1) time-variable pressure gradients, and (2) linearly time-variable buoyancy. The new model is shown to have a superior performance compared to the classic Blackadar solutions (and later improvements on these solutions), and it covers a much wider range of conditions.
Around and about an application of the GAMLSS package to non-stationary flood frequency analysis
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.
Artificial immune algorithm for multi-depot vehicle scheduling problems
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.
LOGISTICS SCHEDULING: ANALYSIS OF TWO-STAGE PROBLEMS
Institute of Scientific and Technical Information of China (English)
Yung-Chia CHANG; Chung-Yee LEE
2003-01-01
This paper studies the coordination effects between stages for scheduling problems where decision-making is a two-stage process. Two stages are considered as one system. The system can be a supply chain that links two stages, one stage representing a manufacturer; and the other, a distributor.It also can represent a single manufacturer, while each stage represents a different department responsible for a part of operations. A problem that jointly considers both stages in order to achieve ideal overall system performance is defined as a system problem. In practice, at times, it might not be feasible for the two stages to make coordinated decisions due to (i) the lack of channels that allow decision makers at the two stages to cooperate, and/or (ii) the optimal solution to the system problem is too difficult (or costly) to achieve.Two practical approaches are applied to solve a variant of two-stage logistic scheduling problems. The Forward Approach is defined as a solution procedure by which the first stage of the system problem is solved first, followed by the second stage. Similarly, the Backward Approach is defined as a solution procedure by which the second stage of the system problem is solved prior to solving the first stage. In each approach, two stages are solved sequentially and the solution generated is treated as a heuristic solution with respect to the corresponding system problem. When decision makers at two stages make decisions locally without considering consequences to the entire system,ineffectiveness may result - even when each stage optimally solves its own problem. The trade-off between the time complexity and the solution quality is the main concern. This paper provides the worst-case performance analysis for each approach.
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.
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...... be serviced within a given time-window by a team consisting of a driver and loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/ configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams...... annealing heuristic approach to solve the problem. Computational experiments show that the tabu search approach outperforms the simulated annealing approach, and is capable of finding good solutions....
Automated problem scheduling and reduction of synchronization delay effects
Saltz, Joel H.
1987-01-01
It is anticipated that in order to make effective use of many future high performance architectures, programs will have to exhibit at least a medium grained parallelism. A framework is presented for partitioning very sparse triangular systems of linear equations that is designed to produce favorable preformance results in a wide variety of parallel architectures. Efficient methods for solving these systems are of interest because: (1) they provide a useful model problem for use in exploring heuristics for the aggregation, mapping and scheduling of relatively fine grained computations whose data dependencies are specified by directed acrylic graphs, and (2) because such efficient methods can find direct application in the development of parallel algorithms for scientific computation. Simple expressions are derived that describe how to schedule computational work with varying degrees of granularity. The Encore Multimax was used as a hardware simulator to investigate the performance effects of using the partitioning techniques presented in shared memory architectures with varying relative synchronization costs.
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.
A Bayesian Optimisation Algorithm for the Nurse Scheduling Problem
Jingpeng, Li
2008-01-01
A Bayesian optimization algorithm for the nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurses assignment. Unlike our previous work that used Gas to implement implicit learning, the learning in the proposed algorithm is explicit, ie. Eventually, we will be able to identify and mix building blocks directly. The Bayesian optimization algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated, ie in our case, a new rule string has been obtained. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again usin...
A MULTICRITERIA PERMUTATION FLOWSHOP SCHEDULING PROBLEM WITH SETUP TIMES
Directory of Open Access Journals (Sweden)
M.Saravanan
2014-07-01
Full Text Available The permutation flow shop scheduling problem has been completely concentrated on in late decades, both from single objective and additionally from multi-objective points of view. To the best of our information, little has been carried out with respect to the multi-objective flow shop with sequence dependent setup times are acknowledged. As setup times and multi-criteria problems are significant in industry, we must concentrate on this area. We propose a simple and powerful meta-heuristic algorithm as artificial immune system for the sequence dependent setup time’s flow shop problem with several criteria. The objective functions are framed to simultaneously minimize the makespan time, tardiness time, earliness time and total completion time. The proposed approach is in conjunction with the constructive heuristic of Nawaz et al. evaluated using benchmark problems taken from Taillard and compared with the prevailing Simulated annealing approach and B-Grasp approach. Computational experiments indicate that the proposed algorithm is better than the SA approach and B-Grasp approach in all cases and can be very well applied to find better schedule.
Rak, Josef
2016-03-01
An induction heating problem can be described by a parabolic differential equation. For this equation, specific Joule looses must be computed. It can be done by solving the Fredholm Integral Equation of the second kind for the eddy current of density. When we use the Nyström method with the singularity subtraction, the computation time is rapidly reduced. This paper shows the method for finding non-stationary temperature distribution in the metal body with illustrative examples.
Non-Stationary Effects and Cross Correlations in Solar Activity
Nefedyev, Yuri; Panischev, Oleg; Demin, Sergey
2016-07-01
In this paper within the framework of the Flicker-Noise Spectroscopy (FNS) we consider the dynamic properties of the solar activity by analyzing the Zurich sunspot numbers. As is well-known astrophysics objects are the non-stationary open systems, whose evolution are the quite individual and have the alternation effects. The main difference of FNS compared to other related methods is the separation of the original signal reflecting the dynamics of solar activity into three frequency bands: system-specific "resonances" and their interferential contributions at lower frequencies, chaotic "random walk" ("irregularity-jump") components at larger frequencies, and chaotic "irregularity-spike" (inertial) components in the highest frequency range. Specific parameters corresponding to each of the bands are introduced and calculated. These irregularities as well as specific resonance frequencies are considered as the information carriers on every hierarchical level of the evolution of a complex natural system with intermittent behavior, consecutive alternation of rapid chaotic changes in the values of dynamic variables on small time intervals with small variations of the values on longer time intervals ("laminar" phases). The jump and spike irregularities are described by power spectra and difference moments (transient structural functions) of the second order. FNS allows revealing the most crucial points of the solar activity dynamics by means of "spikiness" factor. It is shown that this variable behaves as the predictor of crucial changes of the sunspot number dynamics, particularly when the number comes up to maximum value. The change of averaging interval allows revealing the non-stationary effects depending by 11-year cycle and by inside processes in a cycle. To consider the cross correlations between the different variables of solar activity we use the Zurich sunspot numbers and the sequence of corona's radiation energy. The FNS-approach allows extracting the
Cappell, M S; Spray, D C; Bennett, M V
1988-06-28
Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.
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...... transmissions cannot use the same edge in the same time period. An exact solution approach based on Dantzig-Wolfe decomposition is proposed along with several heuristics. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results...
Energy Technology Data Exchange (ETDEWEB)
Zentner, I. [IMSIA, UMR EDF-ENSTA-CNRS-CEA 9219, Université Paris-Saclay, 828 Boulevard des Maréchaux, 91762 Palaiseau Cedex (France); Ferré, G., E-mail: gregoire.ferre@ponts.org [CERMICS – Ecole des Ponts ParisTech, 6 et 8 avenue Blaise Pascal, Cité Descartes, Champs sur Marne, 77455 Marne la Vallée Cedex 2 (France); Poirion, F. [Department of Structural Dynamics and Aeroelasticity, ONERA, BP 72, 29 avenue de la Division Leclerc, 92322 Chatillon Cedex (France); Benoit, M. [Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), UMR 7342 (CNRS, Aix-Marseille Université, Ecole Centrale Marseille), 49 rue Frédéric Joliot-Curie, BP 146, 13384 Marseille Cedex 13 (France)
2016-06-01
In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio–temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).
Spectral Model of Non-Stationary, Inhomogeneous Turbulence
Bragg, Andrew D; Clark, Timothy T
2015-01-01
We compare results from a spectral model for non-stationary, inhomogeneous turbulence (Besnard et al., Theor. Comp. Fluid. Dyn., vol. 8, pp 1-35, 1996) with Direct Numerical Simulation (DNS) data of a shear-free mixing layer (SFML) (Tordella et al., Phys. Rev. E, vol. 77, 016309, 2008). The SFML is used as a test case in which the efficacy of the model closure for the physical-space transport of the fluid velocity field can be tested in a flow with inhomogeneity, without the additional complexity of mean-flow coupling. The model is able to capture certain features of the SFML quite well for intermediate to long-times, including the evolution of the mixing-layer width and turbulent kinetic energy. At short-times, and for more sensitive statistics such as the generation of the velocity field anisotropy, the model is less accurate. We present arguments, supported by the DNS data, that a significant cause of the discrepancies is the local approximation to the intrinsically non-local pressure-transport in physical...
Combinatorial particle swarm optimization for solving blocking flowshop scheduling problem
Directory of Open Access Journals (Sweden)
Mansour Eddaly
2016-10-01
Full Text Available This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO as a resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study and statistical analysis were performed to select the most adapted one for this problem. Then, the swarm behavior is tested for solving a combinatorial optimization problem such as a sequencing problem under constraints. Finally, an iterated local search algorithm based on probabilistic perturbation is sequentially introduced to the particle swarm optimization algorithm for improving the quality of solution. The computational results show that our approach is able to improve several best known solutions of the literature. In fact, 76 solutions among 120 were improved. Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements. Also, the performance of the proposed approach is evaluated according to a real-world industrial problem.
The Distributed Assembly Parallel Machine Scheduling Problem with eligibility constraints.
Directory of Open Access Journals (Sweden)
Sara Hatami
2015-01-01
Full Text Available In this paper we jointly consider realistic scheduling extensions: First we study the distributed unrelated parallel machines problems by which there is a set of identical factories with parallel machines in a production stage. Jobs have to be assigned to factories and to machines. Additionally, there is an assembly stage with a single assembly machine. Finished jobs at the manufacturing stage are assembled into final products in this second assembly stage. These two joint features are referred to as the distributed assembly parallel machine scheduling problem or DAPMSP. The objective is to minimize the makespan in the assembly stage. Due to technological constraints, machines cannot be left empty and some jobs might be processed on certain factories only. We propose a mathematical model and two high performing heuristics. The model is tested with two state-of-the-art solvers and, together with the heuristics, 2220 instances are solved in a comprehensive computational experiments. Results show that the proposed model is able to solve moderately-sized instances and one of the heuristics is fast, giving close to optimal solutions in less than half a second in the worst case.
JIT single machine scheduling problem with periodic preventive maintenance
Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani
2016-03-01
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.
Non-stationary time series modeling on caterpillars pest of palm oil for early warning system
Setiyowati, Susi; Nugraha, Rida F.; Mukhaiyar, Utriweni
2015-12-01
The oil palm production has an important role for the plantation and economic sector in Indonesia. One of the important problems in the cultivation of oil palm plantation is pests which causes damage to the quality of fruits. The caterpillar pest which feed palm tree's leaves will cause decline in quality of palm oil production. Early warning system is needed to minimize losses due to this pest. Here, we applied non-stationary time series modeling, especially the family of autoregressive models to predict the number of pests based on its historical data. We realized that there is some uniqueness of these pests data, i.e. the spike value that occur almost periodically. Through some simulations and case study, we obtain that the selection of constant factor has a significance influence to the model so that it can shoot the spikes value precisely.
A note on Tempelmeier's {\\beta}-service measure under non-stationary stochastic demand
Rossi, Roberto; Kilic, Onur A
2011-01-01
Tempelmeier (2007) considers the problem of computing replenishment cycle policy parameters under non-stationary stochastic demand and service level constraints. He analyses two possible service level measures: the minimum no stock-out probability per period ({\\alpha}-service level) and the so called "fill rate", that is the fraction of demand satisfied immediately from stock on hand ({\\beta}-service level). For each of these possible measures, he presents a mixed integer programming (MIP) model to determine the optimal replenishment cycles and corresponding order-up-to levels minimizing the expected total setup and holding costs. His approach is essentially based on imposing service level dependent lower bounds on cycle order-up-to levels. In this note, we argue that Tempelmeier's strategy, in the {\\beta}-service level case, while being an interesting option for practitioners, does not comply with the standard definition of "fill rate". By means of a simple numerical example we demonstrate that, as a consequ...
Scaling in Non-stationary Time Series II Teen Birth Phenomenon
Ignaccolo, M; Grigolini, P; Hamilton, P; West, B J
2003-01-01
This paper is devoted to the problem of statistical mechanics raised by the analysis of an issue of sociological interest: the teen birth phenomenon. It is expected that these data are characterized by correlated fluctuations, reflecting the cooperative properties of the process. However, the assessment of the anomalous scaling generated by these correlations is made difficult, and ambiguous as well, by the non-stationary nature of the data that show a clear dependence on seasonal periodicity (periodic component) and an average changing slowly in time (slow component), as well. We use the detrending techniques described in the companion paper \\cite{paper1}, to safely remove all the biases and to derive the genuine scaling of the teen birth phenomenon.
A NEW APPROACH TO JOB SHOP-SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
Ramezanali Mahdavinejad
2007-03-01
Full Text Available In this paper, single-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan i.e. total completion time , in which a simultanous presence of various kinds of ferons is allowed. The process of finding the best solution will be improved by using the suitable hybrid of priority dispatching rules. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. By solving some problems as samples (i.e. Fisher's & Thomson's problems, this algorithm is compared with the others. The results show that when the size of the problem becomes larger the deviation from lower limit increases, but its rate decreases with the size of the problems, so that it reaches to its limit.
Non-stationary background intensity and Caribbean seismic events
Valmy, Larissa; Vaillant, Jean
2014-05-01
We consider seismic risk calculation based on models with non-stationary background intensity. The aim is to improve predictive strategies in the framework of seismic risk assessment from models describing at best the seismic activity in the Caribbean arc. Appropriate statistical methods are required for analyzing the volumes of data collected. The focus is on calculating earthquakes occurrences probability and analyzing spatiotemporal evolution of these probabilities. The main modeling tool is the point process theory in order to take into account past history prior to a given date. Thus, the seismic event conditional intensity is expressed by means of the background intensity and the self exciting component. This intensity can be interpreted as the expected event rate per time and / or surface unit. The most popular intensity model in seismology is the ETAS (Epidemic Type Aftershock Sequence) model introduced and then generalized by Ogata [2, 3]. We extended this model and performed a comparison of different probability density functions for the triggered event times [4]. We illustrate our model by considering the CDSA (Centre de Données Sismiques des Antilles) catalog [1] which contains more than 7000 seismic events occurred in the Lesser Antilles arc. Statistical tools for testing the background intensity stationarity and for dynamical segmentation are presented. [1] Bengoubou-Valérius M., Bazin S., Bertil D., Beauducel F. and Bosson A. (2008). CDSA: a new seismological data center for the French Lesser Antilles, Seismol. Res. Lett., 79 (1), 90-102. [2] Ogata Y. (1998). Space-time point-process models for earthquake occurrences, Annals of the Institute of Statistical Mathematics, 50 (2), 379-402. [3] Ogata, Y. (2011). Significant improvements of the space-time ETAS model for forecasting of accurate baseline seismicity, Earth, Planets and Space, 63 (3), 217-229. [4] Valmy L. and Vaillant J. (2013). Statistical models in seismology: Lesser Antilles arc case
Auto-Regressive Models of Non-Stationary Time Series with Finite Length
Institute of Scientific and Technical Information of China (English)
FEI Wanchun; BAI Lun
2005-01-01
To analyze and simulate non-stationary time series with finite length, the statistical characteristics and auto-regressive (AR) models of non-stationary time series with finite length are discussed and studied. A new AR model called the time varying parameter AR model is proposed for solution of non-stationary time series with finite length. The auto-covariances of time series simulated by means of several AR models are analyzed. The result shows that the new AR model can be used to simulate and generate a new time series with the auto-covariance same as the original time series. The size curves of cocoon filaments regarded as non-stationary time series with finite length are experimentally simulated. The simulation results are significantly better than those obtained so far, and illustrate the availability of the time varying parameter AR model. The results are useful for analyzing and simulating non-stationary time series with finite length.
Approximation for a scheduling problem with application in wireless networks
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
A network of many sensors and a base station that are deployed over a region is considered.Each sensor has a transmission range,an interference range and a carrier sensing range,which are r,αr and βr,respectively.In this paper,we study the minimum latency conflict-aware many-to-one data aggregation scheduling problem:Given locations of sensors along with a base station,a subset of all sensors,and parameters r,α and β,to find a schedule in which the data of each sensor in the subset can be transmitted to the base station with no conflicts,such that the latency is minimized.We designe an algorithm based on maximal independent sets,which has a latency bound of(a+19b)R + Δb-a + 5 time slots,where a and b are two constant integers relying on α and β,Δ is the maximum degree of network topology,and R is the trivial lower bound of latency.Here Δ contributes to an additive factor instead of a multiplicative one,thus our algorithm is nearly a constant(a+19b)-ratio.
Nurse Scheduling System based on Dynamic Weighted Maximal Constraint Satisfaction Problem
Hattori, Hiromitsu; Isomura, Atsushi; Ito, Takayuki; Ozono, Tadachika; Shintani, Toramatsu
Scheduling has been an important research field in Artificial Intelligence. Because typical scheduling problems could be modeled as a Constraint Satisfaction Problem(CSP), several constraint satisfaction techniques have been proposed. In order to handle the different levels of importance of the constraints, solving a problem as a Weighted Maximal Constraint Satisfaction Problem(W-MaxCSP) is an promising approach. However, there exists the case where unexpected events are added and some sudden changes are required, i.e., the case with dynamic changes in scheduling problems. In this paper, we describe such dynamic scheduling problem as a Dynamic Weighted Maximal Constraint Satisfaction Problem(DW-MaxCSP) in which constraints would changes dynamically. Generally, it is undesirable to determine vastly modified schedule even if re-scheduling is needed. A new schedule should be close to the current one as much as possible. In order to obtain stable solutions, we propose the methodology to maintain portions of the current schedule using the provisional soft constraints, which explicitly penalize the changes from the current schedule. We have experimentally confirmed the efficacy of re-scheduling based on our method with provisional constraints. In this paper, we construct the nurse scheduling system for applying the proposed scheduling method.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem
2015-01-01
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuri...
MODIFIED BOTTLENECK-BASED PROCEDURE FOR LARGE-SCALE FLOW-SHOP SCHEDULING PROBLEMS WITH BOTTLENECK
Institute of Scientific and Technical Information of China (English)
ZUO Yan; GU Hanyu; XI Yugeng
2006-01-01
A new bottleneck-based heuristic for large-scale flow-shop scheduling problems with a bottleneck is proposed, which is simpler but more tailored than the shifting bottleneck (SB)procedure. In this algorithm, a schedule for the bottleneck machine is first constructed optimally and then the non-bottleneck machines are scheduled around the bottleneck schedule by some effective dispatching rules. Computational results show that the modified bottleneck-based procedure can achieve a tradeoff between solution quality and computational time comparing with SB procedure for medium-size problems. Furthermore it can obtain a good solution in quite short time for large-scale scheduling problems.
A Hybrid Bacterial Foraging Algorithm For Solving Job Shop Scheduling Problems
Narendhar, S.; T Amudha
2012-01-01
Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by proposed Hybrid Bacterial Foraging Optimization algorithms are much better when compared with the solution...
An Analysis of Robust Workforce Scheduling Models for a Nurse Rostering Problem
2007-03-01
12 Moz and Pato ...problem and the nurse rerostering problem. The nurse rostering problem has received much attention in the staff scheduling literature (Moz and Pato , 2007...Most recently, Moz and Pato (2007) developed constructive heuristics and genetic algorithms to re-roster a schedule following a disruption. Their use
A Class of Single Machine Scheduling Problems with Variable Processing Time
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, single machine scheduling problems with variableprocessing time are raised. The criterions of the problem considered are minimizing scheduling length of all jobs, flow time and number of tardy jobs and so on. The complexity of the problem is determined.
Performance comparison of some evolutionary algorithms on job shop scheduling problems
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.
Rolling optimization algorithm based on collision window for single machine scheduling problem
Institute of Scientific and Technical Information of China (English)
Wang Changjun; Xi Yugeng
2005-01-01
Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.
A frequency measurement algorithm for non-stationary signals by using wavelet transform
Seo, Seong-Heon; Oh, Dong Keun
2016-11-01
Scalogram is widely used to measure instantaneous frequencies of non-stationary signals. However, the basic property of the scalogram is observed only for stationary sinusoidal functions. A property of the scalogram for non-stationary signal is analytically derived in this paper. Based on the property, a new frequency measurement algorithm is proposed. In addition, a filter that can separate two similar frequency signals is developed based on the wavelet transform.
Simulation of inhomogeneous, non-stationary and non-Gaussian turbulent winds
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose
2007-01-01
Turbulence time series are needed for wind turbine load simulation. The multivariate Fourier simulation method often used for this purpose is extended for inhomogeneous and non-stationary processes of general probability distribution. This includes optional conditional simulation matching simulated...... series to field measurements at selected points. A probability model for the application of turbine wind loads is discussed, and finally the technique for non-stationary processes is illustrated by turbulence simulation during a front passage....
Research on remanufacturing scheduling problem based on critical chain management
Cui, Y.; Guan, Z.; He, C.; Yue, L.
2017-06-01
Remanufacturing is the recycling process of waste products as “as good as new products”, compared with materials recycling, remanufacturing represents a higher form of recycling. The typical structure of remanufacturing system consists of three parts: disassembly workshop, remanufacturing workshop and assembly workshop. However, the management of production planning and control activities can differ greatly from management activities in traditional manufacturing. Scheduling in a remanufacturing environment is more complex and the scheduler must deal with more uncertainty than in a traditional manufacturing environment. In order to properly schedule in a remanufacturing environment the schedule must be able to cope with several complicating factors which increase variability. This paper introduced and discussed seven complicating characteristics that require significant changes in production planning and control activities, in order to provide a new method for remanufacturing production scheduling system.
Extracting stationary segments from non-stationary synthetic and cardiac signals
Rodríguez, María. G.; Ledezma, Carlos A.; Perpiñán, Gilberto; Wong, Sara; Altuve, Miguel
2015-01-01
Physiological signals are commonly the result of complex interactions between systems and organs, these interactions lead to signals that exhibit a non-stationary behaviour. For cardiac signals, non-stationary heart rate variability (HRV) may produce misinterpretations. A previous work proposed to divide a non-stationary signal into stationary segments by looking for changes in the signal's properties related to changes in the mean of the signal. In this paper, we extract stationary segments from non-stationary synthetic and cardiac signals. For synthetic signals with different signal-to-noise ratio levels, we detect the beginning and end of the stationary segments and the result is compared to the known values of the occurrence of these events. For cardiac signals, RR interval (cardiac cycle length) time series, obtained from electrocardiographic records during stress tests for two populations (diabetic patients with cardiovascular autonomic neuropathy and control subjects), were divided into stationary segments. Results on synthetic signals reveal that the non-stationary sequence is divided into more stationary segments than needed. Additionally, due to HRV reduction and exercise intolerance reported on diabetic cardiovascular autonomic neuropathy patients, non-stationary RR interval sequences from these subjects can be divided into longer stationary segments compared to the control group.
Can we identify non-stationary dynamics of trial-to-trial variability?
Directory of Open Access Journals (Sweden)
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
Modelling and prediction of non-stationary optical turbulence behaviour
Doelman, Niek; Osborn, James
2016-07-01
There is a strong need to model the temporal fluctuations in turbulence parameters, for instance for scheduling, simulation and prediction purposes. This paper aims at modelling the dynamic behaviour of the turbulence coherence length r0, utilising measurement data from the Stereo-SCIDAR instrument installed at the Isaac Newton Telescope at La Palma. Based on an estimate of the power spectral density function, a low order stochastic model to capture the temporal variability of r0 is proposed. The impact of this type of stochastic model on the prediction of the coherence length behaviour is shown.
Robust Nonlinear Causality Analysis of Non-Stationary Multivariate Physiological Time Series.
Schaeck, Tim; Muma, Michael; Feng, Mengling; Guan, Cuntai; Zoubir, Abdelhak
2017-05-26
An important research area in biomedical signal processing is that of quantifying the relationship between simultaneously observed time series and to reveal interactions between the signals. Since biomedical signals are potentially non-stationary and the measurements may contain outliers and artifacts, we introduce a robust time-varying generalized partial directed coherence (rTV-gPDC) function. The proposed method, which is based on a robust estimator of the timevarying autoregressive (TVAR) parameters, is capable of revealing directed interactions between signals. By definition, the rTV-gPDC only displays the linear relationships between the signals. We therefore suggest to approximate the residuals of the TVAR process, which potentially carry information about the nonlinear causality by a piece-wise linear time-varying moving-average (TVMA) model. The performance of the proposed method is assessed via extensive simulations. To illustrate the method's applicability to real-world problems, it is applied to a neurophysiological study that involves intracranial pressure (ICP), arterial blood pressure (ABP), and brain tissue oxygenation level (PtiO2) measurements. The rTV-gPDC reveals causal patterns that are in accordance with expected cardiosudoral meachanisms and potentially provides new insights regarding traumatic brain injuries (TBI). The rTV-gPDC is not restricted to the above problem but can be useful in revealing interactions in a broad range of applications.
Stochastic approach to the numerical solution of the non-stationary Parker's transport equation
Wawrzynczak, A; Gil, A
2015-01-01
We present the newly developed stochastic model of the galactic cosmic ray (GCR) particles transport in the heliosphere. Mathematically Parker transport equation (PTE) describing non-stationary transport of charged particles in the turbulent medium is the Fokker-Planck type. It is the second order parabolic time-dependent 4-dimensional (3 spatial coordinates and particles energy/rigidity) partial differential equation. It is worth to mention that, if we assume the stationary case it remains as the 3-D parabolic type problem with respect to the particles rigidity R. If we fix the energy it still remains as the 3-D parabolic type problem with respect to time. The proposed method of numerical solution is based on the solution of the system of stochastic differential equations (SDEs) being equivalent to the Parker's transport equation. We present the method of deriving from PTE the equivalent SDEs in the heliocentric spherical coordinate system for the backward approach. The obtained stochastic model of the Forbu...
Stochastic approach to the numerical solution of the non-stationary Parker's transport equation
Wawrzynczak, A.; Modzelewska, R.; Gil, A.
2015-01-01
We present the newly developed stochastic model of the galactic cosmic ray (GCR) particles transport in the heliosphere. Mathematically Parker transport equation (PTE) describing non-stationary transport of charged particles in the turbulent medium is the Fokker-Planck type. It is the second order parabolic time-dependent 4-dimensional (3 spatial coordinates and particles energy/rigidity) partial differential equation. It is worth to mention that, if we assume the stationary case it remains as the 3-D parabolic type problem with respect to the particles rigidity R. If we fix the energy/rigidity it still remains as the 3-D parabolic type problem with respect to time. The proposed method of numerical solution is based on the solution of the system of stochastic differential equations (SDEs) being equivalent to the Parker's transport equation. We present the method of deriving from PTE the equivalent SDEs in the heliocentric spherical coordinate system for the backward approach. The advantages and disadvantages of the forward and the backward solution of the PTE are discussed. The obtained stochastic model of the Forbush decrease of the GCR intensity is in an agreement with the experimental data.
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.
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.
The Simultaneous Vehicle Scheduling and Passenger Service Problem
DEFF Research Database (Denmark)
Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.
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...... by the express-bus network in the Greater Copenhagen Area. The results are encouraging and indicate a potential decrease of passenger waiting times in the network of 10-20%, with the vehicle scheduling costs remaining largely unaffected....
Comparison of heuristic approaches for the multiple depot vehicle scheduling problem
A.S. Pepin; G. Desaulniers (Guy); A. Hertz (Alain); D. Huisman (Dennis)
2006-01-01
textabstractGiven a set of timetabled tasks, the multi-depot vehicle scheduling problem is a well-known problem that consists of determining least-cost schedules for vehicles assigned to several depots such that each task is accomplished exactly once by a vehicle. In this paper, we propose to compar
Polynomial-time approximation schemes for scheduling problems with time lags
X. Zhang (Xiandong); S.L. van de Velde (Steef)
2010-01-01
textabstractWe identify two classes of machine scheduling problems with time lags that possess Polynomial-Time Approximation Schemes (PTASs). These classes together, one for minimizing makespan and one for minimizing total completion time, include many well-studied time lag scheduling problems. The
Seismic response of structures: from non-stationary to non-linear effects
Carlo Ponzo, Felice; Ditommaso, Rocco; Mucciarelli, Marco; Smith, Tobias
2013-04-01
The need for an effective seismic protection of buildings, and all the problems related to their management and maintenance over time, have led to a growing interest associated to develop of new integrated techniques for structural health monitoring and for damage detection and location during both ambient vibration and seismic events. It is well known that the occurrence of damage on any kind of structure is able to modify its dynamic characteristics. Indeed, the main parameters affected by the changes in stiffness characteristics are: periods of vibration, mode shapes and all the related equivalent viscous damping factors. With the aim to evaluate structural dynamic characteristics, their variation over time and after earthquakes, several Non Destructive Evaluation (NDE) methods have been proposed in the last years. Most of these are based on simplified relationship that provide the maximum inter-story drift evaluated combining structural variations in terms of: peak ground acceleration and/or structural eigenfrequencies and/or equivalent viscous damping factors related the main modes of the monitored structure. The NDE methods can be classified into four different levels. The progress of the level increases the quality and the number of the information. The most popular are certainly Level I methods being simple in implementation and economic in management. These kinds of methods are mainly based on the fast variation (less than 1 minute) of the structural fundamental frequency and the related variation of the equivalent viscous damping factor. Generally, it is possible to distinguish two types of variations: the long term variations, which may also be linked to external factors (temperature change, water content in the foundation soils, etc.) and short period variations (for example, due to seismic events), where apparent frequencies variations could occurred due to non-stationary phenomena (particular combination of input and structural response). In these
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA...
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...
Determination of hydraulic fracture parameters using a non-stationary fluid injection
Valov, A. V.; Golovin, S. V.
2016-06-01
In this paper, one provides a theoretical justification of the possibility of hydraulic fracture parameters determination by using a non-stationary fluid injection. It is assumed that the fluid is pumped into the fractured well with the time-periodic flow rate. It is shown that there is a phase shift between waves of fluid pressure and velocity. For the modelling purposes, the length and width of the fracture are assumed to be fixed. In the case of infinite fracture, one constructs an exact solution that ensures analytical determination of the phase shift in terms of the physical parameters of the problem. In the numerical calculation, the phase shift between pressure and velocity waves is found for a finite fracture. It is shown that the value of the phase shift depends on the physical parameters and on the fracture geometry. This makes it possible to determine parameters of hydraulic fracture, in particular its length, by the experimental measurement of the time shift and comparison with the numerical solution.
An Improved Shuffled Frog-Leaping Algorithm for Flexible Job Shop Scheduling Problem
Directory of Open Access Journals (Sweden)
Kong Lu
2015-02-01
Full Text Available The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the proposed algorithm has a powerful search capability in solving the flexible job shop scheduling problem compared with other heuristic algorithms, such as the genetic algorithm, tabu search and ant colony optimization. Moreover, the results also show that the improved strategies could improve the performance of the algorithm effectively.
An Optimization Model for Scheduling Problems with Two-Dimensional Spatial Resource Constraint
Garcia, Christopher; Rabadi, Ghaith
2010-01-01
Traditional scheduling problems involve determining temporal assignments for a set of jobs in order to optimize some objective. Some scheduling problems also require the use of limited resources, which adds another dimension of complexity. In this paper we introduce a spatial resource-constrained scheduling problem that can arise in assembly, warehousing, cross-docking, inventory management, and other areas of logistics and supply chain management. This scheduling problem involves a twodimensional rectangular area as a limited resource. Each job, in addition to having temporal requirements, has a width and a height and utilizes a certain amount of space inside the area. We propose an optimization model for scheduling the jobs while respecting all temporal and spatial constraints.
Single-Machine Group Scheduling Problems with Deterioration to Minimize the Sum of Completion Times
Directory of Open Access Journals (Sweden)
Yong He
2012-01-01
Full Text Available We consider two single-machine group scheduling problems with deteriorating group setup and job processing times. That is, the job processing times and group setup times are linearly increasing (or decreasing functions of their starting times. Jobs in each group have the same deteriorating rate. The objective of scheduling problems is to minimize the sum of completion times. We show that the sum of completion times minimization problems remains polynomially solvable under the agreeable conditions.
An integrated approach for modeling and solving the scheduling problem of container handling systems
Institute of Scientific and Technical Information of China (English)
CHEN Lu; XI Li-feng; CAI Jian-guo; BOSTEL Nathalie; DEJAX Pierre
2006-01-01
An integrated model is presented to schedule the container handling system. The objective is to improve the cooperation between different types of equipments, and to increase the productivity of the terminal. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence constraint, setup times and blocking (HFSS-B). A tabu search algorithm is proposed to solve this problem. The quality and efficiency of the proposed algorithm is analyzed from the computational point of view.
The Study of a New Method for Forecasting Non-stationary Series
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A new method for forecasting non-stationary series is developed. Its steps are as follows: Step 1. Data delaminating. Non-stationary series is delaminated into several multi-scale steady data layers and one trend layer. Step 2. Modeling and forecasting each stationary data layer. Step 3. Imitating trend layer using polynomial. Step 4. Combining the forecasting layers and imitating layer into one series. The EMD (Empirical Mode Decomposition) method suitable to process non-stationary series is selected to delaminate data, while ARMA (Auto Regressive Moving Average) model is employed to model and forecast stationary data layer and least square error method for trend layer regression. Aiming at forecasting length, forecasting orientation and selective method, experiments are performed for SAR (Synthetic Aperture Radar) images. Finally, an example is provided, in which the whole SAR image is restored via the method proposed by this paper.
Quantum radiation of non-stationary Kerr-Newman-de Sitter black hole
Institute of Scientific and Technical Information of China (English)
Jiang Qing-Quan; Yang Shu-Zheng; Li Hui-Ling
2005-01-01
By introducing a new tortoise coordinate transformation, we investigate the quantum thermal and non-thermal radiations of a non-stationary Kerr-Newman-de Sitter black hole. The accurate location and radiate temperature of the event horizon as well as the maximum energy of the non-thermal radiation are derived. It is shown that the radiate temperature and the maximum energy are related to not only the evaporation rate, but also the shape of the event horizon, moreover the maximum energy depends on the electromagnetic potential. Finally, we use the results to reduce the non-stationary Kerr-Newman black hole, the non-stationary Kerr black hole, the stationary Kerr-Newman-de Sitter black hole, and the static Schwarzshild black hole.
Non-stationary drying of ceramic-like materials controlled through acoustic emission method
Kowalski, Stefan Jan; Szadzińska, Justyna
2012-12-01
This paper presents results of convective drying of ceramic-like materials in non-stationary conditions. The effect of periodically changing drying parameters at different frequencies and amplitudes on material quality has been investigated. During drying tests the destruction of the material was controlled trough the acoustic emission method and monitored with a digital camera. The experiments were carried out on cylindrically shaped samples made of KOC kaolin clay. The non-stationary drying consisted in periodical changes of the drying medium temperature and humidity. It has been found that a properly arranged methodology of non-stationary drying positively affects the product quality, mainly when drying is carried on with periodical changes of air humidity and to lesser extent with periodical changes of air temperature.
Compounding approach for univariate time series with non-stationary variances
Schäfer, Rudi; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich
2015-01-01
A defining feature of non-stationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent parameters. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here we consider two concrete, but diverse examples of such non-stationary systems, the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end we have to estimate the parameter distribution for univariate time series in a highly non-stationary situation.
He, Fei; Wei, Hua-Liang; Billings, Stephen A.
2015-08-01
This paper introduces a new approach for nonlinear and non-stationary (time-varying) system identification based on time-varying nonlinear autoregressive moving average with exogenous variable (TV-NARMAX) models. The challenging model structure selection and parameter tracking problems are solved by combining a multiwavelet basis function expansion of the time-varying parameters with an orthogonal least squares algorithm. Numerical examples demonstrate that the proposed approach can track rapid time-varying effects in nonlinear systems more accurately than the standard recursive algorithms. Based on the identified time domain model, a new frequency domain analysis approach is introduced based on a time-varying generalised frequency response function (TV-GFRF) concept, which enables the analysis of nonlinear, non-stationary systems in the frequency domain. Features in the TV-GFRFs which depend on the TV-NARMAX model structure and time-varying parameters are investigated. It is shown that the high-dimensional frequency features can be visualised in a low-dimensional time-frequency space.
Ordinal scheduling problem and its asymptotically optimal algorithms on parallel machine system
Institute of Scientific and Technical Information of China (English)
TAN Zhiyi; HE Yong
2004-01-01
Focusing on the ordinal scheduling problem on a parallel machine system, we discuss the background of ordinal scheduling and the motivation of ordinal algorithms. In addition, for the ordinal scheduling problem on identical parallel machines with the objective to maximize the minimum machine load, we then give two asymptotically optimal algorithm classes which have worst-case ratios very close to the upper bound of the problem for any given m. These results greatly improve the results proposed by He Yong and Tan Zhiyi in 2002.
An evolutionary approach for solving the job shop scheduling problem in a service industry
Directory of Open Access Journals (Sweden)
Milad Yousefi
2015-03-01
Full Text Available In this paper, an evolutionary-based approach based on the discrete particle swarm optimization (DPSO algorithm is developed for finding the optimum schedule of a registration problem in a university. Minimizing the makespan, which is the total length of the schedule, in a real-world case study is considered as the target function. Since the selected case study has the characteristics of job shop scheduling problem (JSSP, it is categorized as a NP-hard problem which makes it difficult to be solved by conventional mathematical approaches in relatively short computation time.
Probabilistic blind deconvolution of non-stationary sources
DEFF Research Database (Denmark)
Olsson, Rasmus Kongsgaard; Hansen, Lars Kai
2004-01-01
We solve a class of blind signal separation problems using a constrained linear Gaussian model. The observed signal is modelled by a convolutive mixture of colored noise signals with additive white noise. We derive a time-domain EM algorithm `KaBSS' which estimates the source signals, the associa......We solve a class of blind signal separation problems using a constrained linear Gaussian model. The observed signal is modelled by a convolutive mixture of colored noise signals with additive white noise. We derive a time-domain EM algorithm `KaBSS' which estimates the source signals......, the associated second-order statistics, the mixing filters and the observation noise covariance matrix. KaBSS invokes the Kalman smoother in the E-step to infer the posterior probability of the sources, and one-step lower bound optimization of the mixing filters and noise covariance in the M-step. In line...... with (Parra and Spence, 2000) the source signals are assumed time variant in order to constrain the solution sufficiently. Experimental results are shown for mixtures of speech signals....
The problem of scheduling for the linear section of a single-track railway
Akimova, Elena N.; Gainanov, Damir N.; Golubev, Oleg A.; Kolmogortsev, Ilya D.; Konygin, Anton V.
2016-06-01
The paper is devoted to the problem of scheduling for the linear section of a single-track railway: how to organize the flow in both directions in the most efficient way. In this paper, the authors propose an algorithm for scheduling, examine the properties of this algorithm and perform the computational experiments.
A New Algorithm for Resource Constraint Project Scheduling Problem Based on Multi-Agent Systems
Institute of Scientific and Technical Information of China (English)
何曙光; 齐二石; 李钢
2003-01-01
The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocation decision involved in RCPSP has also been developed. And this algorithm can be used in the multi-project scheduling field as well.Finally, an illustration is given.
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 schedul...
Benbouzid-Sitayeb, Fatima; Ammi, Ismaïl; Varnier, Christophe; Zerhouni, Noureddine
2008-01-01
International audience; In this paper, an integrated ACO approach to solve joint production and preventive maintenance scheduling problem in permutation flowshops is considered. A newly developed antcolony algorithm is proposed and analyzed for solving this problem, based on a common representation of production and maintenance data, to obtain a joint schedule that is, subsequently, improved by a new local search procedure. The goal is to optimize a common objective function which takes into ...
Exact methods for time constrained routing and related scheduling problems
DEFF Research Database (Denmark)
Kohl, Niklas
1995-01-01
real difference is how the coordinating master problem - a concave non-differentiable maximization problem - is solved. We show how the constrained shortest path problem can be solved efficiently, and present a number of different strategies for solving the master problem. The lower bound obtainable...
Multi-agent Optimization Design for Multi-resource Job Shop Scheduling Problems
Xue, Fan; Fan, Wei
As a practical generalization of the job shop scheduling problem, multi-resource job shop scheduling problem (MRJSSP) is discussed in this paper. In this problem, operations may be processed by a type of resources and jobs have individual deadlines. How to design and optimize this problem with DSAFO, a novel multi-agent algorithm, is introduced in detail by a case study, including problem analysis, agent role specification, and parameter selection. Experimental results show the effectiveness and efficiency of designing and optimizing MRJSSPs with multi-agent.
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.
Polynomial-time approximation schemes for scheduling problems with time lags
Zhang, Xiandong; Velde, Steef
2010-01-01
textabstractWe identify two classes of machine scheduling problems with time lags that possess Polynomial-Time Approximation Schemes (PTASs). These classes together, one for minimizing makespan and one for minimizing total completion time, include many well-studied time lag scheduling problems. The running times of these approximation schemes are polynomial in the number of jobs, but exponential in the number of machines and the ratio between the largest time lag and the smallest positive ope...
A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem
2010-01-01
A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific p...
Solving scheduling tournament problems using a new version of CLONALG
Pérez-Cáceres, Leslie; Riff, María Cristina
2015-01-01
The travelling tournament problem (TTP) is an important and well-known problem within the collective sports research community. The problem is NP-hard which makes difficult finding quality solution in short amount of time. Recently a new kind of TTP has been proposed 'The Relaxed Travelling Tournament Problem'. This version of the problem allows teams to have some days off during the tournament. In this paper, we propose an immune algorithm that is able to solve both problem versions. The algorithm uses moves which are based on the team home/away patterns. One of these moves has been specially designed for the relaxed travel tournament instances. We have tested the algorithm using well-known problem benchmarks and the results obtained are very encouraging.
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.
Modelling non-stationary dynamic gene regulatory processes with the BGM model
Grzegorczyk, Marco; Husmeier, Dirk; Rahnenfuehrer, Joerg
2011-01-01
Recently, a Bayesian network model for inferring non-stationary regulatory processes from gene expression time series has been proposed. The Bayesian Gaussian Mixture (BGM) Bayesian network model divides the data into disjunct compartments (data subsets) by a free allocation model, and infers networ
Effect of non-stationary climate on infectious gastroenteritis transmission in Japan
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.
Effect of non-stationary climate on infectious gastroenteritis transmission in Japan.
Onozuka, Daisuke
2014-06-03
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.
On the measurement of the thermal conductivity of liouids by a non-stationary method
Held, E.F.M. van der; Hardebol, J.; Kalshoven, J.
1953-01-01
In 1949 in this journal 1) a paper appeared dealing with a non-stationary method for measuring the thermal conductivity of liquids. This method, indicated first by Stålhane and Pyk 2), was based upon the temperature rise at a certain distance from an electrically heated wire, producing a constant he
An investigation of setup instability in non-stationary stochastic inventory systems
Kilic, Onur A.; Tarim, S. Armagan
In stochastic inventory systems unfolding uncertainties in demand lead to the revision of earlier replenishment plans which in turn results in an instability or so-called system nervousness. In this paper, we provide the grounds for measuring system nervousness in non-stationary demand environments,
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...
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...
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...
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 tim...
Exact methods for time constrained routing and related scheduling problems
DEFF Research Database (Denmark)
Kohl, Niklas
1995-01-01
This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set of custo......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...
Climate change and non-stationary flood risk for the Upper Truckee River Basin
Directory of Open Access Journals (Sweden)
L. E. Condon
2014-05-01
Full Text Available Future flood frequency for the Upper Truckee River Basin (UTRB is assessed using non-stationary extreme value models and design life risk methodology. Historical floods are simulated at two UTRB gauge locations, Farad and Reno using the Variable Infiltration Capacity (VIC model and non-stationary Generalized Extreme Value (GEV models. The non-stationary GEV models are fit to the cool season (November–April monthly maximum flows using historical monthly precipitation totals and average temperature. Future cool season flood distributions are subsequently calculated using downscaled projections of precipitation and temperature from the Coupled Model Intercomparison Project Phase-5 (CMIP-5 archive. The resulting exceedance probabilities are combined into a single risk metric using recent developments in design life risk methodologies. This paper provides the first end-to-end analysis using non-stationary GEV methods coupled with contemporary downscaled climate projections to demonstrate how the risk profile of existing infrastructure evolves with time over its design life. Results show that flood risk increases significantly over the analysis period (from 1950 through 2099. This highlights the potential to underestimate flood risk using traditional methodologies that do not account for time varying risk. Although model parameters, for the non-stationary method are sensitive to small changes in input parameters, analysis shows that the changes in risk over time are robust. Overall, flood risk at both locations (Farad and Reno is projected to increase 10–20% between the historical period 1950–1999 and the future period 2000–2050 and 30–50% between the same historical period and 2050–2099.
Agilan, V.; Umamahesh, N. V.
2017-03-01
Present infrastructure design is primarily based on rainfall Intensity-Duration-Frequency (IDF) curves with so-called stationary assumption. However, in recent years, the extreme precipitation events are increasing due to global climate change and creating non-stationarity in the series. Based on recent theoretical developments in the Extreme Value Theory (EVT), recent studies proposed a methodology for developing non-stationary rainfall IDF curve by incorporating trend in the parameters of the Generalized Extreme Value (GEV) distribution using Time covariate. But, the covariate Time may not be the best covariate and it is important to analyze all possible covariates and find the best covariate to model non-stationarity. In this study, five physical processes, namely, urbanization, local temperature changes, global warming, El Niño-Southern Oscillation (ENSO) cycle and Indian Ocean Dipole (IOD) are used as covariates. Based on these five covariates and their possible combinations, sixty-two non-stationary GEV models are constructed. In addition, two non-stationary GEV models based on Time covariate and one stationary GEV model are also constructed. The best model for each duration rainfall series is chosen based on the corrected Akaike Information Criterion (AICc). From the findings of this study, it is observed that the local processes (i.e., Urbanization, local temperature changes) are the best covariate for short duration rainfall and global processes (i.e., Global warming, ENSO cycle and IOD) are the best covariate for the long duration rainfall of the Hyderabad city, India. Furthermore, the covariate Time is never qualified as the best covariate. In addition, the identified best covariates are further used to develop non-stationary rainfall IDF curves of the Hyderabad city. The proposed methodology can be applied to other situations to develop the non-stationary IDF curves based on the best covariate.
Multi-trip vehicle routing and scheduling problem with time window in real life
Sze, San-Nah; Chiew, Kang-Leng; Sze, Jeeu-Fong
2012-09-01
This paper studies a manpower scheduling problem with multiple maintenance operations and vehicle routing considerations. Service teams located at a common service centre are required to travel to different customer sites. All customers must be served within given time window, which are known in advance. The scheduling process must take into consideration complex constraints such as a meal break during the team's shift, multiple travelling trips, synchronisation of service teams and working shifts. The main objective of this study is to develop a heuristic that can generate high quality solution in short time for large problem instances. A Two-stage Scheduling Heuristic is developed for different variants of the problem. Empirical results show that the proposed solution performs effectively and efficiently. In addition, our proposed approximation algorithm is very flexible and can be easily adapted to different scheduling environments and operational requirements.
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.
Directory of Open Access Journals (Sweden)
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.
An Iterative Layered Tabu Search Algorithm for Complex Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
LIUMin; DONGMingyu; WUCheng
2005-01-01
In this paper, aiming at the complex characteristics that there exist two interrelated decision processes: job-assignment decision and job-sequencing decision in the complex job shop scheduling problem with parallel machines and technical constraints, we propose an Iterative layered tabu search algorithm (ILTSA), which combines the iterative and layered mechanism with tabu search algorithm. In ILTSA, we define the notation of the optimization layer including the job-assignment optimization layer and the job-sequencing optimization layer which correspond to the above two interrelated decision processes respectively. On the basis, we use the corresponding tabu search algorithms in different optimization layers and switch iteratively the above two tabu search algorithms between the two optimization layers to improve the performance of the scheduling algorithm effectively. In the above two TS algorithms, the measuring functions are the objective of the whole scheduling problem. At last, we make numerical computations for different scale scheduling problems of minimizing the makespan and minimizing the total number of tardy jobs respectively, and numerical computational results show that ILTSA is very efficient and suitable for solving larger scale job shop scheduling problem with parallel machines and technical constraints. Also, we apply successfully ILTSA to a practical complex job shop scheduling problem with parallel machines and technical constraints in one of the largest cotton colored weaving enterprises in China.
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
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.......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...
Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems
Directory of Open Access Journals (Sweden)
Z. Ismail
2009-01-01
Full Text Available Problem statement: Southern Waste Management environment (SWM environment is a company responsible for the collection and disposal of solid waste for the city of Johor Bahru, a city with over one million populations. The company is implementing an integrated solid waste management system where it involved in the optimization of resources to ensure the effectiveness of its services. Formulating this real life problem into vehicle routing problem with stochastic demand model and using some designed algorithms to minimize operation cost of solid waste management. Approach: The implementation of Ant Colony Optimization (ACO for solving solid waste collection problem as a VRPSD model was described. A set of data modified from the well known 50 customers problems were used to find the route such that the expected traveling cost was minimized. The total cost was minimized by adopting a preventive restocking policy which was trading off the extra cost of returning to depot after a stock-out with the cost of returning depot for restocking before a stock-out actually occurs. For comparison purposes, Simulated Annealing (SA was used to generate the solution under the same condition. Results: For the problem size with 12 customers with vehicle capacity 10 units, both algorithms obtained the same best cost which is 69.4358 units. But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. Conclusion: SA was able to obtain good solutions for small ranges especially small size of problem. For ACS, it is always provide good results for all tested ranges and problems sizes of the tested problem.
Mathematical Model and Hybrid Scatter Search for Cost Driven Job-shop Scheduling Problem
Directory of Open Access Journals (Sweden)
Bai Jie
2011-07-01
Full Text Available Job-shop scheduling problem (JSP is one of the most well-known machine scheduling problems and one of the strongly NP-hard combinatorial optimization problems. Cost optimization is an attractive and critical research and development area for both academic and industrial societies. This paper presents a cost driven model of the job-shop scheduling problem in which the solutions are driven by business inputs, such as the cost of the product transitions, revenue loss due to the machine idle time and earliness/tardiness penalty. And then, a new hybrid scatter search algorithm is proposed to solve the cost driven job-shop scheduling problem by introducing the simulated annealing (SA into the improvement method of scatter search (SS. In order to illustrate the effectiveness of the hybrid method, some test problems are generated, and the performance of the proposed method is compared with other evolutionary algorithms such as genetic algorithm and simulated annealing. The experimental simulation tests show that the hybrid method is quite effective at solving the cost driven job-shop scheduling problem.
On scheduling models for the frequency interval assignment problem with cumulative interferences
Kiatmanaroj, Kata; Artigues, Christian; Houssin, Laurent
2016-05-01
In this article, models and methods for solving a real-life frequency assignment problem based on scheduling theory are investigated. A realistic frequency assignment problem involving cumulative interference constraints in which the aim is to maximize the number of assigned users is considered. If interferences are assumed to be binary, a multiple carrier frequency assignment problem can be treated as a disjunctive scheduling problem since a user requesting a number of contiguous frequencies can be considered as a non-preemptive task with a processing time, and two interfering users can be modelled through a disjunctive constraint on the corresponding tasks. A binary interference version of the problem is constructed and a disjunctive scheduling model is derived. Based on the binary representation, two models are proposed. The first one relies on an interference matrix and the second one considers maximal cliques. A third, cumulative, model that yields a new class of scheduling problems is also proposed. Computational experiments show that the case-study frequency assignment problem can be solved efficiently with disjunctive scheduling techniques.
Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems
National Research Council Canada - National Science Library
Z. Ismail; S. L. Loh
2009-01-01
Problem statement: Southern Waste Management environment (SWM environment) is a company responsible for the collection and disposal of solid waste for the city of Johor Bahru, a city with over one million populations...
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.
Ship Block Transportation Scheduling Problem Based on Greedy Algorithm
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Chong Wang
2016-05-01
Full Text Available Ship block transportation problems are crucial issues to address in reducing the construction cost and improving the productivity of shipyards. Shipyards aim to maximize the workload balance of transporters with time constraint such that all blocks should be transported during the planning horizon. This process leads to three types of penalty time: empty transporter travel time, delay time, and tardy time. This study aims to minimize the sum of the penalty time. First, this study presents the problem of ship block transportation with the generalization of the block transportation restriction on the multi-type transporter. Second, the problem is transformed into the classical traveling salesman problem and assignment problem through a reasonable model simplification and by adding a virtual node to the proposed directed graph. Then, a heuristic algorithm based on greedy algorithm is proposed to assign blocks to available transporters and sequencing blocks for each transporter simultaneously. Finally, the numerical experiment method is used to validate the model, and its result shows that the proposed algorithm is effective in realizing the efficient use of the transporters in shipyards. Numerical simulation results demonstrate the promising application of the proposed method to efficiently improve the utilization of transporters and to reduce the cost of ship block logistics for shipyards.
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.
Packing, Scheduling and Covering Problems in a Game-Theoretic Perspective
Kleiman, Elena
2011-01-01
Many packing, scheduling and covering problems that were previously considered by computer science literature in the context of various transportation and production problems, appear also suitable for describing and modeling various fundamental aspects in networks optimization such as routing, resource allocation, congestion control, etc. Various combinatorial problems were already studied from the game theoretic standpoint, and we attempt to complement to this body of research. Specifically, we consider the bin packing problem both in the classic and parametric versions, the job scheduling problem and the machine covering problem in various machine models. We suggest new interpretations of such problems in the context of modern networks and study these problems from a game theoretic perspective by modeling them as games, and then concerning various game theoretic concepts in these games by combining tools from game theory and the traditional combinatorial optimization. In the framework of this research we in...
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.
Number of Tardy Jobs of Single Machine Scheduling Problem with Variable Processing Time
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The number of tardy jobs of the single machine scheduling problem with a variable processing time is studied in accordance with the published instances of traffic transportation management engineering. It is proved by 3-partition problem that if the problem is of ready time and common deadline-constrained, its complexity is NP-hard in the strong sense. Finally, a polynomial algorithm for solving unit processing time and common deadline problems is proposed.
Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems
Heyward, Ann O.
1989-01-01
A two-stage heuristic solution approach for a class of multiobjective, n-job, 1-machine scheduling problems is described. Minimization of job-to-job interference for n jobs is sought. The first stage generates alternative schedule sequences by interchanging pairs of schedule elements. The set of alternative sequences can represent nodes of a decision tree; each node is reached via decision to interchange job elements. The second stage selects the parent node for the next generation of alternative sequences through automated paired comparison of objective performance for all current nodes. An application of the heuristic approach to communications satellite systems planning is presented.
Directory of Open Access Journals (Sweden)
Chih-Chiang Lin
2010-01-01
Full Text Available The broadcast scheduling problem (BSP in packet radio networks is a well-known NP-complete combinatorial optimization problem. The broadcast scheduling avoids packet collisions by allowing only one node transmission in each collision domain of a time division multiple access (TDMA network. It also improves the transmission utilization by assigning one transmission time slot to one or more nodes; thus, each node transmits at least once in each time frame. An optimum transmission schedule could minimize the length of a time frame while minimizing the number of idle nodes. In this paper, we propose a new iterated local search (ILS algorithm that consists of two special perturbation and local search operators to solve the BSPs. Computational experiments are applied to benchmark data sets and randomly generated problem instances. The experimental results show that our ILS approach is effective in solving the problems with only a few runtimes, even for very large networks with 2,500 nodes.
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
In this paper, we investigate the problem of scheduling a 6 DOF robotic arm to carry out a sequence of spray painting tasks. The duration of any given painting task is process dependent and fixed, but the duration of an “intertask”, corresponding to the process of relocating and reorienting...... the robot arm from one painting task to the next one, is influenced by the order of tasks and must be minimized by the scheduler. There are multiple solutions for reaching any given painting task and tasks can be performed in either of two different directions. Further complicating the problem...... 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...
A fuzzy modeling for single machine scheduling problem with deteriorating jobs
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Mohammad Mahavi Mazdeh
2010-06-01
Full Text Available This paper addresses a bi-criteria scheduling problem with deteriorating jobs on a single machine. We develop a model for a single machine bi-criteria scheduling problem (SMBSP with the aim of minimizing total tardiness and work in process (WIP costs. WIP cost increases as a job passes through a series of stages in the production process. Due to the uncertainty involved in real-world scheduling problems, it is sometimes unrealistic or even impossible to acquire exact input data. Hence, we consider the SMBSP under the hypothesis of fuzzy L-R processing time's knowledge and fuzzy L-R due date. The effectiveness of the proposed model and the denoted methodology is demonstrated through a test problem.
Scheduling Internal Audit Activities: A Stochastic Combinatorial Optimization Problem
Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.; Karacaer, S.
2010-01-01
The problem of finding the optimal timing of audit activities within an organisation has been addressed by many researchers. We propose a stochastic programming formulation with Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) certainty-equivalent models. In experiments neithe
Cyclic flow shop scheduling problem with two-machine cells
Directory of Open Access Journals (Sweden)
Bożejko Wojciech
2017-06-01
Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.
Scheduling Internal Audit Activities: A Stochastic Combinatorial Optimization Problem
Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.; Karacaer, S.
2010-01-01
The problem of finding the optimal timing of audit activities within an organisation has been addressed by many researchers. We propose a stochastic programming formulation with Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) certainty-equivalent models. In experiments
Solving Job-Shop Scheduling Problems by Genetic Algorithms Based on Building Block Hypothesis
Institute of Scientific and Technical Information of China (English)
CHENG Rong; CHEN You-ping; LI Zhi-gang
2006-01-01
In this paper, we propose a new genetic algorithm for job-shop scheduling problems(JSP). The proposed method uses the operation-based representation, based on schema theorem and building block hypothesis, a new crossover is proposed: By selecting short, low order highly fit schemas to genetic operator, the crossover can exchange meaningful ordering information of parents effectively and can search the global optimization. Simulation results on MT benchmark problem coded by C + + show that our genetic operators are very powerful and suitable to job-shop scheduling problems and our method outperforms the previous GA-based approaches.
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;
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......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...
Directory of Open Access Journals (Sweden)
Shang-Kuan Chen
2016-01-01
Full Text Available In nuclear power plant construction scheduling, a project is generally defined by its dependent preparation time, the time required for construction, and its reactor installation time. The issues of multiple construction teams and multiple reactor installation teams are considered. In this paper, a hierarchical particle swarm optimization algorithm is proposed to solve the nuclear power plant construction scheduling problem and minimize the occurrence of projects failing to achieve deliverables within applicable due times and deadlines.
Directory of Open Access Journals (Sweden)
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.
Wang, Lui; Valenzuela-Rendon, Manuel
1993-01-01
The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.
Non-Stationary Star and the Trajectory of a Circulating Test Body
Petry, Walter
2010-01-01
A simple model of a spherically symmetric, pulsating star is calculated. The application to the Sun gives a 166-min radial pulsation. The theory of gravitation in flat space-time implies for a spherically symmetric, nonstationary star small time-dependent exterior gravitational effects. The perturbed equations of motion of a test body moving around the non-stationary star are given. The test body moves away from the center during the epoch of collapsing star and moves towards the center during the epoch of expanding star but the converse is also possible under some conditions. The application to the Sun-Earth system is too small to be measured. This effect may be measurable for very compact, non-stationary objects circulated of a nearby test body.
Hu, Y. M.; Liang, Z. M.; Jiang, X. L.; Bu, H.
2015-06-01
In this paper, a novel approach for non-stationary hydrological frequency analysis is proposed. The approach is due to the following consideration that, at present the data series used to detect mutation characteristic is very short, which may only reflect the partial characteristic of the population. That is to say, the mutation characteristic of short series may not fully represent the mutation characteristic of population, such as the difference of mutation degree between short sample and population. In this proposed method, an assumption is done that the variation hydrological series in a big time window owns an expected vibration center (EVC), which is a linear combination of the two mean values of the two subsample series obtained through separating the original hydrological series by a novel optimal segmentation technique (change rate of slope method). Then using the EVC to reconstruct non-stationary series to meet the requirement of stationary, and further ensure the conventional frequency analysis methods is valid.
Exact Stationary and Non-stationary Solutions to Inelastic Maxwell Model with Infinite Energy
Ilyin, Oleg
2016-11-01
The one-dimensional inelastic Boltzmann equation with a constant collision rate (the Maxwell model) is considered. It is shown that for special values of restitution parameter there exists a stationary solution with the characteristic function in the form e^{-P(log (z))z}, where P is a periodic function. The corresponding distribution function belongs to a one special class of stochastic processes termed as a generalized stable in the probability theory. The Fourier transform of the non-stationary equation has the solution bigl (1+P(log (z))zbigr )e^{-Q(log (z))z}. It is proved that this solution is a characteristic function if periodic functions P, Q satisfy some not very restrictive conditions. The stationary and non-stationary solutions correspond to a gas with infinite temperature.
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.
Ahalpara, D P; Parikh, J C; Verma, A; Ahalpara, Dilip P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.; Verma, Amit
2006-01-01
A method based on wavelet transform and genetic programming is proposed for characterizing and modeling variations at multiple scales in non-stationary time series. The cyclic variations, extracted by wavelets and smoothened by cubic splines, are well captured by genetic programming in the form of dynamical equations. For the purpose of illustration, we analyze two different non-stationary financial time series, S&P CNX Nifty closing index of the National Stock Exchange (India) and Dow Jones industrial average closing values through Haar, Daubechies-4 and continuous Morlet wavelets for studying the character of fluctuations at different scales, before modeling the cyclic behavior through GP. Cyclic variations emerge at intermediate time scales and the corresponding dynamical equations reveal characteristic behavior at different scales.
Pattern Recognition of Non-Stationary Time Series with Finite Length
Institute of Scientific and Technical Information of China (English)
FEI Wanchun; BAI Lun
2006-01-01
Statistical learning and recognition methods were used to extract the characteristics of size series measurements of cocoon filaments that are non-stationary in terms of mean and auto-covariance, by using the time varying parameter auto-regressive (TVPAR) model. After the system was taught to recognize the size data, the system correctly recognized the size of series of cocoon filaments as much as 96.95% of the time for a single series and 98.72% of the time for the mean of two series. The correct recognition rate was higher after suitable filtering. The theory and method can be used to analyze other types of non-stationary finite length time series.
Identification of Modal Parameters with Linear Structure under Non-stationary Ambient Excitation
Institute of Scientific and Technical Information of China (English)
续秀忠; 华宏星; 李中付; 陈兆能
2004-01-01
Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.
Optimizing a Military Supply Chain in the Presence of Random, Non-Stationary Demands
2003-12-01
The challenge is to design an efficient military logistics supply chain that satisfies uncertain, non-stationary demands, while taking into account the...deployment of transportation assets and supplies at the operational level, with possible interdiction by enemy forces, We term this model, Optimal Military ... Logistics Supply Chain (OPTiMiLSC), This is a two-level, multiple time period scenario-based stochastic model OPTiMiLSC uses a combination of
Hawking effect of Dirac particles in non-stationary Kerr space-time
Institute of Scientific and Technical Information of China (English)
黎忠恒; 赵峥
1995-01-01
In the process of dealing with the Hawking effect of Dirac particles in the non-stationary Kerr space-time, a new universal method to define the generalized Tortoise coordinate transformation is given. By means of this coordinate transformation, one can discuss the properties of the dynamical equation of particles near event horizons, and get automatically the temperature of Hawking radiation using the method suggested by Damour and others, and thereby dodge the difficulties in calculating the renormalised energy-momentum tensor.
The maxima and sums of multivariate non-stationary Gaussian sequences
Institute of Scientific and Technical Information of China (English)
TAN Zhong-quan; YANG Yang
2015-01-01
Let{Xk1, · · · , Xkp, k≥1}be a p-dimensional standard (zero-means, unit-variances) non-stationary Gaussian vector sequence. In this work, the joint limit distribution of the maxima of {Xk1, · · · , Xkp, k≥1}, the incomplete maxima of those sequences subject to random failure and the partial sums of those sequences are obtained.
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...... of volatility is common to, or independent across, the vector of series under analysis. The bootstrap is shown to perform very well in practice....
MySSP: non-stationary evolutionary sequence simulation, including indels.
Rosenberg, Michael S
2007-02-26
MySSP is a new program for the simulation of DNA sequence evolution across a phylogenetic tree. Although many programs are available for sequence simulation, MySSP is unique in its inclusion of indels, flexibility in allowing for non-stationary patterns, and output of ancestral sequences. Some of these features can individually be found in existing programs, but have not all have been previously available in a single package.
Blind estimation of statistical properties of non-stationary random variables
Mansour, Ali; Mesleh, Raed; Aggoune, el-Hadi M.
2014-12-01
To identify or equalize wireless transmission channels, or alternatively to evaluate the performance of many wireless communication algorithms, coefficients or statistical properties of the used transmission channels are often assumed to be known or can be estimated at the receiver end. For most of the proposed algorithms, the knowledge of transmission channel statistical properties is essential to detect signals and retrieve data. To the best of our knowledge, most proposed approaches assume that transmission channels are static and can be modeled by stationary random variables (uniform, Gaussian, exponential, Weilbul, Rayleigh, etc.). In the majority of sensor networks or cellular systems applications, transmitters and/or receivers are in motion. Therefore, the validity of static transmission channels and the underlying assumptions may not be valid. In this case, coefficients and statistical properties change and therefore the stationary model falls short of making an accurate representation. In order to estimate the statistical properties (represented by the high-order statistics and probability density function, PDF) of dynamic channels, we firstly assume that the dynamic channels can be modeled by short-term stationary but long-term non-stationary random variable (RV), i.e., the RVs are stationary within unknown successive periods but they may suddenly change their statistical properties between two successive periods. Therefore, this manuscript proposes an algorithm to detect the transition phases of non-stationary random variables and introduces an indicator based on high-order statistics for non-stationary transmission which can be used to alter channel properties and initiate the estimation process. Additionally, PDF estimators based on kernel functions are also developed. The first part of the manuscript provides a brief introduction for unbiased estimators of the second and fourth-order cumulants. Then, the non-stationary indicators are formulated
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
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.
The Analysis of Non-Stationary Pooled Time-Series Cross-Section-Data
Directory of Open Access Journals (Sweden)
Christoph Birkel
2015-07-01
Full Text Available It is common in macro-level research on violent crime to analyze datasets combining a cross-section (N units with a time-series (T periods dimension. A large body of methodological literature accumulated since the 1990s raises questions regarding the validity of conventional models for such Pooled Time-Series Cross-Section- (PTCS data in the presence of non-stationarity (i. e. stochastic trends. Extant research shows that conventional techniques lead to consistent estimates only under specific conditions, and standard procedures for statistical inference do not apply. The approaches proposed in the literature to test for stochastic trends and cointegration (see the introduction to this issue are reviewed, as well as methods for estimation and inference in the non-stationary PTCS-context. A host of procedures has been developed, including methods to take simultaneously cross-section dependence and/or structural breaks into account. Thus there are now all the tools needed for valid analyses of non-stationary PTCS-data available, although many of them need large samples to perform well. The general approach to the analysis of non-stationary PTCS-data is illustrated using a data set with robbery rates for eleven West-German federal states 1971-2004. Several meaningful long-run relationships are identified and estimated in these analyses.
Studying the Dynamics of Non-stationary Jet Streams Formation in the Northern Hemisphere Troposphere
Emtsev, Sergey; Krasouski, Aliaksandr; Svetashev, Alexander; Turishev, Leonid; Barodka, Siarhei
2015-04-01
In the present study, we investigate dynamics of non-stationary jets formation in troposphere by means of mesoscale simulations in the Weather Research & Forecasting (WRF) modeling system, analyzing jet streams that affected the territory of Belarus over the time period of 2010-2012. For that purpose, we perform modeling on domains with 5 km, 3 km and 1 km grid steps and 35 vertical coordinate levels with an upper boundary of 10 hPa. We focus our attention to identification of basic regularities in formation, movements and transformations of jet streams, as well as to analysis of their characteristic features, geographical position and underlying atmospheric processes and their classification. On the basis of these regularities, we define basic meteorological parameters that can be used to directly or indirectly (as well as qualitatively and quantitatively) identify the presence of jet streams in the specific region of troposphere, and also to determine their localization, stage of development and other characteristics. Furthermore, we estimate energetic parameters of the identified jet streams and their impact on synoptic situation in the surrounding region. Analyzing meteorological fields obtained from satellite observations, we elaborate a methodology of operational detection and localization of non-stationary jet streams from satellite data. Validation of WRF modeling results with these data proves that mesoscale simulations with WRF are able to provide quite successful forecasts of non-stationary tropospheric jet streams occurrence and also determination of their localization and main characteristics up to 3 days in advance.
Stationary versus non-stationary (13)C-MFA: a comparison using a consistent dataset.
Noack, Stephan; Nöh, Katharina; Moch, Matthias; Oldiges, Marco; Wiechert, Wolfgang
2011-07-10
Besides the well-established (13)C-metabolic flux analysis ((13)C-MFA) which characterizes a cell's fluxome in a metabolic and isotopic stationary state a current area of research is isotopically non-stationary MFA. Non-stationary (13)C-MFA uses short-time isotopic transient data instead of long-time isotopic equilibrium data and thus is capable to resolve fluxes within much shorter labeling experiments. However, a comparison of both methods with data from one single experiment has not been made so far. In order to create a consistent database for directly comparing both methods a (13)C-labeling experiment in a fed-batch cultivation with a Corynebacterium glutamicum lysine producer was carried out. During the experiment the substrate glucose was switched from unlabeled to a specifically labeled glucose mixture which was immediately traced by fast sampling and metabolite quenching. The time course of labeling enrichments in intracellular metabolites until isotopic stationarity was monitored by LC-MS/MS. The resulting dataset was evaluated using the classical as well as the isotopic non-stationary MFA approach. The results show that not only the obtained relative data, i.e. intracellular flux distributions, but also the more informative quantitative fluxome data significantly depend on the combination of the measurements and the underlying modeling approach used for data integration. Taking further criteria on the experimental and computational part into consideration, the current limitations of both methods are demonstrated and possible pitfalls are concluded.
Self-organising mixture autoregressive model for non-stationary time series modelling.
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.
A comparison of three approaches to non-stationary flood frequency analysis
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".
Band-phase-randomized Surrogates to assess nonlinearity in non-stationary time series
Guarin, Diego; Orozco, Alvaro
2011-01-01
Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear surrogate data methods. In this document, we propose a methodology to extend the procedure for generating constrained surrogate time series in order to assess nonlinearity in non-stationary data. The method is based on the band-phase-randomized surrogates, which consists (contrary to the linear surrogate data methods) in randomizing only a portion of the Fourier phases in the high frequency band. Analysis of simulated time series showed that in comparison to the linear surrogate data method, our method is able to discriminate between linear stationarity, linear non-stationary and nonlinear time series. When apply...
Solving the Scheduling Problem in Computational Grid using Artificial Bee Colony Algorithm
Directory of Open Access Journals (Sweden)
Seyyed Mohsen Hashemi
2013-07-01
Full Text Available Scheduling tasks on computational grids is known as NP-complete problem. Scheduling tasks in Grid computing, means assigning tasks to resources such that the time termination and average waiting time criteria and the number of required machines are optimized. Based on heuristic or meta-heuristic search have been proposed to obtain optimal solutions. The presented method tries to optimize all of the mentioned criteria with artificial bee colony system with consideration to precedence of tasks. Bee colony optimization is one of algorithms which categorized in swarm intelligence that can be used in optimization problems. This algorithm is based on the intelligent behavior of honey bees in foraging process. The result shows using bees for solving scheduling problem in computational grid makes better finish time and average waiting time.
Deterministic and randomized scheduling problems under the lp norm on two identical machines
Institute of Scientific and Technical Information of China (English)
LIN Ling; TAN Zhi-yi; HE Yong
2005-01-01
Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in large-size computing, task arrangement in flexible manufacturing systems, etc., are multiprocessor scheduling problem. In the traditional parallel machine scheduling problems, it is assumed that the problems are considered in offline or online environment. But in practice, problems are often not really offline or online but somehow in-between. This means that, with respect to the online problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi-online ones. In this paper, the semi-online problem P2|decr|lp (p＞1) is considered where jobs come in non-increasing order of their processing times and the objective is to minimize the sum of the lp norm of every machine's load. It is shown that LS algorithm is optimal for any lp norm, which extends the results known in the literature. Furthermore, randomized lower bounds for the problems P2|online|lp and P2|decr|lp are presented.
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.
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.
Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals
Rodríguez Molins, Mario
2015-01-01
Despite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is ...
Multi-product valid inequalities for the discrete lot-sizing and scheduling problem
Gicquel, Céline; Minoux, Michel
2015-01-01
International audience; We consider a problem arising in the context of industrial production planning, namely the multi-product discrete lot-sizing and scheduling problem with sequence-dependent changeover costs. We aim at developing an exact solution approach based on a Cut & Branch procedure for this combinatorial optimization problem. To achieve this, we propose a new family of multi-product valid inequalities which corresponds to taking into account the conflicts between different produc...
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 ...... the problem. The tabu search approach employs strategic oscillation and diversification to try to explore a broad region of the solution space. Computational examples suggest that the tabu search approach can find good solutions....
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.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs.The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.
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...... metaheuristics for solving the offline scheduling problem are introduced. Computationally evaluating the heuristics shows that all heuristics find useful solutions with a gap of 20\\% between upper and lower bounds. The metaheuristics give better results than the greedy heuristics, but also have larger time usage...
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.
Solution of the NP-hard total tardiness minimization problem in scheduling theory
Lazarev, A. A.
2007-06-01
The classical NP-hard (in the ordinary sense) problem of scheduling jobs in order to minimize the total tardiness for a single machine 1‖Σ T j is considered. An NP-hard instance of the problem is completely analyzed. A procedure for partitioning the initial set of jobs into subsets is proposed. Algorithms are constructed for finding an optimal schedule depending on the number of subsets. The complexity of the algorithms is O( n 2Σ p j ), where n is the number of jobs and p j is the processing time of the jth job ( j = 1, 2, …, n).
Reactive Scheduling Presentation for an Open Shop problem focused on job\\\\\\'s due dates
Directory of Open Access Journals (Sweden)
hadi naseri
2016-02-01
Full Text Available scheduling consists of assignment resources in order to perform a set of tasks in a given time horizon, that optimizes the usage of available resources. Most of researches in open shop district (area have stationary and certain status, means the situation that all data are certain and won't change in time horizon. Whereas real world scheduling problems are rarely stationary and certain. Reactive programming is a researching district that considers and peruses each changes and uncertain assumptions in real world scheduling problems, so in this paper, first we express a mixed integer programming model to produce initial scheduling for open shop problem, in continue we will generalize the presented model to it's equivalent reactive programming with due date's changing. Finally we will express an algorithm due to necessity for revise the primal scheduling. This algorithm and whole models have been implemented and ran in AIMMS software environment and the computational results have been reported.
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.
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
Directory of Open Access Journals (Sweden)
Sekhri Larbi
2014-12-01
Full Text Available The optimal resources allocation to tasks was the primary objective of the research dealing with scheduling problems. These problems are characterized by their complexity, known as NP-hard in most cases. Currently with the evolution of technology, classical methods are inadequate because they degrade system performance (inflexibility, inefficient resources using policy, etc.. In the context of parallel and distributed systems, several computing units process multitasking applications in concurrent way. Main goal of such process is to schedule tasks and map them on the appropriate machines to achieve the optimal overall system performance (Minimize the Make-span and balance the load among the machines. In this paper we present a Time Petri Net (TPN based approach to solve the scheduling problem by mapping each entity (tasks, resources and constraints to correspondent one in the TPN. In this case, the scheduling problem can be reduced to finding an optimal sequence of transitions leading from an initial marking to a final one. Our approach improves the classical mapping algorithms by introducing a control over resources allocation and by taking into consideration the resource balancing aspect leading to an acceptable state of the system. The approach is applied to a specific class of problems where the machines are parallel and identical. This class is analyzed by using the TiNA (Time Net Analyzer tool software developed in the LAAS laboratory (Toulouse, France.
Cyclic delivery-scheduling problem with synchronization of vehicles\\' arrivals at logistic centers
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Katarzyna Zofia Gdowska
2015-12-01
Full Text Available Background: In this paper a cyclic delivery-scheduling problem with vehicles serving fixed routes is presented. Each vehicle is assigned to one route to which some manufacturers' warehouses and logistics centers belong. A vehicle is to be loaded at a manufacturer's warehouse, then to deliver goods to a logistics center and may be also loaded there with other goods and to transport them to the next node along the route. One logistic center belongs to several routes, so the goods delivered by one vehicle may continue their journey by another truck. For every route the frequency of the vehicle is fixed and known. The objective here is to obtain such synchronization of vehicles arrivals in logistics centers, so that it is possible to organize their arrivals in repeatable blocks. Methods: In the paper the cyclic delivery-scheduling problem with vehicles serving fixed routes is formulated as a MIP model. Due to the fixed routes and desirable synchronization of vehicles arrivals in shared points this problem seems to be similar to the public transit network timetabling problem. Because of that the model presented here was based on a model dedicated to the public transit network timetabling problem, where optimization criterion was to maximize synchronization of vehicles' arrivals at the shared nodes. Results: Mixed integer programming model was employed for solving several cases of cyclic delivery-scheduling problem with vehicles serving fixed routes. Computational experiments are reported and obtained results are presented. Conclusions: The mixed integer programming model for the cyclic delivery-scheduling problem with synchronization of vehicles arrivals at logistic centers presented in this paper can be utilized for generating schedules for a group of vehicles serving fixed long routes. It may result in reducing total operational cost related to this group of vehicles as well as in reducing the goods travel time from the place of origin to their
Analysis of dispatching rules application on scheduling problem in flexible-flow shop production
Directory of Open Access Journals (Sweden)
Rakićević Zoran M.
2014-01-01
Full Text Available In this paper we analyzed a group of simple heuristic methods, which are used for solving the scheduling problem in manufacturing and services. The analysis was performed on the scheduling problem in a flexible-flow shop production, which is known by the English term - Flexible-Flow Shop (FFS. The task is to determine the schedule of processing multiple products on multiple machines, where all the products have the same sequence of processing and for each process there are multiple machines available. For this FFS problem we present the corresponding mathematical model of mixed integer programming. Among potential methods for solving the set task, we consider simple heuristics because the original scheduling problem is NP-hard and finding the exact optimal solution would require unacceptably long computing time. Heuristic methods are based on priority rules that are performed based on the relations of importance between products and their processing time on individual machines. Heuristic methods are widely used for solving practical problems, which was the motivation for the analysis performed in this paper. The aim of the analysis is to identify those priority rules, from a set of considered, which provide a good solution to a hypothetical scheduling problem example, where the evaluation of solution is performed using different criteria functions. The analysis that is presented in the paper was obtained by using the computer program LEKIN. The main results of the analysis indicated that priority rules give different solutions to the problem of FFS and that each of these solutions is a significantly good result in terms of some of the considered criteria functions.
Waters, Melissa B; Lerman, Dorothea C; Hovanetz, Alyson N
2009-01-01
The separate and combined effects of visual schedules and extinction plus differential reinforcement of other behavior (DRO) were evaluated to decrease transition-related problem behavior of 2 children diagnosed with autism. Visual schedules alone were ineffective in reducing problem behavior when transitioning from preferred to nonpreferred activities. Problem behavior decreased for both participants when extinction and DRO were introduced, regardless of whether visual schedules were also used.
An Integer Linear Programming Solution to the Telescope Network Scheduling Problem
Lampoudi, Sotiria; Eastman, Jason
2015-01-01
Telescope networks are gaining traction due to their promise of higher resource utilization than single telescopes and as enablers of novel astronomical observation modes. However, as telescope network sizes increase, the possibility of scheduling them completely or even semi-manually disappears. In an earlier paper, a step towards software telescope scheduling was made with the specification of the Reservation formalism, through the use of which astronomers can express their complex observation needs and preferences. In this paper we build on that work. We present a solution to the discretized version of the problem of scheduling a telescope network. We derive a solvable integer linear programming (ILP) model based on the Reservation formalism. We show computational results verifying its correctness, and confirm that our Gurobi-based implementation can address problems of realistic size. Finally, we extend the ILP model to also handle the novel observation requests that can be specified using the more advanc...
Marwati, Rini; Yulianti, Kartika; Pangestu, Herny Wulandari
2016-02-01
A fuzzy evolutionary algorithm is an integration of an evolutionary algorithm and a fuzzy system. In this paper, we present an application of a genetic algorithm to a fuzzy evolutionary algorithm to detect and to solve chromosomes conflict. A chromosome conflict is identified by existence of any two genes in a chromosome that has the same values as two genes in another chromosome. Based on this approach, we construct an algorithm to solve a lecture scheduling problem. Time codes, lecture codes, lecturer codes, and room codes are defined as genes. They are collected to become chromosomes. As a result, the conflicted schedule turns into chromosomes conflict. Built in the Delphi program, results show that the conflicted lecture schedule problem is solvable by this algorithm.
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.
Directory of Open Access Journals (Sweden)
Mostafa Kazemi
2012-10-01
Full Text Available In this paper, we consider job shop scheduling and machine location problem, simultaneously. Processing, transportation, and setup times are defined as deterministic parameters. The purpose of this paper is to determine machine location and job scheduling such that the make span and transportation cost is minimized. Therefore, the proposed model is a multi-objective problem one, where the first objective function minimizes make span and another minimizes the transportation cost. To solve the multi-objective problem, two methods are evaluated. Considering combination of job shop scheduling problem and machine location problem makes the proposed model more complex than job shop scheduling problem, which is an NP-hard problem. Therefore, to solve the proposed model, genetic algorithm as a meta-heuristic algorithm is implemented. To show the efficiency of the proposed genetic algorithm, 6×6 job shop scheduling problems are considered.
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.
DEFF Research Database (Denmark)
Muller, Laurent Flindt
2009-01-01
We present an application of an Adaptive Large Neighborhood Search (ALNS) algorithm to the Resource-constrained Project Scheduling Problem (RCPSP). The ALNS framework was first proposed by Pisinger and Røpke [19] and can be described as a large neighborhood search algorithm with an adaptive layer...
A Heuristic Algorithm for the Two-Machine Flowshop Group Scheduling Problem
Institute of Scientific and Technical Information of China (English)
王秀利; 吴惕华
2002-01-01
This paper presents the two-machine flowshop group scheduling problem with the optimal objective ofmaximum lateness. A dominance rule within group and a dominance rule between groups are established. Thesedominance rules along with a previously established dominance rule are used to develop a heuristic algorithm.Experimental results are given and analyzed.
Tabu search for the job-shop scheduling problem with multi-purpose machines
Hurink, Johann; Jurisch, Bernd; Thole, Monika
1994-01-01
In this paper we study the following generalization of the job-shop scheduling problem. Each operation can be performed by one machine out of a set of machines given for this operation. The processing time does not depend on the machine which has been chosen for processing the operation. This proble
An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction
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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.
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Wei-min Ma
2015-01-01
Full Text Available We consider parallel-machine scheduling problems with past-sequence-dependent (psd delivery times and aging maintenance. The delivery time is proportional to the waiting time in the system. Each machine has an aging maintenance activity. We develop polynomial algorithms to three versions of the problem to minimize the total absolute deviation of job completion times, the total load, and the total completion time.
Energy Technology Data Exchange (ETDEWEB)
Hoogeveen, J.A.; Van de Velde, S.L.
1994-12-31
We address the problem of scheduling n jobs in a flow shop environment that consists of a batching machine with capacity c and a standard machine with capacity 1 such that total completion time is minimized. We formulate this problem as a pidgin integer programming problem by using the concept of position dependent completion times; to this formulation we apply Lagrangian relaxation to obtain a strong lower bound. We show that this lower bound dominates the bound that was obtained by Ahmadi et al. by applying Lagrangian relaxation to an ordinary formulation of this problem.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.
Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue
2015-01-01
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.
Directory of Open Access Journals (Sweden)
Xiaopan Chen
Full Text Available As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.
Directory of Open Access Journals (Sweden)
Mohamed A.A.-F. Mansour
2011-01-01
Full Text Available Problem statement: In this article we address the multi-objective Periodic Maintenance Scheduling Problem (PMSP of scheduling a set of cyclic maintenance operations for a given set of machines through a specified planning period to minimize the total variance of workforce levels measured in man-hours and maintenance costs with equal weights. Approach: The article proposed a mixed integer non-linear math programming model and a linearised model for the PMSP. Also, we proposed a Genetic Algorithm (GA for solving the problem using a new genome representation considered as a new addition to the maintenance scheduling literature. The algorithms were compared on a set of representative test problems. Results: The developed GA proves its capability and superiority to find good solutions for the PMSP and outperforms solutions found by the commercial optimization package CPLEX. The results indicated that the developed algorithms were able to identify optimal solutions for small size problems up to 5 machines and 6 planning periods.The GAs defined solutions in 22 seconds consuming less than two kilobytes with a reliability of 0.84 while the nonlinear and linear models consumes on average 705 and 37 kilobytes respectively. Conclusion: The developed GA could define solutions of average performance of 0.34 and 0.8 for the linearized algorithm compared with lower bound defined by the nonlinear math programming model. We hope to expand the developed algorithms for integrating maintenance planning and aggregate production planning problems.
Solving Resource-constrained Multiple Project Scheduling Problem Using Timed Colored Petri Nets
Institute of Scientific and Technical Information of China (English)
WU Yu; ZHUANG Xin-cun; SONG Guo-hui; XU Xiao-dong; LI Cong-xin
2009-01-01
To solve the resource-constrained multiple project scheduling problem (RCMPSP) more effectively, a method based on timed colored Petri net (TCPN) was proposed. In this methodology, firstly a novel mapping mechanism between traditional network diagram such as CPM (critical path method)/PERT (program evaluation and review technique) and TCPN was presented. Then a primary TCPN (PTCPN) for solving RCMPSP was modeled based on the proposed mapping mechanism. Meanwhile, the object PTCPN was used to simulate the multiple projects scheduling and to find the approximately optimal value of RCMPSP. Finally, the performance of the proposed approach for solving RCMPSP was validated by executing a mould manufacturing example.
Ermuratschii V.V.; Gritsay M.A
2014-01-01
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 iterati...
A voxelation-corrected non-stationary 3D cluster-size test based on random field theory.
Li, Huanjie; Nickerson, Lisa D; Zhao, Xuna; Nichols, Thomas E; Gao, Jia-Hong
2015-09-01
Cluster-size tests (CSTs) based on random field theory (RFT) are commonly adopted to identify significant differences in brain images. However, the use of RFT in CSTs rests on the assumption of uniform smoothness (stationarity). When images are non-stationary, CSTs based on RFT will likely lead to increased false positives in smooth regions and reduced power in rough regions. An adjustment to the cluster size according to the local smoothness at each voxel has been proposed for the standard test based on RFT to address non-stationarity, however, this technique requires images with a large degree of spatial smoothing, large degrees of freedom and high intensity thresholding. Recently, we proposed a voxelation-corrected 3D CST based on Gaussian random field theory that does not place constraints on the degree of spatial smoothness. However, this approach is only applicable to stationary images, requiring further modification to enable use for non-stationary images. In this study, we present modifications of this method to develop a voxelation-corrected non-stationary 3D CST based on RFT. Both simulated and real data were used to compare the voxelation-corrected non-stationary CST to the standard cluster-size adjusted non-stationary CST based on RFT and the voxelation-corrected stationary CST. We found that voxelation-corrected stationary CST is liberal for non-stationary images and the voxelation-corrected non-stationary CST performs better than cluster-size adjusted non-stationary CST based on RFT under low smoothness, low intensity threshold and low degrees of freedom. Published by Elsevier Inc.
An Improved Ant Colony Algorithm for a Single-machine Scheduling Problem with Setup Times
Institute of Scientific and Technical Information of China (English)
YE Qiang; LIU Xinbao; LIU Lin; YANG Shanglin
2006-01-01
Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutually independent and available at time zero. The machine processes the jobs sequentially and it is not idle if there is any job to be processed. The operation of each job cannot be interrupted. The machine cannot process more than one job at a time. A setup time is needed if the machine switches from one type of job to another. The objective is to find an optimal schedule with the minimal total jobs' completion time. While the sum of jobs' processing time is always a constant, the objective is to minimize the sum of setup times. Ant colony optimization (ACO) is a meta-heuristic that has recently been applied to scheduling problem. In this paper we propose an improved ACO-Branching Ant Colony with Dynamic Perturbation (DPBAC) algorithm for the single-machine scheduling problem. DPBAC improves traditional ACO in following aspects: introducing Branching Method to choose starting points; improving state transition rules; introducing Mutation Method to shorten tours; improving pheromone updating rules and introducing Conditional Dynamic Perturbation Strategy. Computational results show that DPBAC algorithm is superior to the traditional ACO algorithm.
Minimizing the total tardiness for the tool change scheduling problem on parallel machines
Directory of Open Access Journals (Sweden)
Antonio Costa
2016-04-01
Full Text Available This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.
Identifying and tracking switching, non-stationary opponents: a Bayesian approach
CSIR Research Space (South Africa)
Hernandez-Leal, P
2016-02-01
Full Text Available and Tracking Switching, Non-stationary Opponents: a Bayesian Approach Pablo Hernandez-Leal1, Matthew E. Taylor2, Benjamin Rosman3, L. Enrique Sucar1 and Enrique Munoz de Cote1 1Instituto Nacional de Astrofı´sica, O´ptica y Electro´nica Sta. Marı´a Tonantzintla..., Puebla, Mexico 2Washington State University Pullman, Washington, USA 3Council for Scientific and Industrial Research, and the University of the Witwatersrand South Africa Abstract In many situations, agents are required to use a set of strategies...
A bayesian approach for learning and tracking switching, non-stationary opponents
CSIR Research Space (South Africa)
Hernandez-Leal, P
2016-02-01
Full Text Available and Multiagent Systems, 9-13 May 2016, Singapore A Bayesian Approach for Learning and Tracking Switching, Non- Stationary Opponents (Extended Abstract) Pablo Hernandez-Leal Instituto Nacional de Astrofísica, Óptica y Electrónica Puebla, México pablohl...@ccc.inaoep.mx Benjamin Rosman Council for Scientific and Industrial Research, and the University of the Witwatersrand, South Africa brosman@csir.co.za Matthew E. Taylor Washington State University, Pullman, Washington, USA taylorm@eecs.wsu.edu L. Enrique Sucar...
Mathematical modeling of non-stationary heat and mass transfer in disperse systems
Ermakova, L. A.; Krasnoperov, S. Y.; Kalashnikov, S. N.
2016-09-01
The work describes mathematical model of non-stationary heat and mass transfer processes in dispersed environment, taking into account the phase transition; presents the results of numeric modelling for conditions of direct reduction in high-temperature reducing atmosphere, corresponding to the direct reduction in the jet-emulsion unit according to the principles of self-organization. The method was developed for calculation of heat and mass transfer of the aggregate of iron material particles in accordance with the given distribution law.
Energy Technology Data Exchange (ETDEWEB)
Golovin, Sergey V., E-mail: sergey@hydro.nsc.r [Lavrentyev Institute of Hydrodynamics SB RAS, 630090 Novosibirsk (Russian Federation); Department of Mechanics and Mathematics, Novosibirsk State University, 630090 Novosibirsk (Russian Federation)
2011-01-17
Equations of magnetohydrodynamics (MHD) in the natural curvilinear system of coordinates where trajectories and magnetic lines play a role of coordinate curves are reduced to the non-linear vector wave equation coupled with the incompressibility condition in the form of the generalized Cauchy integral. The symmetry group of obtained equation, equivalence transformation, and group classification with respect to the constitutive equation are calculated. New exact solutions with functional arbitrariness describing non-stationary incompressible flows with constant total pressure are given by explicit formulae. The corresponding magnetic surfaces have the shape of deformed nested cylinders, tori, or knotted tubes.
Analysis of structural seismic behaviour: from non stationary to non linear effects
Carlo Ponzo, Felice; Ditommaso, Rocco; Monaco, Lisa
2014-05-01
to either non-linearity (i.e. Damage) or non-stationary phenomenon (the particular combination of input and response). This fact may lead to erroneous conclusions attributing the frequency variations to the structural damage instead that to non-stationary phenomena. This article deals with the theoretical foundation of the analysis of non-stationary behaviour of structures, and then provides experimental evidence in order to distinguish non-linearity from simple non-stationary phenomena. Further work must be performed in order to fully validate this kind of approach and to completely define these threshold for various structural forms and building typologies. REFERENCES Ponzo F. C., Ditommaso R., Auletta G., Mossucca A. (2010). A Fast Method for Structural Health Monitoring of Italian Strategic Reinforced Concrete Buildings. Bulletin of Earthquake Engineering. Volume 8, Number 6, pp. 1421-1434. DOI: 10.1007/s10518-010-9194-6.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The performance of automatic speech recognizer degrades seriously when there are mismatches between the training and testing conditions. Vector Taylor Series (VTS) approach has been used to compensate mismatches caused by additive noise and convolutive channel distortion in the cepstral domain. In this paper, the conventional VTS is extended by incorporating noise clustering into its EM iteration procedure, improving its compensation effectiveness under non-stationary noisy environments. Recognition experiments under babble and exhibition noisy environments demonstrate that the new algorithm achieves35 % average error rate reduction compared with the conventional VTS.
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....
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....
Diagnostics of many-particle electronic states: non-stationary currents and residual charge dynamics
Maslova, N. S.; Mantsevich, V. N.; Arseyev, P. I.
2017-01-01
We propose the method for identifying many particle electronic states in the system of coupled quantum dots (impurities) with Coulomb correlations. We demonstrate that different electronic states can be distinguished by the complex analysis of localized charge dynamics and non-stationary characteristics. We show that localized charge time evolution strongly depends on the properties of initial state and analyze different time scales in charge kinetics for initially prepared singlet and triplet states. We reveal the conditions for existence of charge trapping effects governed by the selection rules for electron transitions between the states with different occupation numbers.
Continuous wavelet transform for non-stationary vibration detection with phase-OTDR.
Qin, Zengguang; Chen, Liang; Bao, Xiaoyi
2012-08-27
We propose the continuous wavelet transform for non-stationary vibration measurement by distributed vibration sensor based on phase optical time-domain reflectometry (OTDR). The continuous wavelet transform approach can give simultaneously the frequency and time information of the vibration event. Frequency evolution is obtained by the wavelet ridge detection method from the scalogram of the continuous wavelet transform. In addition, a novel signal processing algorithm based on the global wavelet spectrum is used to determine the location of vibration. Distributed vibration measurements of 500 Hz and 500 Hz to 1 kHz sweep events over 20 cm fiber length are demonstrated using a single mode fiber.
CAPACITATED LOT SIZING AND SCHEDULING PROBLEMS USING HYBRID GA/TS APPROACHES
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
The capacitated lot sizing and scheduling problem that involves in determining the production amounts and release dates for several items over a given planning horizon are given to meet dynamic order demand without incurring backloggings. The problem considering overtime capacity is studied. The mathematical model is presented, and a genetic algorithm (GA) approach is developed to solve the problem. The initial solutions are generated after using heuristic method. Capacity balancing procedure is employed to stipulate the feasibility of the solutions. In addition, a technique based on Tabu search (TS) is inserted into the genetic algorithm to deal with the scheduled overtime and help the convergence of algorithm. Computational simulation is conducted to test the efficiency of the proposed hybrid approach, which turns out to improve both the solution quality and execution speed.
Models and Strategies for Variants of the Job Shop Scheduling Problem
Grimes, Diarmuid
2011-01-01
Recently, a variety of constraint programming and Boolean satisfiability approaches to scheduling problems have been introduced. They have in common the use of relatively simple propagation mechanisms and an adaptive way to focus on the most constrained part of the problem. In some cases, these methods compare favorably to more classical constraint programming methods relying on propagation algorithms for global unary or cumulative resource constraints and dedicated search heuristics. In particular, we described an approach that combines restarting, with a generic adaptive heuristic and solution guided branching on a simple model based on a decomposition of disjunctive constraints. In this paper, we introduce an adaptation of this technique for an important subclass of job shop scheduling problems (JSPs), where the objective function involves minimization of earliness/tardiness costs. We further show that our technique can be improved by adding domain specific information for one variant of the JSP (involving...
Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju
2014-04-01
Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.
Single-machine group scheduling problems with deteriorating and learning effect
Xingong, Zhang; Yong, Wang; Shikun, Bai
2016-07-01
The concepts of deteriorating jobs and learning effects have been individually studied in many scheduling problems. However, most studies considering the deteriorating and learning effects ignore the fact that production efficiency can be increased by grouping various parts and products with similar designs and/or production processes. This phenomenon is known as 'group technology' in the literature. In this paper, a new group scheduling model with deteriorating and learning effects is proposed, where learning effect depends not only on job position, but also on the position of the corresponding job group; deteriorating effect depends on its starting time of the job. This paper shows that the makespan and the total completion time problems remain polynomial optimal solvable under the proposed model. In addition, a polynomial optimal solution is also presented to minimise the maximum lateness problem under certain agreeable restriction.
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.
Waters, Melissa B.; Lerman, Dorothea C.; Hovanetz, Alyson N.
2009-01-01
The separate and combined effects of visual schedules and extinction plus differential reinforcement of other behavior (DRO) were evaluated to decrease transition-related problem behavior of 2 children diagnosed with autism. Visual schedules alone were ineffective in reducing problem behavior when transitioning from preferred to nonpreferred…
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.
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...
Recent trends in solving the deterministic resource constrained Project Scheduling Problem
DEFF Research Database (Denmark)
Karam, Ahmed; Lazarova-Molnar, Sanja
2013-01-01
, a number of new and promising meta-heuristic approaches for solving the RCPSP problem have emerged. In this paper, we provide a detailed review of the most recent approaches for solving the RCPSP that have been proposed in literature. In particular, we present a comparison, classification and analysis......, based on a number of relevant metrics. Extensive numerical results based on well-known benchmark problem instance sets of size J30, J60 and J120 from Project Scheduling Problem Library (PSPLIB), as well as comparisons among state-of-the-art hybrid meta-heuristic algorithms demonstrate the effectiveness...
An Optimal Algorithm for a Class of Parallel Machines Scheduling Problem
Institute of Scientific and Technical Information of China (English)
常俊林; 邵惠鹤
2004-01-01
This paper considers the parallel machines scheduling problem where jobs are subject to different release times. A constructive heuristic is first proposed to solve the problem in a modest amount of computer time. In general, the quality of the solutions provided by heuristics degrades with the increase of the probiem's scale. Combined the global search ability of genetic algorithm, this paper proposed a hybrid heuristic to improve the quality of solutions further. The computational results show that the hybrid heuristic combines the advantages of heuristic and genetic algorithm effectively and can provide very good solutions to some large problems in a reasonable amount of computer time.
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...... tests are run on a generic setup with simulated data. The test results are very promising. The production delays are reduced significantly in the new solutions compared with the corresponding delays observed in a simulation of manual planning....
An intelligent approach for variable size segmentation of non-stationary signals.
Azami, Hamed; Hassanpour, Hamid; Escudero, Javier; Sanei, Saeid
2015-09-01
In numerous signal processing applications, non-stationary signals should be segmented to piece-wise stationary epochs before being further analyzed. In this article, an enhanced segmentation method based on fractal dimension (FD) and evolutionary algorithms (EAs) for non-stationary signals, such as electroencephalogram (EEG), magnetoencephalogram (MEG) and electromyogram (EMG), is proposed. In the proposed approach, discrete wavelet transform (DWT) decomposes the signal into orthonormal time series with different frequency bands. Then, the FD of the decomposed signal is calculated within two sliding windows. The accuracy of the segmentation method depends on these parameters of FD. In this study, four EAs are used to increase the accuracy of segmentation method and choose acceptable parameters of the FD. These include particle swarm optimization (PSO), new PSO (NPSO), PSO with mutation, and bee colony optimization (BCO). The suggested methods are compared with other most popular approaches (improved nonlinear energy operator (INLEO), wavelet generalized likelihood ratio (WGLR), and Varri's method) using synthetic signals, real EEG data, and the difference in the received photons of galactic objects. The results demonstrate the absolute superiority of the suggested approach.
An intelligent approach for variable size segmentation of non-stationary signals
Directory of Open Access Journals (Sweden)
Hamed Azami
2015-09-01
Full Text Available In numerous signal processing applications, non-stationary signals should be segmented to piece-wise stationary epochs before being further analyzed. In this article, an enhanced segmentation method based on fractal dimension (FD and evolutionary algorithms (EAs for non-stationary signals, such as electroencephalogram (EEG, magnetoencephalogram (MEG and electromyogram (EMG, is proposed. In the proposed approach, discrete wavelet transform (DWT decomposes the signal into orthonormal time series with different frequency bands. Then, the FD of the decomposed signal is calculated within two sliding windows. The accuracy of the segmentation method depends on these parameters of FD. In this study, four EAs are used to increase the accuracy of segmentation method and choose acceptable parameters of the FD. These include particle swarm optimization (PSO, new PSO (NPSO, PSO with mutation, and bee colony optimization (BCO. The suggested methods are compared with other most popular approaches (improved nonlinear energy operator (INLEO, wavelet generalized likelihood ratio (WGLR, and Varri’s method using synthetic signals, real EEG data, and the difference in the received photons of galactic objects. The results demonstrate the absolute superiority of the suggested approach.
Local multifractal detrended fluctuation analysis for non-stationary image's texture segmentation
Wang, Fang; Li, Zong-shou; Li, Jin-wei
2014-12-01
Feature extraction plays a great important role in image processing and pattern recognition. As a power tool, multifractal theory is recently employed for this job. However, traditional multifractal methods are proposed to analyze the objects with stationary measure and cannot for non-stationary measure. The works of this paper is twofold. First, the definition of stationary image and 2D image feature detection methods are proposed. Second, a novel feature extraction scheme for non-stationary image is proposed by local multifractal detrended fluctuation analysis (Local MF-DFA), which is based on 2D MF-DFA. A set of new multifractal descriptors, called local generalized Hurst exponent (Lhq) is defined to characterize the local scaling properties of textures. To test the proposed method, both the novel texture descriptor and other two multifractal indicators, namely, local Hölder coefficients based on capacity measure and multifractal dimension Dq based on multifractal differential box-counting (MDBC) method, are compared in segmentation experiments. The first experiment indicates that the segmentation results obtained by the proposed Lhq are better than the MDBC-based Dq slightly and superior to the local Hölder coefficients significantly. The results in the second experiment demonstrate that the Lhq can distinguish the texture images more effectively and provide more robust segmentations than the MDBC-based Dq significantly.
Li, Yanbin; Mulani, Sameer B.; Kapania, Rakesh K.; Fei, Qingguo; Wu, Shaoqing
2017-07-01
An algorithm that integrates Karhunen-Loeve expansion (KLE) and the finite element method (FEM) is proposed to perform non-stationary random vibration analysis of structures under excitations, represented by multiple random processes that are correlated in both time and spatial domains. In KLE, the auto-covariance functions of random excitations are discretized using orthogonal basis functions. The KLE for multiple correlated random excitations relies on expansions in terms of correlated sets of random variables reflecting the cross-covariance of the random processes. During the response calculations, the eigenfunctions of KLE used to represent excitations are applied as forcing functions to the structure. The proposed algorithm is applied to a 2DOF system, a 2D cantilever beam and a 3D aircraft wing under both stationary and non-stationary correlated random excitations. Two methods are adopted to obtain the structural responses: a) the modal method and b) the direct method. Both the methods provide the statistics of the dynamic response with sufficient accuracy. The structural responses under the same type of correlated random excitations are bounded by the response obtained by perfectly correlated and uncorrelated random excitations. The structural response increases with a decrease in the correlation length and with an increase in the correlation magnitude. The proposed methodology can be applied for the analysis of any complex structure under any type of random excitation.
Self-adaptive change detection in streaming data with non-stationary distribution
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.
Non-Stationary Hydrologic Frequency Analysis using B-Splines Quantile Regression
Nasri, B.; St-Hilaire, A.; Bouezmarni, T.; Ouarda, T.
2015-12-01
Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic structures and water resources system under the assumption of stationarity. However, with increasing evidence of changing climate, it is possible that the assumption of stationarity would no longer be valid and the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extreme flows based on B-Splines quantile regression, which allows to model non-stationary data that have a dependence on covariates. Such covariates may have linear or nonlinear dependence. A Markov Chain Monte Carlo (MCMC) algorithm is used to estimate quantiles and their posterior distributions. A coefficient of determination for quantiles regression is proposed to evaluate the estimation of the proposed model for each quantile level. The method is applied on annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in these variables and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for annual maximum and minimum discharge with high annual non-exceedance probabilities. Keywords: Quantile regression, B-Splines functions, MCMC, Streamflow, Climate indices, non-stationarity.
Tracking non-stationary EEG sources using adaptive online recursive independent component analysis.
Hsu, Sheng-Hsiou; Pion-Tonachini, Luca; Jung, Tzyy-Ping; Cauwenberghs, Gert
2015-01-01
Electroencephalographic (EEG) source-level analyses such as independent component analysis (ICA) have uncovered features related to human cognitive functions or artifactual activities. Among these methods, Online Recursive ICA (ORICA) has been shown to achieve fast convergence in decomposing high-density EEG data for real-time applications. However, its adaptation performance has not been fully explored due to the difficulty in choosing an appropriate forgetting factor: the weight applied to new data in a recursive update which determines the trade-off between the adaptation capability and convergence quality. This study proposes an adaptive forgetting factor for ORICA (adaptive ORICA) to learn and adapt to non-stationarity in the EEG data. Using a realistically simulated non-stationary EEG dataset, we empirically show adaptive forgetting factors outperform other commonly-used non-adaptive rules when underlying source dynamics are changing. Standard offline ICA can only extract a subset of the changing sources while adaptive ORICA can recover all. Applied to actual EEG data recorded from a task-switching experiments, adaptive ORICA can learn and re-learn the task-related components as they change. With an adaptive forgetting factor, adaptive ORICA can track non-stationary EEG sources, opening many new online applications in brain-computer interfaces and in monitoring of brain dynamics.
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 CO_{2} and seasonal maxima of cumulated daily precipitations are presented.
Scale parameters in stationary and non-stationary GEV modeling of extreme precipitation
Panagoulia, Dionysia; Economou, Polychronis; Caroni, Chrys
2013-04-01
The generalized extreme value (GEV) distribution is often fitted to environmental time series of extreme values such as annual maxima of daily precipitation. We study two methodological issues here. First we compare methods of selecting the best model among a set of 16 GEV models that allow non-stationary scale and location parameters. Results of simulation studies showed that both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) correctly detected non-stationarity but the BIC was superior in selecting the correct model more often. The second issue is how best to produce confidence intervals (CIs) for the parameters of the model and other quantities such as the return levels that are usually required for hydrological and climatological time series. Four bootstrap CIs - normal, percentile, basic, and bias corrected and accelerated (BCa) - constructed by random-t resampling, fixed-t resampling and the parametric bootstrap methods were compared. CIs for parameters of the stationary model do not present major differences. CIs for the more extreme quantiles tend to become very wide for all bootstrap methods. For non-stationary GEV models with linear time dependence of location or log-linear time dependence of scale, coverage probabilities of the CIs are reasonably accurate for the parameters. For the extreme percentiles, the BCa method is best overall and the fixed-t method also gives good average coverage probabilities.
Meta-RaPS Algorithm for the Aerial Refueling Scheduling Problem
Kaplan, Sezgin; Arin, Arif; Rabadi, Ghaith
2011-01-01
The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on multiple tankers (machines). ARSP assumes that jobs have different release times and due dates, The total weighted tardiness is used to evaluate schedule's quality. Therefore, ARSP can be modeled as a parallel machine scheduling with release limes and due dates to minimize the total weighted tardiness. Since ARSP is NP-hard, it will be more appropriate to develop a pproimate or heuristic algorithm to obtain solutions in reasonable computation limes. In this paper, Meta-Raps-ATC algorithm is implemented to create high quality solutions. Meta-RaPS (Meta-heuristic for Randomized Priority Search) is a recent and promising meta heuristic that is applied by introducing randomness to a construction heuristic. The Apparent Tardiness Rule (ATC), which is a good rule for scheduling problems with tardiness objective, is used to construct initial solutions which are improved by an exchanging operation. Results are presented for generated instances.
Ramli, Razamin; Tein, Lim Huai
2016-08-01
A good work schedule can improve hospital operations by providing better coverage with appropriate staffing levels in managing nurse personnel. Hence, constructing the best nurse work schedule is the appropriate effort. In doing so, an improved selection operator in the Evolutionary Algorithm (EA) strategy for a nurse scheduling problem (NSP) is proposed. The smart and efficient scheduling procedures were considered. Computation of the performance of each potential solution or schedule was done through fitness evaluation. The best so far solution was obtained via special Maximax&Maximin (MM) parent selection operator embedded in the EA, which fulfilled all constraints considered in the NSP.
A Genetic Algorithm Approach for Solving a Flexible Job ShopScheduling Problem
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Sayedmohammadreza Vaghefinezhad
2012-05-01
Full Text Available Flexible job shop scheduling has been noticed as an effective manufacturing system to cope with rapid development in todays competitive environment. Flexible job shop scheduling problem (FJSSP is known as a NP-hard in the field of the optimization problem. Assuming the dynamic state of the real world, make these problems more and more complicated. Most studies in the field of FJSSP have only focused on minimizing the total makespan. In this paper, a mathematical model for FJSSP has been developed. The objective function is maximizing the total profit while meeting some constraints. Considering time-varying raw material and selling price and dissimilar demand for each period, are attempts that have been done to decrease gaps between reality and the model. A manufacturer that produces various parts of gas valves has been used as a case study. The scheduling problem for multi part, multi period, and multi operation with parallel machines has been solved by genetic algorithm (GA. The best obtained answer determines the economic amount of production by different machines that belong to predefined operations for each part to satisfy customer demand in each period.
Duan, Qian-Qian; Yang, Gen-Ke; Pan, Chang-Chun
2014-01-01
A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The heuristic returned by the FSM can guide the GA algorithm towards good solutions. The idea behind this is that we can generate promising substructure or partial solution by using FSM. Furthermore, the FSM can guarantee that the entire solution space is uniformly covered. Therefore, the combination of the two algorithms has better global performance than the existing GA or FSM which is operated individually. Finally, a real-life crude oil scheduling problem from the literature is used for conducting simulation. The experimental results validate that the proposed method outperforms the state-of-art GA method.
A Model for Bus Crew Scheduling Problem with Multiple Duty Types
Directory of Open Access Journals (Sweden)
Mingming Chen
2012-01-01
Full Text Available This paper presents an approach for solving the bus crew scheduling problem which considers early, day, and late duty modes with time shift and work intensity constraints. Furthermore, the constraint with the least crew number of a certain duty (e.g., day duty has also been considered. An optimization model is formulated as a 0-1 integer programming problem to improve the efficiency of crew scheduling at the minimum expense of total idle time of crew for a circle bus line. Correspondingly, a heuristic algorithm utilizing the tabu search algorithm has been proposed to solve the model. Finally, the proposed model and algorithm are successfully tested by a case study.
Institute of Scientific and Technical Information of China (English)
Jianjun Qi; Bo Guo; Hongtao Lei; Tao Zhang
2014-01-01
This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem (RACP) by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion (PPSO) combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.
An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times
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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.
Tabrizi, Babak H.; Farid Ghaderi, Seyed
2016-09-01
Simultaneous planning of project scheduling and material procurement can improve the project execution costs. Hence, the issue has been addressed here by a mixed-integer programming model. The proposed model facilitates the procurement decisions by accounting for a number of suppliers offering a distinctive discount formula from which to purchase the required materials. It is aimed at developing schedules with the best net present value regarding the obtained benefit and costs of the project execution. A genetic algorithm is applied to deal with the problem, in addition to a modified version equipped with a variable neighbourhood search. The underlying factors of the solution methods are calibrated by the Taguchi method to obtain robust solutions. The performance of the aforementioned methods is compared for different problem sizes, in which the utilized local search proved efficient. Finally, a sensitivity analysis is carried out to check the effect of inflation on the objective function value.
A Modified Biogeography-Based Optimization for the Flexible Job Shop Scheduling Problem
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Yuzhen Yang
2015-01-01
Full Text Available The flexible job shop scheduling problem (FJSSP is a practical extension of classical job shop scheduling problem that is known to be NP-hard. In this paper, an effective modified biogeography-based optimization (MBBO algorithm with machine-based shifting is proposed to solve FJSSP with makespan minimization. The MBBO attaches great importance to the balance between exploration and exploitation. At the initialization stage, different strategies which correspond to two-vector representation are proposed to generate the initial habitats. At global phase, different migration and mutation operators are properly designed. At local phase, a machine-based shifting decoding strategy and a local search based on insertion to the habitat with best makespan are introduced to enhance the exploitation ability. A series of experiments on two well-known benchmark instances are performed. The comparisons between MBBO and other famous algorithms as well as BBO variants prove the effectiveness and efficiency of MBBO in solving FJSSP.
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Mazur Michał
2015-09-01
Full Text Available A new approach to solving realistic car assembly scheduling problems for mixed model assembly line is presented. It is proposed to decompose the problem into two subproblems: 1 a sequencing problem that generates admissible car sequences fulfilling capacity constraints for all car models in the production plan, 2 a scheduling problem that determines an admissible car sequence with shortest makespan. The details of this approach are illustrated by a simple numerical example.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, we give a mathematical model for earliness-tardiness job scheduling problem with a common due window on parallel and non-identical machines. Because the job scheduling problem discussed in the paper contains a problem of minimizing make-span, which is NP-complete on parallel and uniform machines, a heuristic algorithm is presented to find an approximate solution for the scheduling problem after proving an important theorem. Two numerical examples illustrate that the heuristic algorithm is very useful and effective in obtaining the near-optimal solution.
Mordant, N; Pinton, J F
2001-01-01
It is known that ultrasound techniques yield non-intrusive measurements of hydrodynamic flows. For example, the study of the echoes produced by a large number of particle insonified by pulsed wavetrains has led to a now standard velocimetry technique. In this paper, we propose to extend the method to the continuous tracking of one single particle embedded in a complex flow. This gives a Lagrangian measurement of the fluid motion, which is of importance in mixing and turbulence studies. The method relies on the ability to resolve in time the Doppler shift of the sound scattered by the continuously insonfied particle. For this signal processing problem two classes of approaches are used: time-frequency analysis and parametric high resolution methods. In the first class we consider the spectrogram and reassigned spectrogram, and we apply it to detect the motion of a small bead settling in a fluid at rest. In more non-stationary turbulent flows where methods in the second class are more robust, we have adapted an...
Institute of Scientific and Technical Information of China (English)
M Kamrul AHSAN; De-bi TSAO
2003-01-01
In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm for solving multiple resource-constrained project scheduling problems. The heuristic solves problems in two phases. In the pre-processing phase, the algorithm estimates distance between a state and the goal state and measures complexity of problem instances. In the search phase, the algorithm uses estimates of the pre-processing phase to further estimate distances to the goal state. The search continues in a stepwise generation of a series of intermediate states through search path evaluation process with backtracking. Developments of intermediate states are exclusively based on a bi-criteria new state selection technique where we consider resource utilization and duration estimate to the goal state. We also propose a variable weighting technique based on initial problem complexity measures. Introducing this technique allows the algorithm to efficiently solve complex project scheduling problems. A numerical example illustrates the algorithm and performance is evaluated by extensive experimentation with various problem parameters. Computational results indicate significance of the algorithm in terms of solution quality and computational performance.
A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem
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Xiaohui Li
2010-01-01
Full Text Available A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific problem. Then, since this problem is NP hard in the strong sense, two well-known approximated methods, NSGA-II and SPEA-II, are adopted to solve it. Experimental results show the advantages of NSGA-II for the studied problem. An exact method is then applied to be compared with NSGA-II algorithm in order to prove the efficiency of the former. Experimental results show the advantages of NSGA-II for the studied problem. Computational experiments show that on all the tested instances, our NSGA-II algorithm was able to get the optimal solutions.
Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem
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Mohammed Al-Salem
2016-01-01
Full Text Available The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD for a set of jobs when their weights equal 1 (unweighted problem. This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.
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.
Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines
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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.
A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs
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Chun-Cheng Lin
2014-01-01
Full Text Available This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.
Hybrid metaheuristics for solving a fuzzy single batch-processing machine scheduling problem.
Molla-Alizadeh-Zavardehi, S; Tavakkoli-Moghaddam, R; Lotfi, F Hosseinzadeh
2014-01-01
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.
Non-stationary resonance dynamics of a nonlinear sonic vacuum with grounding supports
Koroleva (Kikot), I. P.; Manevitch, L. I.; Vakakis, Alexander F.
2015-11-01
In a recent work [L.I. Manevitch, A.F.Vakakis, Nonlinear oscillatory acoustic vacuum, SIAM Journal of Applied Mathematics 74(6) (2014), 1742-1762] it was shown that a periodic chain of linearly coupled particles performing low-energy in-plane transverse oscillations behaves as a strongly nonlinear sonic vacuum (with corresponding speed of sound equal to zero). In this work we consider the grounded version of this system by coupling each particle to the ground through lateral springs in order to study the effect of the grounding stiffness on the strongly nonlinear dynamics. In that context we consider the simplest possible such system consisting of two coupled particles and present analytical and numerical studies of the non-stationary planar dynamics. The most significant limiting case corresponding to predominant low energy transversal excitations is considered by taking into account leading order geometric nonlinearities. Then we show that the grounded system behaves as a nonlinear sonic vacuum due to the purely cubic stiffness nonlinearities in the governing equations of motion and the complete absence of any linear stiffness terms. Under certain assumptions the nonlinear normal modes (i.e., the time-periodic nonlinear oscillations) in the configuration space of this system coincide with those of the corresponding linear one, so they obey the same orthogonality relations. Moreover, we analytically find that there are two transitions in the dynamics of this system, with the parameter governing these transitions being the relation between the lateral (grounding) and the interchain stiffnesses. The first transition concerns a bifurcation of one of the nonlinear normal modes (NNMs), whereas the second provides conditions for intense energy transfers and mixing between the NNMs. The drastic effects of these bifurcations on the non-stationary resonant dynamics are discussed. Specifically, the second transition relates to strongly non-stationary dynamics, and signifies
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.
Robust Proactive Project Scheduling Model for the Stochastic Discrete Time/Cost Trade-Off Problem
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Hongbo Li
2015-01-01
Full Text Available We study the project budget version of the stochastic discrete time/cost trade-off problem (SDTCTP-B from the viewpoint of the robustness in the scheduling. Given the project budget and a set of activity execution modes, each with uncertain activity time and cost, the objective of the SDTCTP-B is to minimize the expected project makespan by determining each activity’s mode and starting time. By modeling the activity time and cost using interval numbers, we propose a proactive project scheduling model for the SDTCTP-B based on robust optimization theory. Our model can generate robust baseline schedules that enable a freely adjustable level of robustness. We convert our model into its robust counterpart using a form of the mixed-integer programming model. Extensive experiments are performed on a large number of randomly generated networks to validate our model. Moreover, simulation is used to investigate the trade-off between the advantages and the disadvantages of our robust proactive project scheduling model.
A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz
2012-01-01
This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell produci....... A genetic algorithm-based heuristic is developed to find the near optimal solution for the problem. A case study is implemented at an impeller production line in a factory to demonstrate the result of the proposed approach....
A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz
2012-01-01
This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell produci....... A genetic algorithm-based heuristic is developed to find the near optimal solution for the problem. A case study is implemented at an impeller production line in a factory to demonstrate the result of the proposed approach....
Liu, Gang; Mao, Zhu; Todd, Michael
2016-11-01
This paper proposes a damage detection method based on the geometrical variation of transient trajectories in phase-space, and the proposed methodology is compatible with non-stationary excitations (e.g., earthquake-induced ground motion). The work presented assumes zero-mean non-stationary excitation, and extends the random decrement technique to convert non-stationary response signals of the structure into free-vibration data. Transient trajectories of the structure are reconstructed via the embedding theorem from the converted free-vibration data, and trajectories are mapped successively into phase-space to enhance statistical analysis. Based upon the characterized system dynamics in terms of phase-space, the time prediction error is adopted as the damage index. To identify the presence and severity of damage in a statistically rigorous way, receiver operating characteristic curves and the Bhattacharyya distance are employed. The results from both numerical simulations and experiments validate the proposed framework, when the test structures are subject to non-stationary excitations. The extension achieved in this paper enables the phase-space damage detection approach to be compatible with non-stationary scenarios, such as traffic, wind, and earthquake loadings. Moreover, the results indicate that this phase-state-based method is able to identify damage-induced nonlinearity in response, which is an intrinsic characteristic associated with most structural damage types.
SCHEDULING PROBLEMS OF STATIONARY OBJECTS WITH THE PROCESSOR IN ONE-DIMENSIONAL ZONE
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N. A. Dunichkina
2015-01-01
Full Text Available We consider the mathematical model in which an operating processor serves the set of the stationary objects positioned in a one-dimensional working zone. The processor performs two voyages between the uttermost points of the zone: the forward or direct one, where certain objects are served, and the return one, where remaining objects are served. Servicing of the object cannot start earlier than its ready date. The individual penalty function is assigned to every object, the function depending on the servicing completion time. Minimized criteria of schedule quality are assumed to be total service duration and total penalty. We formulate and study optimization problems with one and two criteria. Proposed algorithms are based on dynamic programming and Pareto principle, the implementations of these algorithms are demonstrated on numerical examples. We show that the algorithm for the problem of processing time minimization is polynomial, and that the problem of total penalty minimization is NP-hard. Correspondingly, the bicriteria problem with the mentioned evaluation criteria is fundamentally intractable, computational complexity of the schedule structure algorithm is exponential. The model describes the fuel supply processes to the diesel-electrical dredgers which extract non-metallic building materials (sand, gravel in large-scale areas of inland waterways. Similar models and optimization problems are important, for example, in applications like the control of satellite group refueling and regular civil aircraft refueling.The article is published in the author’s wording.
Directory of Open Access Journals (Sweden)
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.
New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times
Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid
2017-01-01
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.
New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times
Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid
2017-01-01
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.
A tabu-search heuristic for solving the multi-depot vehicle scheduling problem
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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.
A Non-Stationary Poisson Model for the Scaling of Urban Traffic Fluctuations
Institute of Scientific and Technical Information of China (English)
CHEN Yu-Dong; LI Li; ZHANG Yi; JIN Xue-Xiang
2008-01-01
We investigate the traffic flow volume data on the time dependent activity of Beijing's urban road network.The couplings between the average flux and the fluctuations on individual links are shown to follow certain scaling laws and yield a wide variety of scaling exponents between 1/2 and 1.To quantitatively explain this interesting phenomenon,a non-stationary Poisson arriving model is proposed.The scaling property is interpreted as the result of the time-variation of the arriving rate of flux over the network,which nicely explicates the effect of aggregation windows,and provides a concise model for the dependence of scaling exponent on the external/internal force ratio.
Nonlinear stability of non-stationary cross-flow vortices in compressible boundary layers
Gajjar, J. S. B.
1995-01-01
The nonlinear evolution of long wavelength non-stationary cross-flow vortices in a compressible boundary layer is investigated and the work extends that of Gajjar (1994) to flows involving multiple critical layers. The basic flow profile considered in this paper is that appropriate for a fully three-dimensional boundary layer with O(1) Mach number and with wall heating or cooling. The governing equations for the evolution of the cross-flow vortex are obtained and some special cases are discussed. One special case includes linear theory where exact analytic expressions for the growth rate of the vortices are obtained. Another special case is a generalization of the Bassom & Gajjar (1988) results for neutral waves to compressible flows. The viscous correction to the growth rate is derived and it is shown how the unsteady nonlinear critical layer structure merges with that for a Haberman type of viscous critical layer.
Fluctuation-dissipation relation in a spin glass in the non-stationary regime
Energy Technology Data Exchange (ETDEWEB)
Herisson, D.; Ocio, M
2003-05-01
We present the first experimental determination of the time autocorrelation C(t',t) of magnetization in the non-stationary regime of a spin glass. Quantitative comparison with the corresponding response, the magnetic susceptibility {chi}(t',t), is made possible by the use of a new experimental setup allowing both measurements in the same conditions. Clearly, we observe a non-linear fluctuation-dissipation relation between C and {chi}, depending weakly on the waiting time t'. Following theoretical developments on mean-field models, and lately on short range ones, it is predicted that in the limit of long times, the {chi}(C) relationship should become independent on t'. A scaling procedure allows us to extrapolate to the limit of long waiting times.
Estimation in semi-parametric regression with non-stationary regressors
Chen, Jia; Li, Degui; 10.3150/10-BEJ344
2012-01-01
In this paper, we consider a partially linear model of the form $Y_t=X_t^{\\tau}\\theta_0+g(V_t)+\\epsilon_t$, $t=1,...,n$, where $\\{V_t\\}$ is a $\\beta$ null recurrent Markov chain, $\\{X_t\\}$ is a sequence of either strictly stationary or non-stationary regressors and $\\{\\epsilon_t\\}$ is a stationary sequence. We propose to estimate both $\\theta_0$ and $g(\\cdot)$ by a semi-parametric least-squares (SLS) estimation method. Under certain conditions, we then show that the proposed SLS estimator of $\\theta_0$ is still asymptotically normal with the same rate as for the case of stationary time series. In addition, we also establish an asymptotic distribution for the nonparametric estimator of the function $g(\\cdot)$. Some numerical examples are provided to show that our theory and estimation method work well in practice.
3rd International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Rubini, Riccardo; D'Elia, Gianluca; Cocconcelli, Marco; Chaari, Fakher; Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2014-01-01
This book presents the processings of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13) which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition.The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to po...
Quantum Tunneling of Massive Spin-1 Particles From Non-stationary Metrics
Sakalli, I
2016-01-01
Hawking radiation (HR) is invariant under the coordinate transformation, and it must be independent of the particle type emitting from the considered black hole (BH). From this fact, we focus on the HR of massive vector (spin-1) particles tunneling from Schwarzschild BH expressed in the Kruskal-Szekeres (KS) and dynamic Lemaitre (DL) coordinates. Using the Proca equation (PE) together with Hamilton-Jacobi (HJ) and WKB methods, we show that the tunneling rate, and its consequence Hawking temperature are well recovered by the quantum tunneling of the massive vector particles. This is the first example for the HR of the massive vector particles tunneling from a four dimensional BH expressed in non-stationary regular coordinates.
INCA: a computational platform for isotopically non-stationary metabolic flux analysis.
Young, Jamey D
2014-05-01
13C flux analysis studies have become an essential component of metabolic engineering research. The scope of these studies has gradually expanded to include both isotopically steady-state and transient labeling experiments, the latter of which are uniquely applicable to photosynthetic organisms and slow-to-label mammalian cell cultures. Isotopomer network compartmental analysis (INCA) is the first publicly available software package that can perform both steady-state metabolic flux analysis and isotopically non-stationary metabolic flux analysis. The software provides a framework for comprehensive analysis of metabolic networks using mass balances and elementary metabolite unit balances. The generation of balance equations and their computational solution is completely automated and can be performed on networks of arbitrary complexity.
A Simplified Calculation Method for Non-stationary Random Seismic Response of Jacket Platform
Institute of Scientific and Technical Information of China (English)
HAN Xiao-shuang; MA Jun; ZHAO De-you; ZHOU Bo
2008-01-01
Jacket platform was simulated by non-uniform cantilever beam subjected to axial loading. Based on the Hamilton theory, the equation of bending motion was developed and solved by the classical Ritz method combined with the pseudo-excitation method (PEM) for non-stationary random response with non-classical damping. Usually, random response of this continuous structure is obtained by orthogonality of modes and some normal modes of the structure are needed, causing inconvenience in the analysis of the non-uniform beam whose normal modes are not easy to be obtained. However, if the PEM is extended to calculate random respouse by combining it with the classical Ritz method, the responses of non-uniform beam, such as auto-power spectral density (PSD) function, croes-PSD and higher spectral moments can be solved directly avoiding the calculation of normal modes. The numerical results show that the present method is effective and useful in aseismic design of platforms.
Is the Labour Force Participation Rate Non-Stationary in Romania?
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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.
4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2016-01-01
The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining, or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book no...
Non-stationary frequency domain system identification using time-frequency representations
Guo, Yanlin; Kareem, Ahsan
2016-05-01
System properties of buildings and bridges may vary with time due to temperature changes, aging or extreme loadings. To identify these time-varying system properties, this study proposes a new output-only non-stationary system identification (SI) framework based on instantaneous or marginal spectra derived from the time-frequency representation, e.g., short time Fourier or wavelet transform. Spectra derived from these time-frequency representations are very popular in tracking time-varying frequencies; however, they have seldom been used to identify the time-varying damping ratio because a short window needed to capture the time-varying information amplifies the bandwidth significantly, which may lead to considerably overestimating the damping ratio. To overcome this shortcoming, this study modifies the theoretical frequency response function (FRF) to explicitly account for the windowing effect, and therefore enables SI directly using instantaneous or marginal spectra derived from the wavelet or short time Fourier transform. The response spectrum estimated using the short time window and the modified FRF are both influenced by the same time window, thus the instantaneous or time-localized marginal spectrum of response can be fitted to the modified FRF to identify frequency and damping ratio at each time instant. This spectral-based SI framework can reliably identify damping in time-varying systems under non-stationary excitations. The efficacy of the proposed framework is demonstrated by both numerical and full-scale examples, and also compared to the time-domain SI method, stochastic subspace identification (SSI), since the time-domain SI approaches and their extensions are popular in identifying time-varying systems utilizing recursive algorithms or moving windows.
Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model
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.
Extension of the Dynasearch to the Two-Machine Permutation Flowshop Scheduling Problem
Tanaka, Shunji
The purpose of this study is to construct a solution algorithm for the two-machine permutation flowshop problem based on the dynasearch. The dynasearch is an efficient local search algorithm that employs a special neighborhood structure called dynasearch swap neighborhood. Its primary advantage is that the neighborhood of a solution can be explored in polynomial time although it is composed of an exponential number of solutions. The dynasearch for machine scheduling was originally developed for the single-machine total weighted tardiness problem. Then, it was extended to the problem with idle time and setup times. This study further extends the dynasearch to the two-machine permutation flowshop problem and its effectiveness is examined by numerical experiments for both total weighted tardiness and total weighted earliness-tardiness objectives.
A Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container
Institute of Scientific and Technical Information of China (English)
CAO Jinxin; SHI Oixin; Der-Horng Lee
2008-01-01
Truck scheduling and storage allocation, as two separate subproblems in port operations, have been deeply studied in past decades. However, from the operational point of view, they are highly interde-pendent. Storage allocation for import containers has to balance the travel time and queuing time of each container in yard. This paper proposed an integer programming model handling these two problems as a whole. The objective of this model is to reduce congestion and waiting time of container trucks in the termi-nal so as to decrease the makespan of discharging containers. Due to the inherent complexity of the prob-lem, a genetic algorithm and a greedy heuristic algorithm are designed to attain near optimal solutions. It shows that the heuristic algorithm can achieve the optimal solution for small-scale problems. The solutions of small- and large-scale problems obtained from the heuristic algorithm are better than those from the ge-netic algorithm.
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.
Directory of Open Access Journals (Sweden)
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.
Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
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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.
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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.
Solving a Production Scheduling Problem by Means of Two Biobjective Metaheuristic Procedures
Toncovich, Adrián; Oliveros Colay, María José; Moreno, José María; Corral, Jiménez; Corral, Rafael
2009-11-01
Production planning and scheduling problems emphasize the need for the availability of management tools that can help to assure proper service levels to customers, maintaining, at the same time, the production costs at acceptable levels and maximizing the utilization of the production facilities. In this case, a production scheduling problem that arises in the context of the activities of a company dedicated to the manufacturing of furniture for children and teenagers is addressed. Two bicriteria metaheuristic procedures are proposed to solve the sequencing problem in a production equipment that constitutes the bottleneck of the production process of the company. The production scheduling problem can be characterized as a general flow shop with sequence dependant setup times and additional inventory constraints. Two objectives are simultaneously taken into account when the quality of the candidate solutions is evaluated: the minimization of completion time of all jobs, or makespan, and the minimization of the total flow time of all jobs. Both procedures are based on a local search strategy that responds to the structure of the simulated annealing metaheuristic. In this case, both metaheuristic approaches generate a set of solutions that provides an approximation to the optimal Pareto front. In order to evaluate the performance of the proposed techniques a series of experiments was conducted. After analyzing the results, it can be said that the solutions provided by both approaches are adequate from the viewpoint of the quality as well as the computational effort involved in their generation. Nevertheless, a further refinement of the proposed procedures should be implemented with the aim of facilitating a quasi-automatic definition of the solution parameters.
Solving a manpower scheduling problem for airline catering using tabu search
DEFF Research Database (Denmark)
Ho, Sin C.; Leung, Janny M. Y.
and assign teams and start-times for the jobs, so as to service as many flights as possible. Only teams with the appropriate skills can be assigned to a flight. Workload balance among the teams is also a consideration. We present a model formulation and investigate a tabu-search heuristic approach to solve......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...... be serviced within a given time-window by a team consisting of a driver and a loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams...
A New Local Search Algorithm for the Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
HuangWen-qi; YinAi-hua
2003-01-01
In this paper, the job shop scheduling problem concerned with minimizing make-span is discussed, and a new local search algorithm is proposed for it. This local search method is based on an improved shifting bottleneck procedure and Tabu Search technique. This new local search is different from the previous Tabu Search (TS) proposed by other authors, which is because the improved shifting bottleneck procedure is a new technology that is provided by us for the problem, and two remarkable strategies--intensification and diversification of TS are modified. To demonstrate the performance, our algorithm has been tested on many common problem instances (benchmarks) with various sizes and levels of hardness and compared with other algorithms, especially the latest TS in the literatures.Computational experiments show that this algorithm is effective and efficient.
Local Search Algorithm with Hybrid Neighborhood and Its Application to Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
黄文奇; 曾立平
2004-01-01
A new local search method with hybrid neighborhood for Job shop scheduling problem is developed. The proposed hybrid neighborhood is not only efficient in local search, but also can help overcome entrapments while search procedure get trapped at local optima and carry the search to areas of the feasible set with better prospect. New strategies used for breaking out of entrapments are presented and they are helpful for the procedure to improve local optima. A performance comparison of the proposed method with some best-performing algorithms on all 10-job, 10-machine benchmark problems and the other two problems generated by Fisher and Thompson ( ie. , FT6 and FT20) is made. The experiment results show the better optimal performance of the proposed algorithm.
A New Local Search Algorithm for the Job Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
Huang Wen-qi; Yin Ai-hua
2003-01-01
In this paper, the job shop scheduling problem concerned with minimizing make-span is discussed, and a new local search algorithm is proposed for it. This local search method is based on an improved shifting bottleneck procedure and Tabu Search technique. This new local search is different from the previous Tabu Search (TS) proposed by other authors, which is because the improved shifting bottleneck procedure is a new technology that is provided by us for the problem, and two remarkable strategies--intensification and diversification of TS are modified. To demonstrate the performance, our algorithm has been tested on many common problem instances (benchmarks)with various sizes and levels of hardness and compared with other algorithms, especially the latest TS in the literatures.Computational experiments show that this algorithm is effective and efficient.
Benders-based approach for an integrated Lot-Sizing and Scheduling problem
Directory of Open Access Journals (Sweden)
ouerfelli hala
2012-07-01
Full Text Available The main concern of the current paper is to present mathematical model and a decision method for production planning issues of a manufacturing organization. We aim at integrating the medium term and the short term as two levels of decision. These consist in periodical planning with determining the intended produced quantity and scheduling the functioning of machines. It is worth noting that in the literature there exist only few works on the issue of integration because of the shortage of numerical results. Thus, the integrated model presented here allows us to take into consideration the scheduling constraints in the Lot-sizing model. A recent algorithm, based on a heuristic approach to find a production planning with a feasible schedule for each period, has recently been published in which the two levels of decision were applied. In this paper, some of these ideas are developed in order to get an optimal solution. For this, an exact algorithm of Benders’ decomposition method is adopted to the integration problem. This has been proved efficient with reliance primarily on modeling view and the link between the two levels of decision and secondly on the numerical view.
Directory of Open Access Journals (Sweden)
Hong-an Yang
2014-01-01
Full Text Available We focus on solving Stochastic Job Shop Scheduling Problem (SJSSP with random processing time to minimize the expected sum of earliness and tardiness costs of all jobs. To further enhance the efficiency of the simulation optimization technique of embedding Evolutionary Strategy in Ordinal Optimization (ESOO which is based on Monte Carlo simulation, we embed Optimal Computing Budget Allocation (OCBA technique into the exploration stage of ESOO to optimize the performance evaluation process by controlling the allocation of simulation times. However, while pursuing a good set of schedules, “super individuals,” which can absorb most of the given computation while others hardly get any simulation budget, may emerge according to the allocating equation of OCBA. Consequently, the schedules cannot be evaluated exactly, and thus the probability of correct selection (PCS tends to be low. Therefore, we modify OCBA to balance the computation allocation: (1 set a threshold of simulation times to detect “super individuals” and (2 follow an exclusion mechanism to marginalize them. Finally, the proposed approach is applied to an SJSSP comprising 8 jobs on 8 machines with random processing time in truncated normal, uniform, and exponential distributions, respectively. The results demonstrate that our method outperforms the ESOO method by achieving better solutions.
Directory of Open Access Journals (Sweden)
Lei Wang
2017-01-01
Full Text Available In real-world manufacturing systems, production scheduling systems are often implemented under random or dynamic events like machine failure, unexpected processing times, stochastic arrival of the urgent orders, cancellation of the orders, and so on. These dynamic events will lead the initial scheduling scheme to be nonoptimal and/or infeasible. Hence, appropriate dynamic rescheduling approaches are needed to overcome the dynamic events. In this paper, we propose a dynamic rescheduling method based on variable interval rescheduling strategy (VIRS to deal with the dynamic flexible job shop scheduling problem considering machine failure, urgent job arrival, and job damage as disruptions. On the other hand, an improved genetic algorithm (GA is proposed for minimizing makespan. In our improved GA, a mix of random initialization population by combining initialization machine and initialization operation with random initialization is designed for generating high-quality initial population. In addition, the elitist strategy (ES and improved population diversity strategy (IPDS are used to avoid falling into the local optimal solution. Experimental results for static and several dynamic events in the FJSP show that our method is feasible and effective.
Directory of Open Access Journals (Sweden)
Hossein Erfani
2012-09-01
Full Text Available With regard to the fact of the rapid growth of distributed systems and their large spectrum of usage of proposing and representing controlling solutions and optimization of task execution procedures is one of the most important issues. Task scheduling in distributed systems has determining role in improving efficiency in applications such as communication, routing, production plans and project management. The most important issues of good schedule are minimizing makespan and average of waiting time. However, the recent and previous effort usually focused on minimizing makespan. This article presents and analyze a new method based on Ant Colony Optimization (ACO algorithm with considerations to precedence and communication cost for task scheduling problem. In the mentioned method in addition to optimization of finish time, average of waiting time and number of needed processors are also optimized. In this method, by using of a new heuristic list, an algorithm based on ant colony is proposed. The results obtained in comparison with the latest similar models of random search algorithms, proves the higher efficiency of algorithm.
An estimation of distribution algorithm (EDA) variant with QGA for Flowshop scheduling problem
Latif, Muhammad Shahid; Hong, Zhou; Ali, Amir
2014-04-01
In this research article, a hybrid approach is presented which based on well-known meta-heuristics algorithms. This study based on integration of Quantum Genetic Algorithm (QGA) and Estimation of Distribution Algorithm, EDA, (for simplicity we use Q-EDA) for flowshop scheduling, a well-known NP hard Problem, while focusing on the total flow time minimization criterion. A relatively new method has been adopted for the encoding of jobs sequence in flowshop known as angel rotations instead of random keys, so QGA become more efficient. Further, EDA has been integrated to update the population of QGA by making a probability model. This probabilistic model is built and used to generate new candidate solutions which comprised on best individuals, obtained after several repetitions of proposed (Q-EDA) approach. As both heuristics based on probabilistic characteristics, so exhibits excellent learning capability and have minimum chances of being trapped in local optima. The results obtained during this study are presented and compared with contemporary approaches in literature. The current hybrid Q-EDA has implemented on different benchmark problems. The experiments has showed better convergence and results. It is concluded that hybrid Q-EDA algorithm can generally produce better results while implemented for Flowshop Scheduling Problem (FSSP).
Optimizing a multi-objectives flow shop scheduling problem by a novel genetic algorithm
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R. Tavakkoli-Moghaddam
2013-06-01
Full Text Available Flow-shop problems, as a typical manufacturing challenge, have become an interesting area of research. The primary concern is that the solution space is huge and, therefore, the set of feasible solutions cannot be enumerated one by one. In this paper, we present an efficient solution strategy based on a genetic algorithm (GA to minimize the makespan, total waiting time and total tardiness in a flow shop consisting of n jobs and m machines. The primary objective is to minimize the job waiting time before performing the related operations. This is a major concern for some industries such as food and chemical for planning and production scheduling. In these industries, there is a probability of the decay and deterioration of the products prior to accomplishment of operations in workstation, due to the increase in the waiting time. We develop a model for a flowshop scheduling problem, which uses the planner-specified weights for handling a multi-objective optimization problem. These weights represent the priority of planning objectives given by managers. The results of the proposed GA and classic GA are analyzed by the analysis of variance (ANOVA method and the results are discussed.
Directory of Open Access Journals (Sweden)
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.
An adaptive large neighborhood search heuristic for the Electric Vehicle Scheduling Problem
DEFF Research Database (Denmark)
Wen, M.; Linde, Esben; Røpke, Stefan;
2016-01-01
This paper addresses the Electric Vehicle Scheduling Problem (E-VSP), in which a set of timetabled bus trips, each starting from and ending at specific locations and at specific times, should be carried out by a set of electric buses or vehicles based at a number of depots with limited driving...... ranges. The electric vehicles are allowed to be recharged fully or partially at any of the given recharging stations. The objective is to firstly minimize the number of vehicles needed to cover all the timetabled trips, and secondly to minimize the total traveling distance, which is equivalent...
An Efficient Estimation of Distribution Algorithm for Job Shop Scheduling Problem
He, Xiao-Juan; Zeng, Jian-Chao; Xue, Song-Dong; Wang, Li-Fang
An estimation of distribution algorithm with probability model based on permutation information of neighboring operations for job shop scheduling problem was proposed. The probability model was given using frequency information of pair-wise operations neighboring. Then the structure of optimal individual was marked and the operations of optimal individual were partitioned to some independent sub-blocks. To avoid repeating search in same area and improve search speed, each sub-block was taken as a whole to be adjusted. Also, stochastic adjustment to the operations within each sub-block was introduced to enhance the local search ability. The experimental results show that the proposed algorithm is more robust and efficient.
A Grafted Genetic Algorithm for the Job-Shop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
LI Xiang-jun; WANG Shu-zhen; XU Guo-hua
2004-01-01
The standard genetic algorithm has limitations of a low convergence rate and premature convergence in solving the job-shop scheduling problem.To overcome these limitations,this paper presents a new improved hybrid genetic algorithm on the basis of the idea of graft in botany.Through the introduction of a grafted population and crossover probability matrix,this algorithm accelerates the convergence rate greatly and also increases the ability to fight premature convergence.Finally,the approach is tested on a set of standard instances taken from the literature and compared with other approaches.The computation results validate the effectiveness of the proposed algorithm.
A Two-Stage Assembly-Type Flowshop Scheduling Problem for Minimizing Total Tardiness
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Ju-Yong Lee
2016-01-01
Full Text Available This research considers a two-stage assembly-type flowshop scheduling problem with the objective of minimizing the total tardiness. The first stage consists of two independent machines, and the second stage consists of a single machine. Two types of components are fabricated in the first stage, and then they are assembled in the second stage. Dominance properties and lower bounds are developed, and a branch and bound algorithm is presented that uses these properties and lower bounds as well as an upper bound obtained from a heuristic algorithm. The algorithm performance is evaluated using a series of computational experiments on randomly generated instances and the results are reported.
An improved Genetic Algorithm of Bi-level Coding for Flexible Job Shop Scheduling Problems
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Ye Li
2014-07-01
Full Text Available The current study presents an improved genetic algorithm(GA for the flexible job shop scheduling problem (FJSP. The coding is divided into working sequence level and machine level and two effective crossover operators and mutation operators are designed for the generation and reduce the disruptive effects of genetic operators. The algorithm is tested on instances of 10 working sequences and 10 machines. Computational results show that the proposed GA was successfully and efficiently applied to the FJSP. The results were compared with other approaches, such as traditional GA and GA with neural network. Compared to traditional genetic algorithm, the proposed approach yields significant improvement in solution quality.
组合优化调度问题求解方法%The Approach to Solving Combinatorial Optimization Schedule Problems
Institute of Scientific and Technical Information of China (English)
张居阳; 孙吉贵
2003-01-01
Optimization schedule problem is this kind of problem that people often meet in the field of industrial manufacture,transportation and traffic. A good schedule scheme can improve the efficiency of production and reduce the cost of production. So scholars in all of the related fields have high regard for schedule problem at all times. This paper describes the method and technology about combinatorial optimization schedule problems. The research state and advances in this field are reviewed and surveyed. At the end of the paper an approach to solving Job Shop problem,a representative paradigm in schedule problem ,is introduced and discussed concretely.
Yahia, K; Cardoso, A J M; Ghoggal, A; Zouzou, S E
2014-03-01
Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations.
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 c...
限位排序的若干结果%Some Results on Position Restriction Scheduling Problems
Institute of Scientific and Technical Information of China (English)
陈友军; 林诒勋
2008-01-01
In this paper,we first consider the position restriction scheduling problems on a single machine.The problems have been solved in certain special cases,especially for those obtained by restricting the processing time pj=1.We introduce the bipartite matching algorithm to provide some polynomial-time algorithms to solve them.Then we further consider a problem on unrelated processors.
Directory of Open Access Journals (Sweden)
Daniel C Medina
Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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%. CONCLUSIONS/SIGNIFICANCE: 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
Modeling fire spatial non-stationary in Portugal using GWR and GAMLSS
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
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.
Indian Academy of Sciences (India)
Long Zhang; Guoliang Xiong; Hesheng Liu; Huijun Zou; Weizhong Guo
2010-04-01
A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identiﬁcation of time-varying model coefﬁcients and the determination of model order, are addressed by means of neural networks and genetic algorithms, respectively. Firstly, a simulated signal which mimic the rotor vibration during run-up stages was processed for a comparative study on TVAR and other non-parametric time-frequency representations such as Short Time Fourier Transform, Continuous Wavelet Transform, Empirical Mode Decomposition, Wigner–Ville Distribution and Choi–Williams Distribution, in terms of their resolutions, accuracy, cross term suppression as well as noise resistance. Secondly, TVAR was applied to analyse non-stationary vibration signals collected from a rotor test rig during run-up stages, with an aim to extract fault symptoms under non-stationary operating conditions. Simulation and experimental results demonstrate that TVAR is an effective solution to non-stationary signal analysis and has strong capability in signal time-frequency feature extraction.
DEFF Research Database (Denmark)
Chen, Gang; Govindan, Kannan; Yang, Zhong-Zhen
2013-01-01
implementation scenarios of TAS: static TAS (STAS) and dynamic TAS (DTAS). First, a non-stationary M(t)/E/c(t) queueing model is used to analyse a terminal gate system, and solved with a new approximation approach. Then, genetic algorithm is applied to optimise the hourly quota of entry appointments in STAS...
DEFF Research Database (Denmark)
Chen, Gang; Govindan, Kannan; Yang, Zhong-Zhen
2013-01-01
implementation scenarios of TAS: static TAS (STAS) and dynamic TAS (DTAS). First, a non-stationary M(t)/E/c(t) queueing model is used to analyse a terminal gate system, and solved with a new approximation approach. Then, genetic algorithm is applied to optimise the hourly quota of entry appointments in STAS...
Ophem, S. van; Berkhoff, A.P.
2012-01-01
Commonly used adaptive algorithms which determine the coefficients of a finite impulse response feed-forward filter in an active noise control application, as the filtered reference least mean squares algorithm, are not performing well when the sound source is non-stationary. A multiple input and
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A modified bottleneck-based (MB) heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested,which is simpler but more tailored than the shifting bottleneck (SB) procedure.In this algorithm,the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules.Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems.Furthermore,it can obtain a good solution in a short time for large-scale job-shop scheduling problems.
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2014-09-01
In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.
Institute of Scientific and Technical Information of China (English)
张素君; 顾幸生
2015-01-01
An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers (IBFSP) in order to minimize the maximum completion time (i.e makespan). The effective combination of the insertion and swap operator is applied to producing neighborhood individual at the employed bee phase. The tournament selection is adopted to avoid falling into local optima, while, the optimized insert operator embeds in onlooker bee phase for further searching the neighborhood solution to enhance the local search ability of algorithm. The tournament selection with size 2 is again applied and a better selected solution will be performed destruction and construction of iterated greedy (IG) algorithm, and then the result replaces the worse one. Simulation results show that our algorithm has a better performance compared with the HDDE and CHS which were proposed recently. It provides the better known solutions for the makespan criterion to flow shop scheduling problem with limited buffers for the Car benchmark by Carlier and Rec benchmark by Reeves. The convergence curves show that the algorithm not only has faster convergence speed but also has better convergence value.
Solving the Resource Constrained Project Scheduling Problem to Minimize the Financial Failure Risk
Directory of Open Access Journals (Sweden)
Zhi Jie Chen
2012-04-01
Full Text Available In practice, a project usually involves cash in- and out-flows associated with each activity. This paper aims to minimize the payment failure risk during the project execution for the resource-constrained project scheduling problem (RCPSP. In such models, the money-time value, which is the product of the net cash in-flow and the time length from the completion time of each activity to the project deadline, provides a financial evaluation of project cash availability. The cash availability of a project schedule is defined as the sum of these money-time values associated with all activities, which is mathematically equivalent to the minimization objective of total weighted completion time. This paper presents four memetic algorithms (MAs which differ in the construction of initial population and restart strategy, and a double variable neighborhood search algorithm for solving the RCPSP problem. An experiment is conducted to evaluate the performance of these algorithms based on the same number of solutions calculated using ProGen generated benchmark instances. The results indicate that the MAs with regret biased sampling rule to generate initial and restart populations outperforms the other algorithms in terms of solution quality.
A hybrid flow shop model for an ice cream production scheduling problem
Directory of Open Access Journals (Sweden)
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.
Mentaschi, Lorenzo; Vousdoukas, Michalis; Voukouvalas, Evangelos; Sartini, Ludovica; Feyen, Luc; Besio, Giovanni; Alfieri, Lorenzo
2016-09-01
Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are
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.
A Multiobjective Iterated Greedy Algorithm for Truck Scheduling in Cross-Dock Problems
Directory of Open Access Journals (Sweden)
B. Naderi
2014-01-01
Full Text Available The cross-docking system is a new distribution strategy which can reduce inventories, lead times, and improve responding time to customers. This paper considers biobjective problem of truck scheduling in cross-docking systems with temporary storage. The objectives are minimizing both makespan and total tardiness. For this problem, it proposes a multiobjective iterated greedy algorithm employing advance features such as modified crowding selection, restart phase, and local search. To evaluate the proposed algorithm for performance, it is compared with two available algorithms, subpopulation particle swarm optimization-II and strength Pareto evolutionary algorithm-II. The comparison shows that the proposed multiobjective iterated greedy algorithm shows high performance and outperforms the other two algorithms.
Mathematical Model and Algorithm for the Reefer Mechanic Scheduling Problem at Seaports
Directory of Open Access Journals (Sweden)
Jiantong Zhang
2017-01-01
Full Text Available With the development of seaborne logistics, the international trade of goods transported in refrigerated containers is growing fast. Refrigerated containers, also known as reefers, are used in transportation of temperature sensitive cargo, such as perishable fruits. This trend brings new challenges to terminal managers, that is, how to efficiently arrange mechanics to plug and unplug power for the reefers (i.e., tasks at yards. This work investigates the reefer mechanics scheduling problem at container ports. To minimize the sum of the total tardiness of all tasks and the total working distance of all mechanics, we formulate a mathematical model. For the resolution of this problem, we propose a DE algorithm which is combined with efficient heuristics, local search strategies, and parameter adaption scheme. The proposed algorithm is tested and validated through numerical experiments. Computational results demonstrate the effectiveness and efficiency of the proposed algorithm.
Directory of Open Access Journals (Sweden)
Souad Mekni
2014-11-01
Full Text Available In this paper, a modified invasive weed optimization (IWO algorithm is presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs with the criteria to minimize the maximum completion time (makespan, the total workload of machines and the workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour of weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solve continuous optimization problems that’s why the heuristic rule the Smallest Position Value (SPV is used to convert the continuous position values to the discrete job sequences. The computational experiments show that the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it is able to find the optimal and best-known solutions on the instances studied.
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.
Directory of Open Access Journals (Sweden)
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.
Quasi-periodic non-stationary solutions of 3D Euler equations for incompressible flow
Ershkov, Sergey V
2015-01-01
A novel derivation of non-stationary solutions of 3D Euler equations for incompressible inviscid flow is considered here. Such a solution is the product of 2 separated parts: - one consisting of the spatial component and the other being related to the time dependent part. Spatial part of a solution could be determined if we substitute such a solution to the equations of motion (equation of momentum) with the requirement of scale-similarity in regard to the proper component of spatial velocity. So, the time-dependent part of equations of momentum should depend on the time-parameter only. The main result, which should be outlined, is that the governing (time-dependent) ODE-system consist of 2 Riccati-type equations in regard to each other, which has no solution in general case. But we obtain conditions when each component of time-dependent part is proved to be determined by the proper elliptical integral in regard to the time-parameter t, which is a generalization of the class of inverse periodic functions.
Flame generation and maintenance by non-stationary discharge in mixture of air and natural gas
Medeiros, Henrique De Souza; Sagas, Julio; Lacava, Pedro
2013-09-01
Plasma assisted combustion is a promising research field, where the high generation of reactive species by non-equilibrium plasmas is used to modify the combustion kinetics in order to improve the process either by increasing the production of specific species (like molecular hydrogen) or by decreasing pollutant emission. One typical issue observed in plasma assisted combustion is the increase of inflammability limits, i.e the observation of combustion and flame in situation where it is not observed in conventional combustion. To study the effect of a non-stationary discharge in flame generation and maintenance in a mixture for air and natural gas, the air mass flow rate was fixed in 0.80 g/s and the natural gas flow rate was varied between 0.02 and 0.14 g/s, resulting in a variation of equivalence ratio from 0.4 to 3.0. It is observed a dependence of inflammability limits with the applied power. The analysis by mass spectrometry indicates that the increase of inflammability limits with plasma is due not only applied power, but also to hydrogen production in the discharge. Visual analysis together with high speed camera measurements show a modification in spatial distribution of the flame, probably due to modifications both in flow velocity and flame velocity. Supported by FAPESP PRONEX project grant 11/50773-0.
A Review of ENSO Influence on the North Atlantic. A Non-Stationary Signal
Directory of Open Access Journals (Sweden)
Belén Rodríguez-Fonseca
2016-06-01
Full Text Available The atmospheric seasonal cycle of the North Atlantic region is dominated by meridional movements of the circulation systems: from the tropics, where the West African Monsoon and extreme tropical weather events take place, to the extratropics, where the circulation is dominated by seasonal changes in the jetstream and extratropical cyclones. Climate variability over the North Atlantic is controlled by various mechanisms. Atmospheric internal variability plays a crucial role in the mid-latitudes. However, El Niño-Southern Oscillation (ENSO is still the main source of predictability in this region situated far away from the Pacific. Although the ENSO influence over tropical and extra-tropical areas is related to different physical mechanisms, in both regions this teleconnection seems to be non-stationary in time and modulated by multidecadal changes of the mean flow. Nowadays, long observational records (greater than 100 years and modeling projects (e.g., CMIP permit detecting non-stationarities in the influence of ENSO over the Atlantic basin, and further analyzing its potential mechanisms. The present article reviews the ENSO influence over the Atlantic region, paying special attention to the stability of this teleconnection over time and the possible modulators. Evidence is given that the ENSO–Atlantic teleconnection is weak over the North Atlantic. In this regard, the multidecadal ocean variability seems to modulate the presence of teleconnections, which can lead to important impacts of ENSO and to open windows of opportunity for seasonal predictability.
Some strange numerical solutions of the non-stationary Navier-Stokes equations in pipes
Energy Technology Data Exchange (ETDEWEB)
Rummler, B.
2001-07-01
A general class of boundary-pressure-driven flows of incompressible Newtonian fluids in three-dimensional pipes with known steady laminar realizations is investigated. Considering the laminar velocity as a 3D-vector-function of the cross-section-circle arguments, we fix the scale for the velocity by the L{sub 2}-norm of the laminar velocity. The usual new variables are introduced to get dimension-free Navier-Stokes equations. The characteristic physical and geometrical quantities are subsumed in the energetic Reynolds number Re and a parameter {psi}, which involves the energetic ratio and the directions of the boundary-driven part and the pressure-driven part of the laminar flow. The solution of non-stationary dimension-free Navier-Stokes equations is sought in the form u=u{sub L}+u, where u{sub L} is the scaled laminar velocity and periodical conditions in center-line-direction are prescribed for u. An autonomous system (S) of ordinary differential equations for the time-dependent coefficients of the spatial Stokes eigenfunction is got by application of the Galerkin-method to the dimension-free Navier-Stokes equations for u. The finite-dimensional approximations u{sub N({lambda}}{sub )} of u are defined in the usual way. (orig.)
Family of 2n-Point Ternary Non-Stationary Interpolating Subdivision Scheme
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MEHWISH BARI
2017-10-01
Full Text Available This article offers 2n-point ternary non-stationary interpolating subdivision schemes, with the tension parameter, by using Lagrange identities. By choosing the suitable value of tension parameter, we can get different limit curves according to our own choice. Tightness or looseness of the limit curve depends upon the increment or decline the value of tension parameter. The proposed schemes are the counter part of some existing parametric and non-parametric stationary schemes. The main purpose of this article is to reproduce conics and the proposed schemes reproduce conics very well such that circle, ellipse, parabola and hyperbola. We also establish a deviation error formula which is useful to calculate the maximum deviation of limit curve from the original limit curve. The presentation and of the proposed schemes are verified by closed and open figures. The given table shows the less deviation of the limit curves by proposed scheme as compare to the existing scheme. Graphical representation of deviation error is also presented and it shows that as the number of control points increases, the deviation error decreases.
Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations.
Directory of Open Access Journals (Sweden)
Rodrigo Wiff
Full Text Available The food consumption to biomass ratio (C is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed.
Institute of Scientific and Technical Information of China (English)
DU XiuLi; WANG FengQuan
2009-01-01
A new time-domain modal identification method of linear time-lnvariant system driven by the non-stationary Gaussian random excitation is introduced based on the continuous time AR model.The method can identify physical parameters of the system from response data.In order to identify the parameters of the system, the structural dynamic equation is first transformed into the continuous time AR model, and subsequently written into the forms of observation equation and state equation which is just a stochastic differential equation.Secondly, under the assumption that the uniformly modulated function is approximately equal to a constant matrix in a very short time period, the uniformly modulated func-tion is identified piecewise.Then, we present the exact maximum likelihood estimators of parameters by virtue of the Girsanov theorem.Finally, the modal parameters are identified by eigenanalysis.Nu-merical results show that the method we introduce here not only has high precision and robustness, but also has very high computing efficiency.Therefore, it is suitable for real-time modal identification.
Extreme-Point Symmetric Mode Decomposition Method for Nonlinear and Non-Stationary Signal Processing
Wang, Jin-Liang
2013-01-01
To process nonlinear and non-stationary signals, an extreme-point symmetric mode decomposition (ESMD) method is developed. It can be seen as a new alternate of the well-known Hilbert-Huang transform (HHT) method which is widely used nowadays. There are two parts for it. The first part is the decomposition approach which yields a series of intrinsic mode functions (IMFs) together with an optimal adaptive global mean (AGM) curve, the second part is the direct interpolating (DI) approach which yields instantaneous amplitudes and frequencies for the IMFs together with a time-varying energy. Relative to the HHT method it has five characteristics as follows: (1) Different from constructing 2 outer envelopes, its sifting process is implemented by the aid of 1, 2 or 3 inner interpolating curves; (2) It does not decompose the signal to the last trend curve with at most one extreme point, it optimizes the residual component to be an optimal AGM curve which possesses a certain number of extreme points; (3) Its symmetry ...
Isotopically non-stationary metabolic flux analysis: complex yet highly informative.
Wiechert, Wolfgang; Nöh, Katharina
2013-12-01
Metabolic flux analysis (MFA) using isotopic tracers aims at the experimental determination of in vivo reaction rates (fluxes). In recent years, the well-established 13C-MFA method based on metabolic and isotopic steady state was extended to INST-MFA (isotopically non-stationary MFA), which is performed in a transient labeling state. INST-MFA offers short-time experiments with a maximal information gain, and can moreover be applied to a wider range of growth conditions or organisms. Some of these conditions are not accessible by conventional methods. This comes at the price of significant methodological complexity involving high-frequency sampling and quenching, precise analysis of many samples and an extraordinary computational effort. This review gives a brief overview of basic principles, experimental workflows, and recent progress in this field. Special emphasis is laid on the trade-off between total effort and information gain, particularly on the suitability of INST-MFA for certain types of biological questions. In order to integrate INST-MFA as a viable method into the toolbox of MFA, some major challenges must be addressed in the coming years. These are discussed in the outlook. Copyright © 2013 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Caceres, Manuel O [Abdus Salam International Centre for Theoretical Physics, Strada Costiera, 11-34014 Trieste (Italy); Lobos, Alejandro M [Centro Atomico Bariloche, Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, and CONICET, Av E Bustillo Km 9.5, 8400 Bariloche (Argentina)
2006-02-17
We present an eigenvalue theory to study the stochastic dynamics of non-stationary time-periodic Markov processes. The analysis is carried out by solving an integral operator of the Fredholm type, i.e. considering complex-valued functions fulfilling the Kolmogorov compatibility condition. We show that the asymptotic behaviour of the stochastic process is characterized by the smaller time-scale associated with the spectrum of the Kolmogorov operator. The presence of time-periodic elements in the evolution equation for the semigroup leads to a Floquet analysis. The first non-trivial Kolmogorov's eigenvalue is interpreted from a physical point of view. This non-trivial characteristic time-scale strongly depends on the interplay between the stochastic behaviour of the process and the time-periodic structure of the Fokker-Planck equation for continuous processes, or the periodically modulated master equation for discrete Markov processes. We present pedagogical examples in a finite-dimensional vector space to calculate the Kolmogorov characteristic time-scale for discrete Markov processes.
Non-Stationary Dynamics Data Analysis with Wavelet-Svd Filtering
Brenner, M. J.
2003-07-01
Non-stationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular-value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied. The primary objective is the automation of time-frequency analysis with modal system identification. The contribution is a more general approach in which distinct analysis tools are merged into a unified procedure for linear and non-linear data analysis. This method is first applied to aeroelastic pitch-plunge wing section models. Instability is detected in the linear system, and non-linear dynamics are observed from the time-frequency map and parameter estimates of the non-linear system. Aeroelastic and aeroservoelastic flight data from the drone for aerodynamic and structural testing and F18 aircraft are also investigated and comparisons made between the SVD and TSVD results. Input-output data are used to show that this process is an efficient and reliable tool for automated on-line analysis. Published by Elsevier Science Ltd.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
A new time-domain modal identification method of linear time-invariant system driven by the non-stationary Gaussian random excitation is introduced based on the continuous time AR model. The method can identify physical parameters of the system from response data. In order to identify the parameters of the system, the structural dynamic equation is first transformed into the continuous time AR model, and subsequently written into the forms of observation equation and state equation which is just a stochastic differential equation. Secondly, under the assumption that the uniformly modulated function is approximately equal to a constant matrix in a very short time period, the uniformly modulated function is identified piecewise. Then, we present the exact maximum likelihood estimators of parameters by virtue of the Girsanov theorem. Finally, the modal parameters are identified by eigenanalysis. Numerical results show that the method we introduce here not only has high precision and robustness, but also has very high computing efficiency. Therefore, it is suitable for real-time modal identification.
Speech Detection in Non-Stationary Noise Based on the 1/f Process
Institute of Scientific and Technical Information of China (English)
WANG Fan(王帆); ZHENG Fang(郑方); WUWenhx (吴文虎)
2002-01-01
In this paper, an effective and robust active speech detection method is proposed based on the 1/f process technique for signals under non-stationary noisy environments.The Gaussian 1/f process, a mathematical model for statistically self-similar random processes based on fractals, is selected to model both the speech and the background noise. An optimal Bayesian two-class classifier is developed to discriminate them by their 1/f wavelet coefficients with Karhunen-Loeve-type properties. Multiple templates are trained for the speech signal, and the parameters of the background noise can be dynamically adapted in runtime to model the variation of both the speech and the noise. In our experiments, a 10-minute long speech with different types of noises ranging from 20dB to 5dB is tested using this new detection method.A high performance with over 90% detection accuracy is achieved when average SNR is about 10dB.
Analysis of non-stationary turbulent flows using Multivariate EMD and Matching Pursuits
Mohan, Arvind; Agostini, Lionel; Gaitonde, Datta; Visbal, Miguel
2016-11-01
Time-series analysis of highly transient non-stationary turbulent flow is challenging. Traditional Fourier based techniques are generally difficult to apply because of the highly aperiodic nature of the data. Another significant obstacle is assimilating multivariate data, such as multiple variables at a location or from different sources in a flow-field. Such an analysis has the potential to identify sensitive events common among these sources. In this work, we explore two techniques to address these challenges - Multivariate Empirical Mode Decomposition and Matching Pursuits, on deep dynamic stall of a plunging airfoil in a mixed laminar-transitional-turbulent regime. Although primarily used for neuroscience applications, we use them in fluid mechanics and highlight their significant potential to overcome limitations of more traditional techniques. Application of these methods highlight different stages in the development of stall. A first stage shows development of 2-D boundary layer oscillations at frequencies similar to those associated with trailing edge vortices. Subsequently, new instabilities arise due to imminent separation. The separation bubble itself is characterized by relatively higher frequency content, and further analysis indicates its 3-D collapse.
Feng, Ke; Wang, KeSheng; Zhang, Mian; Ni, Qing; Zuo, Ming J.
2017-03-01
The planetary gearbox, due to its unique mechanical structures, is an important rotating machine for transmission systems. Its engineering applications are often in non-stationary operational conditions, such as helicopters, wind energy systems, etc. The unique physical structures and working conditions make the vibrations measured from planetary gearboxes exhibit a complex time-varying modulation and therefore yield complicated spectral structures. As a result, traditional signal processing methods, such as Fourier analysis, and the selection of characteristic fault frequencies for diagnosis face serious challenges. To overcome this drawback, this paper proposes a signal selection scheme for fault-emphasized diagnostics based upon two order tracking techniques. The basic procedures for the proposed scheme are as follows. (1) Computed order tracking is applied to reveal the order contents and identify the order(s) of interest. (2) Vold-Kalman filter order tracking is used to extract the order(s) of interest—these filtered order(s) constitute the so-called selected vibrations. (3) Time domain statistic indicators are applied to the selected vibrations for faulty information-emphasized diagnostics. The proposed scheme is explained and demonstrated in a signal simulation model and experimental studies and the method proves to be effective for planetary gearbox fault diagnosis.
Li, Chuan; Wang, Linghua; Su, Wei; Fang, Cheng
2014-01-01
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft $WIND$ and $GOES$. Both the WTDs of solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail $\\sim \\Delta t^{-\\gamma}$. The SEEs display a broken power-law WTD. The power-law index is $\\gamma_{1} =$ 0.99 for the short waiting times ($$100 hours). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions (CIRs). The power-law index $\\gamma \\sim$ 1.82 is derived for the WTD of SPEs that is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process which was proposed to understand the waiting time statistics of solar flares (Wheatland 2000; Aschwanden $\\&$ McTiernan 2010). We generalize the method and find that, if the SEP event rate $\\lambda = 1/\\Delt...
Institute of Scientific and Technical Information of China (English)
Chen Yu-Dong; Li Li; Zhang Yi; Hu Jian-Ming
2009-01-01
In the study of complex networks(systems),the scaling phenomenon of flow fluctuations rears to a certain power law between the mean flux(activity)(Fi)of the i-th node and its variance σi as σi ∝((Fi)α.Such scaling laws are found to be prevalent both in natural and man-made network systems,but the understanding of their origins still remains limited.This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon:the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems.The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model.Numerical experiments show that the proposed model can recover the multi-scaling phenomenon.
Franco, Glaura C.; Reisen, Valderio A.
2007-03-01
This paper deals with different bootstrap approaches and bootstrap confidence intervals in the fractionally autoregressive moving average (ARFIMA(p,d,q)) process [J. Hosking, Fractional differencing, Biometrika 68(1) (1981) 165-175] using parametric and semi-parametric estimation techniques for the memory parameter d. The bootstrap procedures considered are: the classical bootstrap in the residuals of the fitted model [B. Efron, R. Tibshirani, An Introduction to the Bootstrap, Chapman and Hall, New York, 1993], the bootstrap in the spectral density function [E. Paparoditis, D.N Politis, The local bootstrap for periodogram statistics. J. Time Ser. Anal. 20(2) (1999) 193-222], the bootstrap in the residuals resulting from the regression equation of the semi-parametric estimators [G.C Franco, V.A Reisen, Bootstrap techniques in semiparametric estimation methods for ARFIMA models: a comparison study, Comput. Statist. 19 (2004) 243-259] and the Sieve bootstrap [P. Bühlmann, Sieve bootstrap for time series, Bernoulli 3 (1997) 123-148]. The performance of these procedures and confidence intervals for d in the stationary and non-stationary ranges are empirically obtained through Monte Carlo experiments. The bootstrap confidence intervals here proposed are alternative procedures with some accuracy to obtain confidence intervals for d.
NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Based on the theory of adaptive time-frequency decomposition and Time-Frequency Distribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. According to the input signal features, an appropriate kind of elementary functions with great concentration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using elementary function TF curve surface to fit the input signal's TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal's dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vibrating signal.
Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations.
Wiff, Rodrigo; Roa-Ureta, Ruben H; Borchers, David L; Milessi, Andrés C; Barrientos, Mauricio A
2015-01-01
The food consumption to biomass ratio (C) is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed.
Non-stationary model residuals: information, disinformation and measures of information
Beven, K.
2012-12-01
We expect error in applying hydrological models. They are approximate representations of hydrological processes, driven by approximate estimates of boundary fluxes and compared against uncertain observations of discharge (and perhaps other observables). We should expect, from the nonlinear dynamics of hydrological responses and the epistemic nature of many of the sources of uncertainty, that the residuals should be non-stationary in character. This suggests that it might be difficult to find a simple representation of the error characteristics that could be used, for example, to define a likelihood function for parameter estimation. This is often ignored: the likelihood functions used in hydrology have generally been simple, aleatory and stationary (albeit that this is not a conceptual limitation - as one referee put it, in principle an error model can be infinitely complex!). However, the epistemic nature of the uncertainty does raise the issue of how far nonstationary model residuals might be informative about change in the system and how far they reflect epistemic disinformation in inferring the true nature of the system. Some periods of potential calibration data are clearly disinformative in inference (even if informative about observational techniques), but other unusual events might be particularly revealing about the process responses. Is it therefore possible to define measures of information that can reflect some of these difficulties prior to running a model, or must we resort to data assimilation conditional on a model in detecting nonstationarity?
LMXB X-ray Transients: Revealing Basic Accretion Parameters in Non-stationary Regimes
Yu, Wenfei; Yan, Zhen; Zhang, Hui; Zhang, Wenda
2014-08-01
X-ray observations of low mass X-ray binaries(LMXBs), especially those black hole transient systems, have been very important in shaping up our understanding of black hole accretion and testing accretion theory in a broad range of accretion regimes. We show strong evidence for non-stationary accretion regimes in the X-ray observations of spectral states and multi-wavelength observations of disk-jet coupling in more than 100 outbursts of 36 black hole and neutron star transients in the past decade or so. The occurrence of spectral state transitions and the peak episodic jet power during the rising phase of transient outbursts are found correlated with rate-of-increase of the X-ray luminosity, indicating the rate-of-change of the mass accretion rate, in addition to the mass accretion rate, must be considered when interpreting observations of spectral state transitions and disk-jet coupling in these X-ray transients. This is supported by observations since the increase of the mass accretion rate due to its rate-of-change on the observational time scale of interest is significant during outbursts.
Directory of Open Access Journals (Sweden)
V. Oladokun
2011-12-01
Full Text Available Resource-Constrained Project Scheduling Problem (RCPSP is a Non Polynomial (NP - Hard optimization problem that considers how to assign activities to available resources in order to meet predefined objectives. The problem is usually characterized by precedence relationship between activities with limited capacity of renewable resources. In an environment where resources are limited, projects still have to be finished on time, within the approved budget and in accordance with the preset specifications. Inherently, these tend to make RCPSP, a multi-objective problem. However, it has been treated as a single objective problem with project makespan often recognized as the most relevant objective. As a result of not understanding the multi-objective dimension of some projects, where these objectives need to be simultaneously considered, distraction and conflict of interest have ultimately lead to abandoned or totally failed projects. The aim of this article is to holistically review the relevance and applicability of multi-objective performance dimension of RCPSP in an environment where optimal use of limited resources is important.
Directory of Open Access Journals (Sweden)
Yan Sun
2015-01-01
Full Text Available We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1 multicommodity flow routing; (2 a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3 carbon dioxide emissions consideration; and (4 a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.
A Heuristic Genetic Algorithm for No-Wait Flowshop Scheduling Problem
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
No-wait flowshop scheduling problems with the objective to minimize the total flow time is an important sequencing problem in the field of developing production plans and has a wide engineering background.Genetic algorithm (GA) has the capability of global convergence and has been proven effective to solve NP-hard combinatorial optimization problems, while simple heuristics have the advantage of fast local convergence and can be easily implemented.In order to avoid the defect of slow convergence or premature, a heuristic genetic algorithm is proposed by incorporating the simple heuristics and local search into the traditional genetic algorithm.In this hybridized algorithm, the structural information of no-wait flowshops and high-effective heuristics are incorporated to design a new method for generating initial generation and a new crossover operator.The computational results show the developed heuristic genetic algorithm is efficient and the quality of its solution has advantage over the best known algorithm.It is suitable for solving the large scale practical problems and lays a foundation for the application of meta-heuristic algorithms in industrial production.
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.
Indian Academy of Sciences (India)
P Chitra; P Venkatesh; R Rajaram
2011-04-01
The task scheduling problem in heterogeneous distributed computing systems is a multiobjective optimization problem (MOP). In heterogeneous distributed computing systems (HDCS), there is a possibility of processor and network failures and this affects the applications running on the HDCS. To reduce the impact of failures on an application running on HDCS, scheduling algorithms must be devised which minimize not only the schedule length (makespan) but also the failure probability of the application (reliability). These objectives are conﬂicting and it is not possible to minimize both objectives at the same time. Thus, it is needed to develop scheduling algorithms which account both for schedule length and the failure probability. Multiobjective Evolutionary Computation algorithms (MOEAs) are well-suited for Multiobjective task scheduling on heterogeneous environment. The two Multi-Objective Evolutionary Algorithms such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Evolutionary Programming (MOEP) with non-dominated sorting are developed and compared for the various random task graphs and also for a real-time numerical application graph. The metrics for evaluating the convergence and diversity of the obtained non-dominated solutions by the two algorithms are reported. The simulation results conﬁrm that the proposed algorithms can be used for solving the task scheduling at reduced computational times compared to the weighted-sum based biobjective algorithm in the literature.
A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem
Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad
2010-01-01
Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.
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 Bound Algorithm for Project Scheduling Problem with Spatial Resource Constraints
Directory of Open Access Journals (Sweden)
Shicheng Hu
2015-01-01
Full Text Available With respect to the block assembly schedule in a shipbuilding enterprise, a spatial resource constrained project scheduling problem (SRCPSP is proposed, which aims to minimize the makespan of a project under the constraints of the availability of a two-dimensional spatial resource and the precedence relationship between tasks. In order to solve SRCPSP to the optimum, a branch and bound algorithm (BB is developed. For the BB-SRCPSP, first, an implicitly enumerative branch scheme is presented. Secondly, a precedence based lower bound, as well as an effective dominance rule, is employed for pruning. Next, a heuristic based algorithm is used to decide the order of a node to be selected for expansion such that the efficiency of the algorithm is further improved. In addition, a maximal space based arrangement is applied to the configuration of the areas required each day in an available area. Finally, the simulation experiment is conducted to illustrate the effectiveness of the BB-SRCPSP.
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)
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.
A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series
Pinzon, Jorge E.; Tucker, Compton J.
2014-01-01
The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
Directory of Open Access Journals (Sweden)
Daniel Maposa
2016-03-01
Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate.Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value
Indian Academy of Sciences (India)
Dilip P Ahalpara; Amit Verma; Jiterndra C Parikh; Prasanta K Panigrahi
2008-09-01
A method based on wavelet transform is developed to characterize variations at multiple scales in non-stationary time series. We consider two different financial time series, S&P CNX Nifty closing index of the National Stock Exchange (India) and Dow Jones industrial average closing values. These time series are chosen since they are known to comprise of stochastic fluctuations as well as cyclic variations at different scales. The wavelet transform isolates cyclic variations at higher scales when random fluctuations are averaged out; this corroborates correlated behaviour observed earlier in financial time series through random matrix studies. Analysis is carried out through Haar, Daubechies-4 and continuous Morlet wavelets for studying the character of fluctuations at different scales and show that cyclic variations emerge at intermediate time scales. It is found that Daubechies family of wavelets can be effectively used to capture cyclic variations since these are local in nature. To get an insight into the occurrence of cyclic variations, we then proceed to model these wavelet coefficients using genetic programming (GP) approach and using the standard embedding technique in the reconstructed phase space. It is found that the standard methods (GP as well as artificial neural networks) fail to model these variations because of poor convergence. A novel interpolation approach is developed that overcomes this difficulty. The dynamical model equations have, primarily, linear terms with additive Padé-type terms. It is seen that the emergence of cyclic variations is due to an interplay of a few important terms in the model. Very interestingly GP model captures smooth variations as well as bursty behaviour quite nicely.
A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series
Directory of Open Access Journals (Sweden)
Jorge E. Pinzon
2014-07-01
Full Text Available The NDVI3g time series is an improved 8-km normalized difference vegetation index (NDVI data set produced from Advanced Very High Resolution Radiometer (AVHRR instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
A high-frequency kriging approach for non-stationary environmental processes
Energy Technology Data Exchange (ETDEWEB)
Fuentes, M. [North Carolina State Univ., Raleigh, NC (United States). Dept. of Statistics
2001-07-01
Emission reductions were mandated in the Clean Air Act Amendments of 1990 with the expectation that they would result in major reductions in the concentrations of atmospherically transported pollutants. The emission reductions are intended to reduce public health risks and to protect sensitive ecosystems. To determine whether the emission reductions are having the intended effect on atmospheric concentrations, monitoring data must be analyzed taking into consideration the spatial structure shown by the data. Maps of pollutant concentrations and fluxes are useful over different geopolitical boundaries, to discover when, where, and to what extent the U.S. Nation's air quality is improving or declining. Since the spatial covariance structure shown by the data changes with location, the standard kriging methodology for spatial interpolation cannot be used because it assumes stationarity of the process. We present a new methodology for spatial interpolation of non-stationary processes. In this method the field is represented locally as a stationary isotropic random field, but the parameters of the stationary random field are allowed to vary across space. A procedure for interpolation is presented that uses an expression for the spectral density at high frequencies. New fitting algorithms are developed using spectral approaches. In cases where the data are distributed exactly or approximately on a lattice, it is argued that spectral approaches have potentially enormous computational benefits compared with maximum likelihood. The methods are extended to interpolation questions using approximate Bayesian approaches to account for parameter uncertainty. We develop applications to obtain the total loading of pollutant concentrations and fluxes over different geo-political boundaries. (author)
Kreppel, Katharina S; Caminade, Cyril; Telfer, Sandra; Rajerison, Minoarison; Rahalison, Lila; Morse, Andy; Baylis, Matthew
2014-10-01
Plague, a zoonosis caused by Yersinia pestis, is found in Asia and the Americas, but predominantly in Africa, with the island of Madagascar reporting almost one third of human cases worldwide. Plague's occurrence is affected by local climate factors which in turn are influenced by large-scale climate phenomena such as the El Niño Southern Oscillation (ENSO). The effects of ENSO on regional climate are often enhanced or reduced by a second large-scale climate phenomenon, the Indian Ocean Dipole (IOD). It is known that ENSO and the IOD interact as drivers of disease. Yet the impacts of these phenomena in driving plague dynamics via their effect on regional climate, and specifically contributing to the foci of transmission on Madagascar, are unknown. Here we present the first analysis of the effects of ENSO and IOD on plague in Madagascar. We use a forty-eight year monthly time-series of reported human plague cases from 1960 to 2008. Using wavelet analysis, we show that over the last fifty years there have been complex non-stationary associations between ENSO/IOD and the dynamics of plague in Madagascar. We demonstrate that ENSO and IOD influence temperature in Madagascar and that temperature and plague cycles are associated. The effects on plague appear to be mediated more by temperature, but precipitation also undoubtedly influences plague in Madagascar. Our results confirm a relationship between plague anomalies and an increase in the intensity of ENSO events and precipitation. This work widens the understanding of how climate factors acting over different temporal scales can combine to drive local disease dynamics. Given the association of increasing ENSO strength and plague anomalies in Madagascar it may in future be possible to forecast plague outbreaks in Madagascar. The study gives insight into the complex and changing relationship between climate factors and plague in Madagascar.
Three hybridization models based on local search scheme for job shop scheduling problem
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
An imperialist competitive algorithm for solving the production scheduling problem in open pit mine
Directory of Open Access Journals (Sweden)
Mojtaba Mokhtarian Asl
2016-06-01
Full Text Available Production scheduling (planning of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem.
Energy Technology Data Exchange (ETDEWEB)
Souza Filho, Erito M.; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE); Lima, Leonardo [Centro Federal de Educacao Tecnologica Celso Sukow da Fonseca (CEFET-RJ), Rio de Janeiro, RJ (Brazil)
2008-07-01
Pipeline 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. In this work 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. We propose an integer linear programming formulation and a variable neighborhood search meta-heuristic in order to compare the performances of the exact and heuristic approaches to the problem. Computational tests in C language and MOSEL/XPRESS-MP language are performed over a real Brazilian pipeline system. (author)
Scheduling of flow shop problems on 3 machines in fuzzy environment with double transport facility
Sathish, Shakeela; Ganesan, K.
2016-06-01
Flow shop scheduling is a decision making problem in production and manufacturing field which has a significant impact on the performance of an organization. When the machines on which jobs are to be processed are placed at different places, the transportation time plays a significant role in production. Further two different transport agents where 1st takes the job from 1st machine to 2nd machine and then returns back to the first machine and the 2nd takes the job from 2nd machine to 3rd machine and then returns back to the 2nd machine are also considered. We propose a method to minimize the total make span; without converting the fuzzy processing time to classical numbers by using a new type of fuzzy arithmetic and a fuzzy ranking method. A numerical example is provided to explain the proposed method.
Directory of Open Access Journals (Sweden)
Hui Lu
2014-01-01
Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.
Decision theory for computing variable and value ordering decisions for scheduling problems
Linden, Theodore A.
1993-01-01
Heuristics that guide search are critical when solving large planning and scheduling problems, but most variable and value ordering heuristics are sensitive to only one feature of the search state. One wants to combine evidence from all features of the search state into a subjective probability that a value choice is best, but there has been no solid semantics for merging evidence when it is conceived in these terms. Instead, variable and value ordering decisions should be viewed as problems in decision theory. This led to two key insights: (1) The fundamental concept that allows heuristic evidence to be merged is the net incremental utility that will be achieved by assigning a value to a variable. Probability distributions about net incremental utility can merge evidence from the utility function, binary constraints, resource constraints, and other problem features. The subjective probability that a value is the best choice is then derived from probability distributions about net incremental utility. (2) The methods used for rumor control in Bayesian Networks are the primary way to prevent cycling in the computation of probable net incremental utility. These insights lead to semantically justifiable ways to compute heuristic variable and value ordering decisions that merge evidence from all available features of the search state.
Directory of Open Access Journals (Sweden)
Jianfei Ye
2015-01-01
Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.
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)
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.
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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.
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M. Saravanan
2014-03-01
Full Text Available A Hybrid flow shop scheduling is characterized ‘n’ jobs ‘m’ machines with ‘M’ stages by unidirectional flow of work with a variety of jobs being processed sequentially in a single-pass manner. The paper addresses the multi-stage hybrid flow shop scheduling problems with missing operations. It occurs in many practical situations such as stainless steel manufacturing company. The essential complexity of the problem necessitates the application of meta-heuristics to solve hybrid flow shop scheduling. The proposed Simulated Annealing algorithm (SA compared with Particle Swarm Optimization (PSO with the objective of minimization of makespan. It is show that the SA algorithm is efficient in finding out good quality solutions for the hybrid flow shop problems with missing operations.
Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan
2015-02-01
An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.
Li, Shanlin; Li, Maoqin
2015-01-01
We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time.
Fetterly, Kenneth A.; Favazza, Christopher P.
2016-08-01
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 ({{d}\\prime} ) 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 {{d}\\prime} estimates which were as much as 2.9× greater than expected of a quantum limited system. Over-estimation of {{d}\\prime}Hotelling model observers due to temporally variable non-stationary noise and correct this bias when the temporally variable non-stationary noise is independent and additive with respect to the test object signal.
Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe
2014-07-01
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.
Maslova, N. S.; Mantsevich, V. N.; Arseyev, P. I.
2017-02-01
We perform theoretical investigation of the localized state dynamics in the presence of interaction with the reservoir and Coulomb correlations. We analyze kinetic equations for electron occupation numbers with different spins taking into account high order correlation functions for the localized electrons. We reveal that in the stationary state electron occupation numbers with the opposite spins always have the same value - the stationary state is a "paramagnetic" one. "Magnetic" properties can appear only in the non-stationary characteristics of the single-impurity Anderson model and in the dynamics of the localized electrons second order correlation functions. We found, that for deep energy levels and strong Coulomb correlations, relaxation time for initial "magnetic" state can be several orders larger than for "paramagnetic" one. So, long-living "magnetic" moment can exist in the system. We also found non-stationary spin polarized currents flowing in opposite directions for the different spins in the particular time interval.
Energy Technology Data Exchange (ETDEWEB)
Liu, Yangqing, E-mail: liuyq05@gmail.com; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China)
2014-07-15
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.
Meltzer, G.; Ivanov, Yu. Ye.
2003-03-01
This paper deals with the recognition of faults in toothing during non-stationary start up and run down of gear drives. In the first part, this task was solved by means of the time-frequency analysis. A planetary gear was used as a case study. Part II contains a new approach using the time-quefrency analysis. The same example was successfully subjected in this procedure.
Quantum Radiation of a Non-stationary Kerr-Newman Black Hole in de Sitter Space-Time
Institute of Scientific and Technical Information of China (English)
JIANG Qing-Quan; YANG Shu-Zheng
2006-01-01
Hawking radiation of Klein-Gordon and Dirac particles in a non-stationary Kerr-Newman-de-Sitter black hole is studied by introducing a new tortoise coordinate transformation. The result shows that the Fermi-Dirac radiant spectrum displays a new term that represents the interaction between the spin of spinor particles and the rotation of black holes, which is absent in the Bose-Einstein distribution of Klein-Gordon particles.
Directory of Open Access Journals (Sweden)
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.
Park, Jeryang; Rao, P. Suresh C.
2014-11-01
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.
Energy Technology Data Exchange (ETDEWEB)
Morsi, Walid G. [University of New Brunswick, Fredericton, New Brunswick (Canada); El-Hawary, M.E. [Dalhousie University, Halifax, Nova Scotia (Canada)
2010-07-15
High power quality (PQ) level represents one of the main objectives towards smart grid. The currently used PQIs that are a measure of the PQ level are defined under the umbrella of the Fourier foundation that produces unrealistic results in case of non-stationary PQ disturbances. In order to accurately measure those indices, wavelet packet transform (WPT) is used in this paper to reformulate the recommended PQIs and hence benefiting from the WPT capabilities in accurately analyzing non-stationary waveforms and providing a uniform time-frequency sub-bands leading to reduced size of the data to be processed which is a necessity to facilitate the implementation of smart grid. Numerical examples' results considering non-stationary waveforms prove the suitability of the WPT for PQIs measurement; also the results indicate that Daubechies 10 could be the best candidate wavelet basis function that could provide acceptable accuracy while requiring less number of wavelet coefficients and hence reducing the data size. Moreover, a new time-frequency overall and node crest factors are introduced in this paper. The new node crest factor is able to determine the node or the sub-band that is responsible for the largest impact which could not be achieved using traditional approaches. (author)
Uma Maheswari, R.; Umamaheswari, R.
2017-02-01
Condition Monitoring System (CMS) substantiates potential economic benefits and enables prognostic maintenance in wind turbine-generator failure prevention. Vibration Monitoring and Analysis is a powerful tool in drive train CMS, which enables the early detection of impending failure/damage. In variable speed drives such as wind turbine-generator drive trains, the vibration signal acquired is of non-stationary and non-linear. The traditional stationary signal processing techniques are inefficient to diagnose the machine faults in time varying conditions. The current research trend in CMS for drive-train focuses on developing/improving non-linear, non-stationary feature extraction and fault classification algorithms to improve fault detection/prediction sensitivity and selectivity and thereby reducing the misdetection and false alarm rates. In literature, review of stationary signal processing algorithms employed in vibration analysis is done at great extent. In this paper, an attempt is made to review the recent research advances in non-linear non-stationary signal processing algorithms particularly suited for variable speed wind turbines.
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.
Institute of Scientific and Technical Information of China (English)
HE Yan; LIU Fei; CAO Hua-jun; LI Cong-bo
2005-01-01
The issue of reducing energy consumption for the job-shop scheduling problem in machining systems is addressed, whose dual objectives are to minimize both the energy consumption and the makespan. First, the biobjective model for the job-shop scheduling problem is proposed. The objective function value of the model represents synthesized optimization of energy consumption and makespan. Then, a heuristic algorithm is developed to locate the optimal or near optimal solutions of the model based on the Tabu search mechanism. Finally, the experimental case is presented to demonstrate the effectiveness of the proposed model and the algorithm.
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.
Memetic algorithm for multi-mode resource-constrained project scheduling problems
Institute of Scientific and Technical Information of China (English)
Shixin Liu; Di Chen; Yifan Wang
2014-01-01
A memetic algorithm (MA) for a multi-mode resource-constrained project scheduling problem (MRCPSP) is pro-posed. We use a new fitness function and two very effective lo-cal search procedures in the proposed MA. The fitness function makes use of a mechanism cal ed “strategic oscil ation” to make the search process have a higher probability to visit solutions around a“feasible boundary”. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A de-tailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
Numerical Estimation Method for the NonStationary Thrust of Pulsejet Ejector Nozzle
Directory of Open Access Journals (Sweden)
A. Yu. Mikushkin
2016-01-01
Full Text Available The article considers a calculation method for the non-stationary thrust of pulsejet ejector nozzle that is based on detonation combustion of gaseous fuel.To determine initial distributions of the thermodynamic parameters inside the detonation tube was carried out a rapid analysis based on x-t-diagrams of motion of glowing combustion products. For this purpose, the section with transparent walls was connected to the outlet of the tube to register the movement of products of combustion.Based on obtained images and gas-dynamic and thermodynamic equations the velocity distribution of the combustion products, its density, pressure and temperature required for numerical analysis were calculated. The world literature presents data on distribution of parameters, however they are given only for direct initiation of detonation at the closed end and for chemically "frozen" gas composition. The article presents the interpolation methods of parameters measured at the temperatures of 2500-2800K.Estimation of the thermodynamic parameters is based on the Chapman-Jouguet theory that the speed of the combustion products directly behind the detonation wave front with respect to the wave front is equal to the speed of sound of these products at a given point. The method of minimizing enthalpy of the final thermodynamic state was used to calculate the equilibrium parameters. Thus, a software package «IVTANTHERMO», which is a database of thermodynamic properties of many individual substances in a wide temperature range, was used.An integral thrust was numerically calculated according to the ejector nozzle surface. We solved the Navier-Stokes equations using the finite-difference Roe scheme of the second order. The combustion products were considered both as an inert mixture with "frozen" composition and as a mixture in chemical equilibrium with the changing temperature. The comparison with experimental results was made.The above method can be used for rapid
Active visual search in non-stationary scenes: coping with temporal variability and uncertainty
Ušćumlić, Marija; Blankertz, Benjamin
2016-02-01
Objective. State-of-the-art experiments for studying neural processes underlying visual cognition often constrain sensory inputs (e.g., static images) and our behavior (e.g., fixed eye-gaze, long eye fixations), isolating or simplifying the interaction of neural processes. Motivated by the non-stationarity of our natural visual environment, we investigated the electroencephalography (EEG) correlates of visual recognition while participants overtly performed visual search in non-stationary scenes. We hypothesized that visual effects (such as those typically used in human-computer interfaces) may increase temporal uncertainty (with reference to fixation onset) of cognition-related EEG activity in an active search task and therefore require novel techniques for single-trial detection. Approach. We addressed fixation-related EEG activity in an active search task with respect to stimulus-appearance styles and dynamics. Alongside popping-up stimuli, our experimental study embraces two composite appearance styles based on fading-in, enlarging, and motion effects. Additionally, we explored whether the knowledge obtained in the pop-up experimental setting can be exploited to boost the EEG-based intention-decoding performance when facing transitional changes of visual content. Main results. The results confirmed our initial hypothesis that the dynamic of visual content can increase temporal uncertainty of the cognition-related EEG activity in active search with respect to fixation onset. This temporal uncertainty challenges the pivotal aim to keep the decoding performance constant irrespective of visual effects. Importantly, the proposed approach for EEG decoding based on knowledge transfer between the different experimental settings gave a promising performance. Significance. Our study demonstrates that the non-stationarity of visual scenes is an important factor in the evolution of cognitive processes, as well as in the dynamic of ocular behavior (i.e., dwell time and
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.
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.
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
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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.
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M.G. Baldoquin de la Peña
2014-06-01
Full Text Available Some of the complex logistical problems faced by companies combine the needs for strategic and tactical decisions concerning the interrelated issues of clustering, scheduling, and routing. Various strategies can be used to solve these problems. We present a problem of this type, involving a company whose fundamental objective is the commercialization of its product in the domestic market. The paper focuses on a model of and method for a solution to the problem of scheduling visits to customers, taking into account the relationship with other phases of product marketing. The model is nonlinear, involves binary and continuous variables, and solved heuristically. Computational experiments show that the proposed solution performed very well for both real-life and theoretical instances.
EA/G-GA for Single Machine Scheduling Problems with Earliness/Tardiness Costs
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Yuh-Min Chen
2011-06-01
Full Text Available An Estimation of Distribution Algorithm (EDA, which depends on explicitly sampling mechanisms based on probabilistic models with information extracted from the parental solutions to generate new solutions, has constituted one of the major research areas in the field of evolutionary computation. The fact that no genetic operators are used in EDAs is a major characteristic differentiating EDAs from other genetic algorithms (GAs. This advantage, however, could lead to premature convergence of EDAs as the probabilistic models are no longer generating diversified solutions. In our previous research [1], we have presented the evidences that EDAs suffer from the drawback of premature convergency, thus several important guidelines are provided for the design of effective EDAs. In this paper, we validated one guideline for incorporating other meta-heuristics into the EDAs. An algorithm named “EA/G-GA” is proposed by selecting a well-known EDA, EA/G, to work with GAs. The proposed algorithm was tested on the NP-Hard single machine scheduling problems with the total weighted earliness/tardiness cost in a just-in-time environment. The experimental results indicated that the EA/G-GA outperforms the compared algorithms statistically significantly across different stopping criteria and demonstrated the robustness of the proposed algorithm. Consequently, this paper is of interest and importance in the field of EDAs.
Improved Hysteretic Noisy Chaotic Neural Network for Broadcast Scheduling Problem in WMNs
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Ming Sun
2013-01-01
Full Text Available It has been proven that the noise-tuning-based hysteretic noisy chaotic neural network (NHNCNN can use the noise tuning factor to improve the optimization performance obviously at lower initial noise levels while can not at initial higher noise levels. In order to improve the optimization performance of the NHNCNN at initial higher noise levels, we introduce a new noise tuning factor into the activation function and propose an improved hysteretic noisy chaotic neural network (IHNCNN model. By regulating the value of the newly introduced noise tuning factor, both noise levels of the activation function and hysteretic dynamics in the IHNCNN can be adjusted to help to improve the global optimization ability as the initial noise amplitude is higher. As a result, the IHNCNN can exhibit better optimization performance at initial higher noise levels. In order to demonstrate the advantage of the IHNCNN over the NHNCNN, the IHNCNN combined with gradual expansion scheme (GES is applied to solve broadcast scheduling problem (BSP in wireless multihop networks (WMNs. The aim of BSP is to design an optimal time-division multiple-access (TDMA frame structure with minimal frame length and maximal channel utilization. Simulation results in BSP show the superiority of the IHNCNN.
Parallel genetic algorithms with migration for the hybrid flow shop scheduling problem
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K. Belkadi
2006-01-01
Full Text Available This paper addresses scheduling problems in hybrid flow shop-like systems with a migration parallel genetic algorithm (PGA_MIG. This parallel genetic algorithm model allows genetic diversity by the application of selection and reproduction mechanisms nearer to nature. The space structure of the population is modified by dividing it into disjoined subpopulations. From time to time, individuals are exchanged between the different subpopulations (migration. Influence of parameters and dedicated strategies are studied. These parameters are the number of independent subpopulations, the interconnection topology between subpopulations, the choice/replacement strategy of the migrant individuals, and the migration frequency. A comparison between the sequential and parallel version of genetic algorithm (GA is provided. This comparison relates to the quality of the solution and the execution time of the two versions. The efficiency of the parallel model highly depends on the parameters and especially on the migration frequency. In the same way this parallel model gives a significant improvement of computational time if it is implemented on a parallel architecture which offers an acceptable number of processors (as many processors as subpopulations.
A hierarchical scheduling problem with a well-solvable second stage
J.B.G. Frenk (Hans); A.H.G. Rinnooy Kan (Alexander); L. Stougie (Leen)
1984-01-01
textabstractIn the hierarchical scheduling model to be considered, the decision at the aggregate level to acquire a number of identical machines has to be based on probabilistic information about the jobs that have to be scheduled on these machines at the detailed level. The objective is to minimize
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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
Minimizing makespan in a two-stage hybrid flow shop scheduling problem with open shop in one stage
Institute of Scientific and Technical Information of China (English)
DONG Jian-ming; HU Jue-liang; CHEN Yong
2013-01-01
This paper considers a scheduling problem in two-stage hybrid flow shop, where the first stage consists of two machines formed an open shop and the other stage has only one machine. The objective is to minimize the makespan, i.e., the maximum completion time of all jobs. We first show the problem is NP-hard in the strong sense, then we present two heuristics to solve the problem. Computational experiments show that the combined algorithm of the two heuristics performs well on randomly generated problem instances.
Lahimer, Asma; Haouari, Mohamed
2011-01-01
This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The problem even in its simplest form is NP-hard in the strong sense. The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems. We propose a new approach based on limited discrepancy search to solve the problem. Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature. Computational results show that the developed approach is efficient in particular for large-size problems.
Birgin, Ernesto G.; Ronconi, Débora P.
2012-10-01
The single machine scheduling problem with a common due date and non-identical ready times for the jobs is examined in this work. Performance is measured by the minimization of the weighted sum of earliness and tardiness penalties of the jobs. Since this problem is NP-hard, the application of constructive heuristics that exploit specific characteristics of the problem to improve their performance is investigated. The proposed approaches are examined through a computational comparative study on a set of 280 benchmark test problems with up to 1000 jobs.
Michas, G.; Vallianatos, F.; Sammonds, P. R.
2014-12-01
Earthquake time series are widely used to characterize the main features of seismicity and to provide useful insights into the dynamics of the seismogenic system. Properties such as fractality/multifractality, intermittency and non-stationary clustering are common in earthquake time series, highlighting the complex nature of the earthquake generation process. Here we use statistical physics to study the temporal properties of the earthquake activity in one of the most seismically active areas in Europe, the Corinth rift (central Greece). The earthquake activity in the Corinth rift is typically characterized by fluctuating behavior, where periods of low to moderate activity are interspersed by sudden seismic bursts, which are related to frequent earthquake swarms and the occurrence of stronger events, followed by aftershock sequences. A multifractal analysis reveals the degree of heterogeneous clustering in the earthquake activity and correlations acting at all time-scales that suggest non-Poissonian behavior. These properties are also displayed in the probability density function of the scaled inter-event times (i.e. the time intervals between the successive earthquakes), where for various time periods and threshold magnitudes the distribution presents scaling and two power-law regions at both short and long time intervals. In addition, we use generalized statistical physics and a stochastic dynamical mechanism with memory effects to model this behavior. During stationary periods where the mean inter-event time does not fluctuate, the solution of this mechanism is the gamma distribution, while for non-stationary periods the solution is a q-generalized gamma distribution, which exhibits power-law asymptotic behavior. These properties seem to be fundamental in non-stationary earthquake time series such that they should be considered in probabilistic hazard assessments, especially in localized seismicity where highly nonrandom activity may be expected.
Self-configuring multi-strategy genetic algorithm for non-stationary environments
Sopov, E.
2015-01-01
Many real-world problems of design and control in a field of the aerospace lead to optimization problems. Such optimization problems are complicated and become a great challenge to many optimization techniques. Moreover, many real-world optimization problems are dynamic and changing over time. Changes occur in the parameters, objectives and/or problem constraints. In this case, search algorithms should have the capability to track moving optima and adapt to a new environment. In past years ma...
An Integer Linear Programming Model for the Radiotherapy Treatment Scheduling Problem
Burke, Edmund K; Petrovic, Sanja
2011-01-01
Radiotherapy represents an important phase of treatment for a large number of cancer patients. It is essential that resources used to deliver this treatment are employed effectively. This paper presents a new integer linear programming model for real-world radiotherapy treatment scheduling and analyses the effectiveness of using this model on a daily basis in a hospital. Experiments are conducted varying the days on which schedules can be created. Results obtained using real-world data from the Nottingham University Hospitals NHS Trust, UK, are presented and show how the proposed model can be used with different policies in order to achieve good quality schedules.
Task-Scheduling in Cloud Computing using Credit Based Assignment Problem
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Mousumi Paul
2011-10-01
Full Text Available This Cloud computing is a latest new computing paradigm where applications, data and IT services are provided across dynamic and geographically dispersed organization. Job scheduling systemproblem is a nucleus and demanding issue in Cloud Computing. How to utilize Cloud computing resources proficiently and gain the maximum profits with job scheduling system is one of the Cloud computing service providers’ ultimate objectives. In this paper we have used credit based scheduling decision to evaluate the entire group of task in the task queue and find the minimal completion time of alltask. Here cost matrix has been generated as the fair tendency of a task to be assigned in a resource.
Trunfio, Roberto
2015-06-01
In a recent article, Guo, Cheng and Wang proposed a randomized search algorithm, called modified generalized extremal optimization (MGEO), to solve the quay crane scheduling problem for container groups under the assumption that schedules are unidirectional. The authors claim that the proposed algorithm is capable of finding new best solutions with respect to a well-known set of benchmark instances taken from the literature. However, as shown in this note, there are some errors in their work that can be detected by analysing the Gantt charts of two solutions provided by MGEO. In addition, some comments on the method used to evaluate the schedule corresponding to a task-to-quay crane assignment and on the search scheme of the proposed algorithm are provided. Finally, to assess the effectiveness of the proposed algorithm, the computational experiments are repeated and additional computational experiments are provided.
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A. Shirzadeh Chaleshtarti
2014-01-01
Full Text Available A lot of projects in real life are subject to some kinds of nonrenewable resources that are not exactly similar to the type defined in the project scheduling literature. The difference stems from the fact that, in those projects, contrary to the common assumption in the project scheduling literature, nonrenewable resources are not available in full amount at the beginning of the project, but they are procured along the project horizon. In this paper, we study this different type of nonrenewable resources. To that end, we extend the resource constrained project scheduling problem (RCPSP by this resource type (RCPSP-NR and customize four basic branch and bound algorithms of RCPSP for it, including precedence tree, extension alternatives, minimal delaying alternatives, and minimal forbidden sets. Several bounding and fathoming rules are introduced to the algorithms to shorten the enumeration process. We perform comprehensive experimental analysis using the four customized algorithms and also CPLEX solver.
DEFF Research Database (Denmark)
Åström, Helena Lisa Alexandra; Friis Hansen, P.; Garrè, Luca
2014-01-01
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...... for flooding increases over time, and the benefits of implementing flood adaptation measures....
Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.
Shalymov, Dmitry S; Fradkov, Alexander L
2016-01-01
We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.
Meltzer, G.; Ivanov, Yu Ye
2003-09-01
This paper deals with the recognition of faults in toothing during non-stationary start-up and run-down of gear drives. In the first part, this task will be solved by means of the time-frequency analysis. As a practical case study, we investigated a planetary gear for passenger cars. New exponental smoothing kernels which respect to the known-in-advance angular acceleration of gear drive were created. These kernels must be adapted in the case of an in-advance-unknown course of rotational speed.
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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.
Energy Technology Data Exchange (ETDEWEB)
Costantini, Valeria [Department of Economics, University of Roma Tre, 77 Via Silvio D' Amico, 00145 Rome (Italy); Martini, Chiara [Italian National Agency for New Technologies, Energy and Environment (ENEA), Lungotevere Thaon di Revel, 76-00196 Rome (Italy)
2010-05-15
The increasing attention given to global energy issues and the international policies needed to reduce greenhouse gas emissions have given a renewed stimulus to research interest in the linkages between the energy sector and economic performance at country level. In this paper, we analyse the causal relationship between economy and energy by adopting a Vector Error Correction Model for non-stationary and cointegrated panel data with a large sample of developed and developing countries and four distinct energy sectors. The results show that alternative country samples hardly affect the causality relations, particularly in a multivariate multi-sector framework. (author)
Energy Technology Data Exchange (ETDEWEB)
Costantini, Valeria, E-mail: v.costantini@uniroma3.i [Department of Economics, University of Roma Tre, 77 Via Silvio D' Amico, 00145 Rome (Italy); Martini, Chiara, E-mail: chiara.martini@enea.i [Italian National Agency for New Technologies, Energy and Environment (ENEA), Lungotevere Thaon di Revel, 76-00196 Rome (Italy)
2010-05-15
The increasing attention given to global energy issues and the international policies needed to reduce greenhouse gas emissions have given a renewed stimulus to research interest in the linkages between the energy sector and economic performance at country level. In this paper, we analyse the causal relationship between economy and energy by adopting a Vector Error Correction Model for non-stationary and cointegrated panel data with a large sample of developed and developing countries and four distinct energy sectors. The results show that alternative country samples hardly affect the causality relations, particularly in a multivariate multi-sector framework.
Yang, Shu-Zheng; Feng, Zhong-Wen; Li, Hui-Ling
2017-02-01
We derive the Hamilton-Jacobi equation from the Dirac equation, then, with the help of the Hamilton-Jacobi equation, the the tunneling radiation behavior of the non-stationary spherical symmetry de Sitter black hole is discussed, at last, we obtained the tunneling rate and Hawking temperature. Our results showed that the Hamilton-Jacobi equation is a fundamental dynamic equation, it can widely be derived from the dynamic equations which describe the particles with any spin. Therefore, people can easy calculate the tunneling behavior from the black holes.
Vanden Berghe, Greet
2012-01-01
Personnel scheduling can become a particularly difficult optimisation problem due to human factors. And yet: people working in healthcare, transportation and other round the clock service regimes perform their duties based on a schedule that was often manually constructed. The unrewarding manual scheduling task deserves more attention from the timetabling community so as to support computation of fair and good quality results. The present abstract touches upon a set of particular characterist...
The single-machine scheduling problems with deteriorating jobs and learning effect
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimization and maximum lateness minimization corresponding to the first and second special cases of our model under some agreeable conditions. However,corresponding to the third special case of our model, we show that the optimal schedules may be different from those of the classical version for the above objective functions.
The nurse scheduling problem: a goal programming and nonlinear optimization approaches
Hakim, L.; Bakhtiar, T.; Jaharuddin
2017-01-01
Nurses scheduling is an activity of allocating nurses to conduct a set of tasks at certain room at a hospital or health centre within a certain period. One of obstacles in the nurse scheduling is the lack of resources in order to fulfil the needs of the hospital. Nurse scheduling which is undertaken manually will be at risk of not fulfilling some nursing rules set by the hospital. Therefore, this study aimed to perform scheduling models that satisfy all the specific rules set by the management of Bogor State Hospital. We have developed three models to overcome the scheduling needs. Model 1 is designed to schedule nurses who are solely assigned to a certain inpatient unit and Model 2 is constructed to manage nurses who are assigned to an inpatient room as well as at Polyclinic room as conjunct nurses. As the assignment of nurses on each shift is uneven, then we propose Model 3 to minimize the variance of the workload in order to achieve equitable assignment on every shift. The first two models are formulated in goal programming framework, while the last model is in nonlinear optimization form.