for Journals by Title or ISSN
for Articles by Keywords
  Subjects -> PHYSICS (Total: 764 journals)
    - MECHANICS (20 journals)
    - NUCLEAR PHYSICS (44 journals)
    - OPTICS (91 journals)
    - PHYSICS (554 journals)
    - SOUND (18 journals)
    - THERMODYNAMICS (29 journals)

PHYSICS (554 journals)            First | 1 2 3 4 5 6 | Last

Doklady Physics     Hybrid Journal   (Followers: 1)
Dynamical Properties of Solids     Full-text available via subscription  
ECS Journal of Solid State Science and Technology     Full-text available via subscription   (Followers: 1)
Egyptian Journal of Remote Sensing and Space Science     Open Access   (Followers: 5)
EJNMMI Physics     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 18)
Energy Procedia     Open Access   (Followers: 3)
Engineering Failure Analysis     Hybrid Journal   (Followers: 28)
Engineering Fracture Mechanics     Hybrid Journal   (Followers: 18)
Environmental Fluid Mechanics     Hybrid Journal   (Followers: 2)
EPJ Nonlinear Biomedical Physics     Open Access  
EPJ Quantum Technology     Open Access  
EPJ Techniques and Instrumentation     Full-text available via subscription  
EPJ Web of Conferences     Open Access  
European Journal of Physics     Full-text available via subscription   (Followers: 5)
European Journal of Physics Education     Open Access   (Followers: 5)
European Physical Journal - Applied Physics     Full-text available via subscription   (Followers: 5)
European Physical Journal C     Hybrid Journal  
Europhysics News     Open Access   (Followers: 1)
Experimental Mechanics     Hybrid Journal   (Followers: 16)
Experimental Methods in the Physical Sciences     Full-text available via subscription  
Experimental Techniques     Hybrid Journal   (Followers: 31)
Exploration Geophysics     Hybrid Journal   (Followers: 3)
Few-Body Systems     Hybrid Journal  
Fire and Materials     Hybrid Journal   (Followers: 5)
Flexible Services and Manufacturing Journal     Hybrid Journal   (Followers: 1)
Fluctuation and Noise Letters     Hybrid Journal   (Followers: 1)
Fluid Dynamics     Hybrid Journal   (Followers: 5)
Fortschritte der Physik/Progress of Physics     Hybrid Journal  
Frontiers in Physics     Open Access   (Followers: 2)
Frontiers of Materials Science     Hybrid Journal   (Followers: 4)
Frontiers of Physics     Hybrid Journal   (Followers: 1)
Fusion Engineering and Design     Hybrid Journal   (Followers: 2)
Geochemistry, Geophysics, Geosystems     Full-text available via subscription   (Followers: 22)
Geografiska Annaler, Series A: Physical Geography     Hybrid Journal   (Followers: 3)
Geophysical Research Letters     Full-text available via subscription   (Followers: 50)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 20)
Glass Physics and Chemistry     Hybrid Journal   (Followers: 2)
Granular Matter     Hybrid Journal   (Followers: 2)
Graphs and Combinatorics     Hybrid Journal   (Followers: 6)
Handbook of Geophysical Exploration: Seismic Exploration     Full-text available via subscription  
Handbook of Metal Physics     Full-text available via subscription  
Handbook of Surface Science     Full-text available via subscription   (Followers: 3)
Handbook of Thermal Analysis and Calorimetry     Full-text available via subscription  
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Heat Transfer - Asian Research     Hybrid Journal   (Followers: 7)
High Energy Density Physics     Hybrid Journal   (Followers: 1)
High Pressure Research: An International Journal     Hybrid Journal   (Followers: 1)
IEEE Journal of Quantum Electronics     Hybrid Journal   (Followers: 15)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 30)
IET Optoelectronics     Hybrid Journal   (Followers: 2)
Il Colle di Galileo     Open Access  
Indian Journal of Biochemistry and Biophysics (IJBB)     Open Access   (Followers: 4)
Indian Journal of Physics     Hybrid Journal   (Followers: 4)
Indian Journal of Pure & Applied Physics (IJPAP)     Open Access   (Followers: 8)
Indian Journal of Radio & Space Physics (IJRSP)     Open Access   (Followers: 6)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 11)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 5)
Infinite Dimensional Analysis, Quantum Probability and Related Topics     Hybrid Journal  
InfraMatics     Open Access  
Infrared Physics & Technology     Hybrid Journal  
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 1)
Intermetallics     Hybrid Journal   (Followers: 6)
International Applied Mechanics     Hybrid Journal   (Followers: 2)
International Geophysics     Full-text available via subscription   (Followers: 3)
International Journal for Computational Methods in Engineering Science and Mechanics     Hybrid Journal   (Followers: 8)
International Journal for Ion Mobility Spectrometry     Hybrid Journal   (Followers: 1)
International Journal for Simulation and Multidisciplinary Design Optimization     Full-text available via subscription   (Followers: 1)
International Journal of Abrasive Technology     Hybrid Journal   (Followers: 2)
International Journal of Aeroacoustics     Full-text available via subscription   (Followers: 6)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 1)
International Journal of Astronomy and Astrophysics     Open Access   (Followers: 3)
International Journal of Computational Materials Science and Surface Engineering     Hybrid Journal   (Followers: 7)
International Journal of Damage Mechanics     Hybrid Journal   (Followers: 5)
International Journal of Fatigue     Hybrid Journal   (Followers: 8)
International Journal of Fracture     Hybrid Journal   (Followers: 9)
International Journal of Geometric Methods in Modern Physics     Hybrid Journal   (Followers: 1)
International Journal of Geophysics     Open Access   (Followers: 3)
International Journal of Heat and Fluid Flow     Hybrid Journal   (Followers: 10)
International Journal of Low Radiation     Hybrid Journal  
International Journal of Low-Carbon Technologies     Open Access   (Followers: 1)
International Journal of Mass Spectrometry     Hybrid Journal   (Followers: 11)
International Journal of Material Forming     Hybrid Journal   (Followers: 2)
International Journal of Materials and Product Technology     Hybrid Journal   (Followers: 4)
International Journal of Mechanical Sciences     Hybrid Journal   (Followers: 5)
International Journal of Mechanics and Materials in Design     Hybrid Journal   (Followers: 5)
International Journal of Medical Physics, Clinical Engineering and Radiation Oncology     Open Access   (Followers: 4)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 2)
International Journal of Microstructure and Materials Properties     Hybrid Journal   (Followers: 7)
International Journal of Microwave Science and Technology     Open Access   (Followers: 2)
International Journal of Modeling, Simulation, and Scientific Computing     Hybrid Journal   (Followers: 1)
International Journal of Modern Physics A     Hybrid Journal   (Followers: 2)
International Journal of Modern Physics B     Hybrid Journal   (Followers: 1)
International Journal of Modern Physics C     Hybrid Journal   (Followers: 1)
International Journal of Modern Physics D     Hybrid Journal   (Followers: 1)
International Journal of Modern Physics E     Hybrid Journal   (Followers: 2)
International Journal of Nanomanufacturing     Hybrid Journal   (Followers: 1)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Nanotechnology     Hybrid Journal   (Followers: 5)
International Journal of Non-Linear Mechanics     Hybrid Journal   (Followers: 4)

  First | 1 2 3 4 5 6 | Last

Journal Cover Flexible Services and Manufacturing Journal     [SJR: 0.671]   [H-I: 25]
   [3 followers]  Follow    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1936-6582 - ISSN (Online) 1936-6590
   Published by Springer-Verlag Homepage  [2210 journals]
  • Rolling horizon planning for a dynamic collaborative routing problem with
           full-truckload pickup and delivery requests
    • Abstract: In order to improve their operational efficiency, small and mid-sized freight forwarders can establish horizontal coalitions in order to exchange customer requests. Decentralized operational transportation planning processes enabling request exchange among forwarders in spite of information asymmetry and distributed decision-making competences is referred to as collaborative transportation planning (CTP). CTP can help forwarders take advantage of economies of scale and reduce their costs of fulfilling customer requests compared to the case of isolated planning without request exchange. In order to exploit the potential of cost-savings embedded in CTP, appropriate request exchange mechanisms have to be developed. In this paper, the dynamic CTP problem of a coalition of freight forwarders serving full-truckload transport requests is studied. Two rolling horizon planning approaches are proposed to solve the dynamic routing problems. It is analyzed how the planning results, in particular the cost reduction realized by CTP, are influenced by different planning settings. Computational experiments show that the planning results of CTP are considerably superior to those obtained by isolated planning, and the realized cost-savings in percentage remain relatively constant, independently of the test settings.
      PubDate: 2015-01-18
  • A quay crane system that self-recovers from random shocks
    • Abstract: The main challenge for a container terminal is to maximize its throughput using limited resources subject to various operational constraints under uncertainty. Traditional methods try to achieve this through an optimized plan by solving a quay crane scheduling problem; but the plan may become obsolete or infeasible after shocks (changes in the system due to uncertainty). To respond to shocks these methods require frequent re-planning, which increases the operations cost. We propose a new method to counter this. Instead of creating plans, we develop an operating protocol to respond to shocks without re-planning. Under this protocol, each quay crane along a berth follows simple rules to serve vessels that arrive continuously in time. If the system is configured properly, it always spontaneously recovers to its efficient form after a random shock. The average throughput of the system operating on its efficient form is very near its full capacity if the crane travel time per bay is relatively short. This self-recovery is robust even under a sequence of shocks as the system persistently restores its throughput after each shock. Most importantly, this is accomplished without complex computation.
      PubDate: 2015-01-13
  • An estimation of distribution algorithm and new computational results for
           the stochastic resource-constrained project scheduling problem
    • Abstract: In this paper we propose an estimation of distribution algorithm (EDA) to solve the stochastic resource-constrained project scheduling problem. The algorithm employs a novel probability model as well as a permutation-based local search. In a comprehensive computational study, we scrutinize the performance of EDA on a set of widely used benchmark instances. Thereby, we analyze the impact of different problem parameters as well as the variance of activity durations. By benchmarking EDA with state-of-the-art algorithms, we can show that its performance compares very favorably to the latter, with a clear dominance in instances with medium to high variance of activity duration.
      PubDate: 2015-01-13
  • Control problems and management policies in health systems: application to
           intensive care units
    • Abstract: The stochastic nature of both patient arrivals and lengths of stay leads inevitably to periodic bed shortages in healthcare units. Physicians are challenged to fit demand to service capacity. If all beds are occupied eligible patients are usually referred to another ward or hospital and scheduled surgeries may be cancelled. Lack of beds may also have consequences for patients, who may be discharged in advance when the number of occupied beds is so high as to compromise the medical care of new incoming patients. In this paper we deal with the problem of obtaining efficient bed-management policies. We introduce a queuing control problem in which neither the arrival rates nor the number of servers can be modified. Bed occupancy control is addressed by modifying the service time rates, to make them dependent on the state of the system. The objective functions are two quality-of-service components: to minimize patient rejections and to minimize the length of stay shortening. The first objective has a clear mathematical formulation: minimize the probability of rejecting a patient. The second objective admits several formulations. Four different expressions, all leading to nonlinear optimization problems, are proposed. The solutions of these optimization problems define different control policies. We obtain the analytical solutions by adopting Markov-type assumptions and comparing them in terms of the two quality-of-service components. We extend these results to the general case using optimization with simulation, and propose a way to simulate general length of stay distributions enabling the inclusion of state-dependent service rates.
      PubDate: 2014-12-16
  • Mixed bundle retailing under a stochastic market
    • Abstract: Bundling is a pervasive marketing strategy in real business. In this paper, we study the strategy of mixed bundling under a stochastic market for two products for a retailer who has monopolistic power in the market, and the bundle consists of one unit of each individual product. The retailer needs to make joint pricing and inventory decisions with the aim of maximizing expected profit. Firstly, the relationship between the prices and market shares of the three bundle variations in the mixed bundling strategy is modeled after the reservation price model, which is commonly adopted in the bundling literature. Based on the market shares, a two-stage stochastic model is proposed to determine inventory decisions, including the ordering decision before the selling season starts and the allocation decisions after demands are realized. Global concavity in the order quantities is demonstrated. For experimental purposes, an algorithm incorporating both pricing and inventory decisions is presented. We measure the importance of incorporating inventory matters into bundling decisions under the stochastic market by calculating expected loss of profit, which can exceed 5 % under some parameter settings. In the numerical experiments, we identify two attributes of mixed bundling performance, which are bundling pricing effect and inventory pooling effect.
      PubDate: 2014-12-06
  • An exact reoptimization algorithm for the scheduling of elevator groups
    • Abstract: The task of an elevator control is to schedule the elevators of a group such that small waiting and travel times for the passengers are obtained. We present an exact reoptimization algorithm for this problem. A reoptimization algorithm computes a new schedule for the elevator group each time a new passenger arrives. Our algorithm uses column generation techniques and is, to the best of our knowledge, the first exact reoptimization algorithm for a group of passenger elevators. To solve the column generation problem, we propose a Branch & Bound method. The overall algorithm finds high-quality solutions very quickly.
      PubDate: 2014-12-01
  • Scheduling movements in the network of an express service provider
    • Abstract: Express service providers manage shipments from senders to receivers under strict service level agreements. Such shipments are usually not sufficient to justify a single transportation, so it is preferred to maximize consolidation of these shipments to reduce cost. The consolidation is organized via depots and hubs: depots are local sorting centers that take care of the collection and delivery of the parcels at the customers, and hubs are used to consolidate the transportation between the depots. A single transportation between two locations, carried out by a certain vehicle at a specific time, is defined as a movement. In this paper, we address the problem of scheduling all movements in an express network at minimum cost. Our approach allows to impose restrictions on the number of arriving/departing movements at the hubs so that sufficient handling capacity is ensured. As the movement scheduling problem is complex, it is divided into two parts: one part concerns the movements between depots and hubs; the other part considers the movements between the hubs. We use a column generation approach and a local search algorithm to solve these two subproblems, respectively. Computational experiments show that by using this approach the total transportation costs are decreased.
      PubDate: 2014-12-01
  • An iterative optimization framework for delay management and train
    • Abstract: Delay management determines which connections should be maintained in case of a delayed feeder train. Recent delay management models incorporate the limited capacity of the railway infrastructure. These models introduce headway constraints to make sure that safety regulations are satisfied. Unfortunately, these headway constraints cannot capture the full details of the railway infrastructure, especially within the stations. We therefore propose an optimization approach that iteratively solves a macroscopic delay management model on the one hand, and a microscopic train scheduling model on the other hand. The macroscopic model determines which connections to maintain and proposes a disposition timetable. This disposition timetable is then validated microscopically for a bottleneck station of the network, proposing a feasible schedule of railway operations. We evaluate our iterative optimization framework using real-world instances around Utrecht in the Netherlands.
      PubDate: 2014-12-01
  • Susceptibility of optimal train schedules to stochastic disturbances of
           process times
    • Abstract: This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact on the scheduler performance.
      PubDate: 2014-12-01
  • Heuristics for an oil delivery vehicle routing problem
    • Abstract: Companies distributing heating oil typically solve vehicle routing problems on a daily basis. Their problems may involve various features such as a heterogeneous vehicle fleet, multiple depots, intra-route replenishments, time windows, driver shifts and optional customers. In this paper, we consider such a rich vehicle routing problem that arises in practice and develop three metaheuristics to address it, namely, a tabu search (TS) algorithm, a large neighborhood search (LNS) heuristic based on this TS heuristic and another LNS heuristic based on a column generation (CG) heuristic. Computational results obtained on instances derived from a real-world dataset indicate that the LNS methods outperform the TS heuristic. Furthermore, the LNS method based on CG tends to produce better quality results than the TS-based LNS heuristic, especially when sufficient computational time is available.
      PubDate: 2014-12-01
  • A genetic local search algorithm for the multi-depot heterogeneous fleet
           capacitated arc routing problem
    • Abstract: This paper studies the multi-depot heterogeneous fleet capacitated arc routing problem (MDHCARP), a problem with rare research in the past, but with many applications in real life. The MDHCARP extends the capacitated arc routing problem (CARP) by considering both the multi-depot case and limited heterogeneous fleet constraints. We propose a genetic local search (GLS) algorithm for the MDHCARP. The GLS is appraised on simplified MDHCARP cases and on general MDHCARP instances from CARP files; and computational results show that the GLS outperforms an extended memetic algorithm and meanwhile they both improve best-known solutions of the simplified MDHCARP benchmark cases.
      PubDate: 2014-12-01
  • Evaluating the impact of flexible practices on the master surgical
           scheduling process: an empirical analysis
    • Abstract: This study focuses on the master surgical scheduling problem and adds two main contributions. First, it presents a novel mixed integer programming model to support the master surgical schedule production. Second, it uses the model to investigate the impact, in terms of scheduled surgeries, of the flexible management of three critical resources, namely surgical teams, operating rooms and surgical units. Our analysis revealed that to maximise the number of surgeries scheduled, it is sufficient to introduce flexibility with respect to surgical teams and ORs. In fact, if both these resources are managed flexibly, then introducing flexibility with respect to surgical units carries no additional advantages. However, if surgical teams or ORs (or both) are not managed flexibly, then managing surgical units flexibly produces significant benefits. In addition, our study shows that if surgical teams cannot be managed flexibly, then introducing flexibility with respect to ORs yields significant benefits. Similarly, it reveals that if ORs cannot be managed flexibly, then introducing flexibility with respect to surgical teams yields significant benefits as well. The work is based on real data from the Meyer University Children’s Hospital in Florence.
      PubDate: 2014-11-28
  • Retraction Note to: Effect of reconfiguration costs on planning for
           capacity scalability in reconfigurable manufacturing systems
    • PubDate: 2014-11-13
  • A policy management game for mass casualty incidents: an experimental
    • Abstract: The number of complex and unique mass casualty incidents has increased due to natural and technological disasters as well as man-made disasters such as political instabilities, economic recession, and terrorism. Thus, health care policy-makers such as the Austrian Samaritan Organization have been continuously improving the training of emergency staff to enable them to quickly evacuate an emergency site, to minimize the number of fatalities at the incident site, and to decrease the patients’ waiting time for treatment. We developed a policy management game to provide a training tool for emergency staff to support such policy-makers. In addition, with this game students can be educated on scheduling and planning techniques such as simulation, queuing theory, and resource allocation. To investigate the potential of our policy management game, we conducted an experimental study with 96 participants including students, practitioners from health care services, and researchers. They acted as incident commanders to decide on sending medical staff to triage, to different treatment rooms for care and to on-site transportation, as well as to transportation to hospitals during three game runs. The participants rated the general structure and organization of the experiment as high. The performance was also improved by many participants during the experiment. We found differences in performance among the different participant groups.
      PubDate: 2014-10-16
  • Combining syndromic surveillance and ILI data using particle filter for
           epidemic state estimation
    • Abstract: Designing effective mitigation strategies against influenza outbreak requires an accurate prediction of a disease’s future course of spreading. Real time information such as syndromic surveillance data and influenza-like-illness (ILI) reports by clinicians can be used to generate estimates of the current state of spreading of a disease. Syndromic surveillance data are immediately available, in contrast to ILI reports that require data collection and processing. On the other hand, they are less credible than ILI data because they are essentially behavioral responses from a community. In this paper, we present a method to combine immediately-available-but-less-reliable syndromic surveillance data with reliable-but-time-delayed ILI data. This problem is formulated as a non-linear stochastic filtering problem, and solved by a particle filtering method. Our experimental results from hypothetical pandemic scenarios show that state estimation is improved by utilizing both sets of data compared to when using only one set. However, the amount of improvement depends on the relative credibility and length of delay in ILI data. An analysis for a linear, Gaussian case is presented to support the results observed in the experiments.
      PubDate: 2014-10-11
  • Planning of a make-to-order production process in the printing industry
    • Abstract: Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The production equipment used gives rise to various technological constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technological and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.
      PubDate: 2014-10-11
  • Optimal server allocation in closed finite queueing networks
    • Abstract: Many topological network design problems in manufacturing and service systems can be modelled with closed queueing networks, finite buffers, and multiple-servers. Because of their integrality, it is difficult to predict the performance of these problems, let alone optimize their parameters. This paper presents a new queue decomposition approach for the modelling of these finite buffer closed queueing networks with multiple servers along with an integrated approach to the optimization of the allocation of the servers in the network topology. The performance and optimization algorithms are described and a number of experiments for series, merge, and split topologies together with the integration of material handling and layout systems are carried out.
      PubDate: 2014-09-09
  • A Bayesian framework for describing and predicting the stochastic demand
           of home care patients
    • Abstract: Home care providers are complex structures which include medical, paramedical and social services delivered to patients at their domicile. High randomness affects the service delivery, mainly in terms of unplanned changes in patients’ conditions, which make the amount of required visits highly uncertain. Hence, each reliable and robust resource planning should include the estimation of the future demand for visits from the assisted patients. In this paper, we propose a Bayesian framework to represent the patients’ demand evolution along with the time and to predict it in future periods. Patients’ demand evolution is described by means of a generalized linear mixed model, whose posterior densities of parameters are obtained through Markov chain Monte Carlo simulation. Moreover, prediction of patients’ demands is given in terms of their posterior predictive probabilities. In the literature, the stochastic description of home care patients’ demand is only marginally addressed and no Bayesian approaches exist to the best of our knowledge. Results from the application to a relevant real case show the applicability of the proposed model in the practice and validate the approach, since parameter densities in accordance to clinical evidences and low prediction errors are found.
      PubDate: 2014-09-06
  • Call for papers
    • PubDate: 2014-09-01
  • Logistics, traffic and transportation
    • PubDate: 2014-07-15
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2014