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  Subjects -> PHYSICS (Total: 797 journals)
    - ELECTRICITY AND MAGNETISM (10 journals)
    - MECHANICS (20 journals)
    - NUCLEAR PHYSICS (48 journals)
    - OPTICS (90 journals)
    - PHYSICS (576 journals)
    - SOUND (22 journals)
    - THERMODYNAMICS (31 journals)

PHYSICS (576 journals)            First | 1 2 3 4 5 6 | Last

Contemporary Physics     Hybrid Journal   (Followers: 15)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 4)
Contributions to Plasma Physics     Hybrid Journal   (Followers: 1)
COSPAR Colloquia Series     Full-text available via subscription   (Followers: 1)
Cryogenics     Hybrid Journal   (Followers: 23)
Current Applied Physics     Full-text available via subscription   (Followers: 3)
Diamond and Related Materials     Hybrid Journal   (Followers: 12)
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: 3)
Egyptian Journal of Remote Sensing and Space Science     Open Access   (Followers: 5)
EJNMMI Physics     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 28)
Energy Procedia     Open Access   (Followers: 2)
Engineering Failure Analysis     Hybrid Journal   (Followers: 56)
Engineering Fracture Mechanics     Hybrid Journal   (Followers: 21)
Environmental Fluid Mechanics     Hybrid Journal   (Followers: 3)
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: 6)
European Journal of Physics Education     Open Access   (Followers: 3)
European Physical Journal - Applied Physics     Full-text available via subscription   (Followers: 6)
European Physical Journal C     Hybrid Journal  
Europhysics News     Open Access  
Experimental Mechanics     Hybrid Journal   (Followers: 20)
Experimental Methods in the Physical Sciences     Full-text available via subscription  
Experimental Techniques     Hybrid Journal   (Followers: 54)
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: 6)
Fortschritte der Physik/Progress of Physics     Hybrid Journal  
Frontiers in Physics     Open Access   (Followers: 4)
Frontiers of Materials Science     Hybrid Journal   (Followers: 3)
Frontiers of Physics     Hybrid Journal   (Followers: 1)
Fusion Engineering and Design     Hybrid Journal   (Followers: 8)
Geochemistry, Geophysics, Geosystems     Full-text available via subscription   (Followers: 23)
Geografiska Annaler, Series A: Physical Geography     Hybrid Journal   (Followers: 3)
Geophysical Research Letters     Full-text available via subscription   (Followers: 56)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 19)
Glass Physics and Chemistry     Hybrid Journal   (Followers: 3)
Global Journal of Physics     Open Access   (Followers: 1)
Granular Matter     Hybrid Journal   (Followers: 1)
Graphs and Combinatorics     Hybrid Journal   (Followers: 6)
Gravitation and Cosmology     Hybrid Journal  
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: 2)
Handbook of Thermal Analysis and Calorimetry     Full-text available via subscription  
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 2)
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: 3)
IEEE Journal of Quantum Electronics     Hybrid Journal   (Followers: 17)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 49)
IET Optoelectronics     Hybrid Journal   (Followers: 1)
Il Colle di Galileo     Open Access  
Imaging Science Journal     Hybrid Journal   (Followers: 2)
Indian Journal of Biochemistry and Biophysics (IJBB)     Open Access   (Followers: 3)
Indian Journal of Physics     Hybrid Journal   (Followers: 3)
Indian Journal of Pure & Applied Physics (IJPAP)     Open Access   (Followers: 10)
Indian Journal of Radio & Space Physics (IJRSP)     Open Access   (Followers: 7)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 15)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 3)
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: 5)
Intermetallics     Hybrid Journal   (Followers: 23)
International Applied Mechanics     Hybrid Journal   (Followers: 3)
International Geophysics     Full-text available via subscription   (Followers: 3)
International Heat Treatment and Surface Engineering     Hybrid Journal   (Followers: 1)
International Journal for Computational Methods in Engineering Science and Mechanics     Hybrid Journal   (Followers: 10)
International Journal for Ion Mobility Spectrometry     Hybrid Journal   (Followers: 1)
International Journal for Simulation and Multidisciplinary Design Optimization     Full-text available via subscription  
International Journal of Abrasive Technology     Hybrid Journal   (Followers: 2)
International Journal of Aeroacoustics     Full-text available via subscription   (Followers: 26)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 1)
International Journal of Astronomy and Astrophysics     Open Access   (Followers: 2)
International Journal of Computational Materials Science and Surface Engineering     Hybrid Journal   (Followers: 6)
International Journal of Damage Mechanics     Hybrid Journal   (Followers: 5)
International Journal of Fatigue     Hybrid Journal   (Followers: 34)
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: 5)
International Journal of Heat and Fluid Flow     Hybrid Journal   (Followers: 24)
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: 17)
International Journal of Material Forming     Hybrid Journal  
International Journal of Materials and Product Technology     Hybrid Journal   (Followers: 4)
International Journal of Mechanical Sciences     Hybrid Journal   (Followers: 8)
International Journal of Mechanics and Materials in Design     Hybrid Journal   (Followers: 4)
International Journal of Medical Physics, Clinical Engineering and Radiation Oncology     Open Access   (Followers: 5)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 1)
International Journal of Microstructure and Materials Properties     Hybrid Journal   (Followers: 7)

  First | 1 2 3 4 5 6 | Last

Journal Cover Flexible Services and Manufacturing Journal
  [SJR: 1.277]   [H-I: 28]   [1 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  [2281 journals]
  • Improving the efficiency of a hospital emergency department: a simulation
           study with indirectly imputed service-time distributions
    • Abstract: Abstract This paper presents a case study which uses simulation to analyze patient flows in a hospital emergency department in Hong Kong. We first analyze the impact of the enhancements made to the system after the relocation of the Emergency Department. After that, we developed a simulation model (using ARENA) to capture all the key relevant processes of the department. When developing the simulation model, we faced the challenge that the data kept by the Emergency Department were incomplete so that the service-time distributions were not directly obtainable. We propose a simulation–optimization approach (integrating simulation with meta-heuristics) to obtain a good set of estimate of input parameters of our simulation model. Using the simulation model, we evaluated the impact of possible changes to the system by running different scenarios. This provides a tool for the operations manager in the Emergency Department to “foresee” the impact on the daily operations when making possible changes (such as, adjusting staffing levels or shift times), and consequently make much better decisions.
      PubDate: 2016-06-01
       
  • Operating room scheduling and rescheduling: a rolling horizon approach
    • Abstract: Abstract In this work we consider the problem of selecting a set of patients among a given waiting list of elective patients and assigning them to a set of available operating room blocks. We assume a block scheduling strategy in which the number and the length of available blocks are given. As each block is related to a specific day, by assigning a patient to a block his/her surgery date is fixed, as well. Each patient is characterized by a recommended maximum waiting time and an uncertain surgery duration. In practical applications, new patients enter the waiting list continuously. Patient selection and assignment is performed by surgery departments on a short-term, usually a week, regular base. We propose a so-called rolling horizon approach for the patient selection and assignment. At each iteration short-term patient assignment is decided. However, in a look-ahead perspective, a longer planning horizon is considered when looking for the patient selection. The mid-term assignment over the next \(n\) weeks is generated by solving an ILP problem, minimizing a penalty function based on total waiting time and tardiness of patients. The approach is iteratively applied by shifting ahead the mid-term planning horizon. When applying the first week solution, unpredictable extensions of surgeries may disrupt the schedule. Such disruptions are recovered in the next iteration: the mid-term solution is rescheduled limiting the number of variations from the previously computed plan. Besides, the approach allows to deal with new patient arrivals. To keep limited the number of disruptions due to uncertain surgery duration, we propose also a robust formulation of the ILP problem. The deterministic and the robust formulation based frameworks are compared over a set of instances, including different stochastic realization of surgery times.
      PubDate: 2016-06-01
       
  • An analytical representation of flexible resource allocation in hospitals
    • Abstract: Abstract Non-linear processes within complex systems are difficult to predict. Using discrete event simulation (DES) models can be helpful for presenting the uncertainty level embedded within these processes. However, the interpretations of the resulting outcomes can be challenging to analyze. This is evident when experimenting with simulation models, and therefore requires the adaptation of existing models. Introducing cyclic entities such as interconnected resources to the simulation model adds a new level of complexity to the model. In practical cases, decision makers often demand a model that enables them to make quick decisions with less complexity involved. However, these individuals still want to be assured of a high degree of accuracy in the results. This article demonstrates how an analytical representation of complex DES models can be developed in order to facilitate prompt yet effective solutions for decision makers. This analytical representation provides a brief overview of the simulation results by using the staff scheduling and nurses’ utilization approaches. Results of the effective use of DES model and managers feedback are encouraging.
      PubDate: 2016-06-01
       
  • Operations management in the home care services: a heuristic for the
           caregivers’ routing problem
    • Abstract: Abstract Home Care Services (HCS) aim at providing complex coordinated health care for patients at their homes. This paper addresses the challenges of routing and scheduling HCS caregivers under precedence and coordination constraints, with patients receiving multiple caregivers. Moreover, the visits are performed simultaneously and possibly in a predefined order. The routing problem involves a fleet of vehicles to serve a number of customers at different locations. The objective is to find the minimal round for vehicle, while satisfying all the customers and without violating customers’ time windows. It has been proved that the complexity of the caregivers routing problem is linked to both (1) the number of care activities per caregiver ratio and (2) the temporal dependencies rate. Given the poor performance of the mathematical modeling based on exact approaches, a heuristic approach called the Caregivers Routing Heuristic (CRH) has been developed and tested using real size instances. In fact, the exact approaches are not able to solve real size instances. The performance of the CRH has been evaluated using real size instances. The numerical results show that the CRH is very efficient in terms of computation times. Otherwise, the CRH is less sensitive than the exact approaches to both complexity axes: the temporal dependencies constraints and the ratio of the number of care activities per caregiver.
      PubDate: 2016-06-01
       
  • Evaluating the impact of flexible practices on the master surgical
           scheduling process: an empirical analysis
    • Abstract: 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: 2016-06-01
       
  • Design and analysis of gastroenterology (GI) clinic in Digestive Health
           Center of University of Wisconsin Health
    • Abstract: Abstract This paper is devoted to the design and analysis of the gastroenterology (GI) clinic in the Digestive Health Center (DHC) of University of Wisconsin Health. The DHC will consolidate several existing clinic and endoscopy locations into a single center. First, the work flow at a current GI clinic is studied. A Markov chain model is developed and then extended to non-Markovian case to evaluate patient average length of stay and staff utilization. The model is validated by the data observed in the clinic. It is shown that the model can provide accurate estimation of system performance. Then, using such a model, design options of the new GI clinic in the DHC are studied. To investigate the impact of different system configurations, what-if analyses are carried out and different patient check-out processes are investigated. Finally, recommendations for enhancing service at the new GI clinic are proposed to the DHC leadership.
      PubDate: 2016-06-01
       
  • The patient assignment problem in home health care: using a data-driven
           method to estimate the travel times of care givers
    • Abstract: Abstract Home health care is one of the recent service systems where human resource planning has a great importance. The assignment of patients to care givers is a relevant issue that the home health care service provider must address before generating the daily routes. The assignment decision is typically made without knowing the visiting sequence, which creates some uncertainties and disparities regarding the effective workload of care givers. However, taking into account travel times in the care giver workload while solving the assignment problem is not straightforward, because travel times can also be affected by clinical conditions of patients and their homes. Providing good travel time estimates that would be used in the assignment decision is the specific topic this paper focuses on. In particular, we propose a data-driven method to estimate the travel times of care givers in the assignment problem when their routes are not available yet. The method, based on the Kernel regression technique, uses the travel times observed from previous periods to estimate the time necessary for visiting a set of patients located in specific geographical locations. The main advantage offered by this technique is the empirical modelling of the travel routes generated by care givers. Numerical results based on realistic problem instances indicate that the proposed estimation method performs better than the average value and k-nearest neighbor search methods and can be successfully used in a two-stage approach that first assigns patients to care givers and then defines their routes.
      PubDate: 2016-06-01
       
  • Combining syndromic surveillance and ILI data using particle filter for
           epidemic state estimation
    • Abstract: 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: 2016-06-01
       
  • A hierarchical facility layout planning approach for large and complex
           hospitals
    • Abstract: Abstract The transportation processes for patients, personnel, and material in large and complex maximum-care hospitals with many departments can consume significant resources and thus induce substantial logistics costs. These costs are largely determined by the allocation of the different departments and wards in possibly multiple connected hospital buildings. We develop a hierarchical layout planning approach based on an analysis of organizational and operational data from the Hannover Medical School, a large and complex university hospital in Hannover, Germany. The purpose of this approach is to propose locations for departments and wards for a given system of buildings such that the consumption of resources due to those transportation processes is minimized. We apply the approach to this real-world organizational and operational dataset as well as to a fictitious hospital building and analyze the algorithmic behavior and resulting layout.
      PubDate: 2016-06-01
       
  • Integrated scheduling of elective surgeries and surgical nurses for
           operating room suites
    • Abstract: Abstract Facing an acute shortage of surgical nurses, operating room suites in China are more and more aware of the need to use surgical nurses efficiently. This goal is hard to achieve due to the strong interactions between the nurse and the surgery scheduling process. This paper addresses the benefit of integrating elective surgery and surgical nurse scheduling in terms of nurse utilization. First, an integer programming (IP) model is proposed to schedule elective surgeries and surgical nurses simultaneously. Then an efficient genetic algorithm (GA) is proposed based on the IP formulation due to the computational complexity of the integrated scheduling problem. A case study using real-life data is presented to validate the performance of the integrated approaches (the IP model and the GA) by comparing them with a two-stage approach that schedules elective surgeries and surgical nurses sequentially.
      PubDate: 2016-06-01
       
  • Control problems and management policies in health systems: application to
           intensive care units
    • Abstract: 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: 2016-06-01
       
  • Patient admission planning using Approximate Dynamic Programming
    • Abstract: Abstract Tactical planning in hospitals involves elective patient admission planning and the allocation of hospital resource capacities. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with uncertain treatment paths and an uncertain number of arrivals in each time period. As such, the method enables integrated decision making for a network of hospital departments and resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various hospital settings.
      PubDate: 2016-06-01
       
  • A Bayesian framework for describing and predicting the stochastic demand
           of home care patients
    • Abstract: 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: 2016-06-01
       
  • A policy management game for mass casualty incidents: an experimental
           study
    • Abstract: 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: 2016-06-01
       
  • Erratum to: Extraction and visualization of industrial service portfolios
           by text mining of 10-K annual reports
    • PubDate: 2016-04-26
       
  • Determining departure times in dynamic and stochastic maritime routing and
           scheduling problems
    • Abstract: Abstract In maritime transportation, decisions are made in a dynamic setting where many aspects of the future are uncertain. However, most academic literature on maritime transportation considers static and deterministic routing and scheduling problems. This work addresses a gap in the literature on dynamic and stochastic maritime routing and scheduling problems, by focusing on the scheduling of departure times. Five simple strategies for setting departure times are considered, as well as a more advanced strategy which involves solving a mixed integer mathematical programming problem. The latter strategy is significantly better than the other methods, while adding only a small computational effort.
      PubDate: 2016-04-20
       
  • Improved critical chain buffer management framework considering resource
           costs and schedule stability
    • Abstract: Abstract The critical chain scheduling and buffer management (CC/BM) methodology has proven to be a favorable approach to schedule resource-constrained projects and to offer a valuable control tool for monitoring projects under uncertainty. The previous studies on CC/BM seem to have neglected the cost performance, which might render its wider applications to the modern economic activities that are mostly performed in a project way. This paper presents an improved CC/BM framework that allows additional resource allocation/reallocation to bring forward activity starting times based on cost and schedule stability criteria. In the planning phase, the decision is made concerning the regular resource availability period in order to minimize the expected resource costs. In the execution phase, a scheduled order repair method for rescheduling along with two reactive resource allocation procedures as the corrective action whenever delays are beyond a certain buffer threshold are presented and examined in order to exhibit a comprehensive project schedule/cost control system that is adaptive to the CC/BM management logic. Finally, our computational experiment demonstrates the benefits of the proposed reactive methods under different cost or availability parameters.
      PubDate: 2016-04-02
       
  • Sustainable transportation and order quantity: insights from
           multiobjective optimization
    • Abstract: Abstract This article applies multiobjective optimization to show how the tradeoffs between cost and carbon emissions may be obtained in the context of sustainable operations. We formulate a model where transportation mode selection and order quantity decisions are considered jointly. We derive structural properties of the model and develop several insights. First, we show that switching to a greener mode of transportation while continuing to optimize the total logistics costs function may lead to a dominated solution. Second, we prove that the modal shift occurs only under strong carbon emissions reduction requirements. Third, we show that the efficient frontier is non-convex and we analyze some implications. Finally, we analyze the impacts of an increase in truck capacity. The results are illustrated through an example of a French retailer.
      PubDate: 2016-03-25
       
  • Simulation modelling in ports and container terminals: literature overview
           and analysis by research field, application area and tool
    • Abstract: Abstract The simulation modelling of shore- and sea-side port operations constitutes a fundamental prerequisite for effective project planning in port development, as the influence of numerous often interactive parameters has to be addressed at an early stage to account for the optimum supply of port facilities and services to current and future demand. This paper presents a detailed review of the available research literature on the application of simulation models in port development, through extensive reference to published journal papers from the onset of the relevant simulation modelling and through the course of the past 54 years (1961–2015). With focus on container terminals, this review aims at analysing the use of port related simulation models and ultimately at assessing their contribution into building the research knowledge necessary to promote sustainable ship-port interfaces and freight transport chains. It was found that over the past 50 years the use of simulation models has been increasingly favoured and instrumental in the development of ports and more specifically of container terminals. Most of the research literature addresses operational issues, accounting for its highest concentration and coherence in the research field of operations research, although the need to utilise the wide-ranging capabilities of simulation modelling in order to offer integrated solutions is recently promoting the dissemination of the relevant literature through sector-specific (i.e. transport and maritime) research fields. Finally, the observed tendency to employ simulation tools which offer the most realistic results reflects the research effort to ensure that simulation modelling offers tangible solutions to the maritime and transport industry.
      PubDate: 2016-02-22
       
  • Health Care Systems Engineering
    • PubDate: 2015-12-12
       
 
 
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