1,720,974 research outputs found
Physical distribution activities and vehicle routing problems in logistics management: a case study
No full textThe vehicle routing path (VRP) is non-deterministic polynomial-time hard (NP-hard) and therefore difficult to solve. The fact that VRP is both of theoretical and practical interest (owing to its real-world applications), explains the amount of attention given to the VRP by researchers during past years. Research on the development of heuristics for the VRP has made considerable progress since the first algorithms were proposed in the early 1960s. Several families of heuristics have been proposed for the VRP. The purpose of this paper is to review some of the most important families of heuristics for the VRP. At the end, the survey presents the solution method used for a small-scale case study in a logistic company in Turkey
Wind power energy and cost analysis study in Turkey
No full textEnergy is a vital input for the social and economic development of any nation. With increasing agricultural and industrial activities in Turkey, the demand for energy is also increasing. Energy should be supplied in several ways, but the important thing is how energy can be supplied cost effectively. Wind has been proven as a reliable and cost effective energy source. Technological improvements have placed wind energy in a position that competes with conventional power generation technologies. The current interest in wind energy is based on the need to develop clean, sustainable energy systems that can be relied on in the long term future. Modern aerodynamics and engineering have improved wind turbines to the extent that they now provide reliable, cost effective, pollution free energy for individual, community and national applications. The significant benefits of wind power should play an increasingly important role in decisions about future power plant construction. The purpose of this paper is to both describe the characteristics of wind power energy, and to analyse its actual cost, using the data provided by a wind turbine in Turkey
CALCULATION THE ENVIRONMENTAL IMPACTS OF BLEVE USING ARTIFICIAL NEURAL NETWORKS
No full textFor the community, major manufacturing facilities pose a high fire risk. BLEVE is known as the sudden outflow of a superheated liquid resulting from the liquid's evaporation under pressure in the atmosphere. The reason for these sudden outflows is caused by fires around the tank, corrosion and overheating inside the tank. Before using the modeling methods in the literature, artificial neural networks were modeled with input data determined using the Levenberg-Marquardt algorithm, which is a multi layer sensor (MLP) (teacher teaming) sort. The real values obtained from the measurement are compared to the network's outputs. The outputs of the real values. which produced, and of the outputs produced by the network using the real inputs are compared the compatibility. The feasibility of performance determination was investigated by using the neural network and curves formed from the resulting values. For BLEVE, the fireball explosion, a scenario was calculated. Artificial neural network results were generated for the outputs of the data on LPG gas explosion in tankers, which have 100, 150 and 200 m(3) volumes. Input values in the generated artificial neural network model; BLEVE's expansion measurement distance values. Thermal radiation heat flux (W/m(2)) values were predicted from the network as an output corresponding to these inputs. In addition, graphics comparing the actual expected values with the values found by the network created with the Levenberg-Marquardt Algorithm were also added
Simulation modeling of hospital emergency departments: Review of literature during normal and disaster times
No full textA comprehensive review of emergency department simulation applications for normal and disaster conditions
No full textHospital emergency departments (HEDs) are the most critical units since they undertake a vital health care mission. It is required for these departments to find out rational solution methods in case of issues occurred in normal and disaster times. Simulation is an effective method to improve policies on operational, tactical and strategic decisions about EDs. The main reasons prompting us to do this study are to reveal the importance of simulation for disaster preparedness of EDs and the innovative aspects of recent ED simulation applications unlike the available literature surveys. This systematic and comprehensive review study can provide an insight for researchers on ED simulation modeling in terms of showing current state and gaps to be focused in the future. (c) 2015 Elsevier Ltd. All rights reserved
Planning the future of emergency departments: Forecasting ED patient arrivals by using regression and neural network models
No full textEmergency departments (EDs) face high numbers of patient arrivals in comparison to other departments of hospitals because they provide non-stop service. Patient arrivals at these departments mostly do not appear in a steady state. Predicting existing uncertainty contributes to the future planning of these departments. Therefore, forecasting patient arrivals at emergency departments is crucial so as to make short and long term plans for physical capacity requirements, staffing, budgeting and arranging staff schedules. In this paper, variations in annual, monthly and daily ED arrivals are analyzed based on regression and neural network models with the aid of a collected data from a public hospital ED in Istanbul. The results show that ANN-based models have higher model accuracy values and lower values of absolute error in terms of forecasting the ED patient arrivals over the long and medium terms. The paper is also aimed to provide ED management and medical staff a useful guide for future planning of their emergency departments in the light of an accurate forecasting
Multi-echelon inventory management in supply chains with uncertain demand and lead times: literature review from an operational research perspective
No full textHistorically, the echelons of the supply chain, warehouse, distributors, retailers, etc., have been managed independently, buffered by large inventories. Increasing competitive pressures and market globalization are forcing firms to develop supply chains that can quickly respond to customer needs. To remain competitive and decrease inventory, these firms must use multi-echelon inventory management interactively, while reducing operating costs and improving customer service. The current paper reviews the literature, addressing multi-echelon inventory management in supply chains from 1996 to 2005. The behaviour of the papers against demand and lead-time uncertainty is the key analysis point of the literature review presented here and it is conducted from an operational research point of view. Finally, directions for future research are suggested
A COMPUTER SIMULATION MODEL TO REDUCE PATIENT LENGTH OF STAY AND TO IMPROVE RESOURCE UTILIZATION RATE IN AN EMERGENCY DEPARTMENT SERVICE SYSTEM
No full text This paper presents a case study of a discrete-event simulation (DES) model of an emergency department (ED) unit in a regional university hospital in Turkey. In this paper emergency department operations of the hospital were modeled, analyzed and improved. The goal of the study is to reduce patient average length of stay (LOS) and to improve patient throughput and utilization of locations and human resources (doctors, nurses, receptionists). Some alternative scenarios in an attempt to determine optimal staff level were evaluated. These alternative approaches illustrate that vital improvement in LOS and throughput can be obtained by minor changes in shift hours and number of resources. Considering future changes in patient demand a scenario which reduces LOS and improves throughput is available in the paper. Significance: The Key Performance Indicators (KPIs) to determine and improve system performance in healthcare emergency departments consist of to reduce patient average length of stay (LOS), to improve patient throughput and resource utilization rates. Alternative scenarios and optimal staff levels are enhanced within the scope of this study
Forecasting patient length of stay in an emergency department by Artificial Neural Networks
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