Wangermann, John Paul
Today's aircraft/airspace system faces complex challenges. Congestion and delays are widespread as air traffic continues to grow. Airlines want to better optimize their operations, and general aviation wants easier access to the system. Additionally, the accident rate must decline just to keep the number of accidents each year constant. New technology provides an opportunity to rethink the air traffic management process. Faster computers, new sensors, and high-bandwidth communications can be used to create new operating models. The choice is no longer between "inflexible" strategic separation assurance and "flexible" tactical conflict resolution. With suitable operating procedures, it is possible to have strategic, four-dimensional separation assurance that is flexible and allows system users maximum freedom to optimize operations. This thesis describes an operating model based on principled negotiation between agents. Many multi-agent systems have agents that have different, competing interests but have a shared interest in coordinating their actions. Principled negotiation is a method of finding agreement between agents with different interests. By focusing on fundamental interests and searching for options for mutual gain, agents with different interests reach agreements that provide benefits for both sides. Using principled negotiation, distributed optimization by each agent can be coordinated leading to iterative optimization of the system. Principled negotiation is well-suited to aircraft/airspace systems. It allows aircraft and operators to propose changes to air traffic control. Air traffic managers check the proposal maintains required aircraft separation. If it does, the proposal is either accepted or passed to agents whose trajectories change as part of the proposal for approval. Aircraft and operators can use all the data at hand to develop proposals that optimize their operations, while traffic managers can focus on their primary duty of ensuring
Huberman, Bernardo A.; Helbing, Dirk
We present an economics-based method for deciding the optimal rates at which vehicles are allowed to enter a highway. The method exploits the naturally occuring fluctuations of traffic flow and is flexible enough to adapt in real time to the transient flow characteristics of road traffic. Simulations based on realistic parameter values show that this strategy is feasible for naturally occuring traffic, and that even far from optimality, injection policies can improve traffic flow. Our results...
Bilal Ahmed Khan; Nai Shyan Lai
Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisi...
Balon, Simon; Leduc, Guy
In this paper we propose a new method to approach optimal Traffic Engineering routing. The method consists of dividing the traffic matrix into $N$ sub-matrices, called strata, and route each of these independently. We propose two different implementations of our method in routers. Our method can also be used to compute a very precise approximation of the optimal value of a given objective function for comparison to heuristic Traffic Engineering algorithms. For this application, our algorithm ...
Delle Monache, Maria Laura; Obsu, Legesse Lemecha; Goatin, Paola; Kassa, Semu Mitiku
The aim of this paper is to optimize the traffic flow on roundabouts using a macroscopic approach. The roundabout is modeled as a sequence of 2x2 junctions: with one mainline and secondary incoming and outgoing roads. We consider two cost functionals: the total travel time and the total waiting time, which give an estimate of the time spent by drivers on the network section. These cost functionals are minimized analytically for each junction with respect to the right of way parameter of the i...
N. Shahsavari Pour; H. Asadi; M. Pour Kheradmand
Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution. Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns depending upon the time of the day. These automated systems do not provide an optimal control for ...
Warberg, Andreas; Larsen, Jesper; Jørgensen, Rene Munk
important conflicts, which support the notion that traffic signal optimization is a multi-objective problem, and relates this to the most common measures of effectiveness. A distinction can be made between classical systems, which operate with a common cycle time, and the more flexible, phase......-based, approach, which is shown to be more suitable for adaptive traffic control. To support this claim three adaptive systems, which use alternatives to the classical optimization procedures, are described in detail....
Rios, Joseph Lucio
This talk will present an overview of Traffic Flow Management (TFM) research at NASA Ames Research Center. Dr. Rios will focus on his work developing a large-scale, parallel approach to solving traffic flow management problems in the national airspace. In support of this talk, Dr. Rios will provide some background on operational aspects of TFM as well a discussion of some of the tools needed to perform such work including a high-fidelity airspace simulator. Current, on-going research related to TFM data services in the national airspace system and general aviation will also be presented.
Wang, Wen-Xu; Wang, Bing-Hong; Zheng, Wen-Chen; Yin, Chuan-Yang; Zhou, Tao
The optimal information feedback is very important to many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. As to traffic flow, a reasonable real-time information feedback can improve the urban traffic condition by providing route guidance. In this paper, the influence of a feedback strategy named congestion coefficient feedback strategy is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other two information feedback strategies, i.e., travel time and mean velocity. PMID:16486093
Full Text Available Traffic and spam are the main problems in the data transmission through the network. Many traffic filtering systems have been proposed to find and filter the traffic over the network. The system Optimal Source Filtering (OSF has implemented a new and optimal filtering mechanism. The new mechanism named as DROP, which monitors and filters the spam and malicious traffic over a network effectively. Traffic filtering systems have been proposed to detect the spammer and malicious traffic, using the optimal rules and policies. Further these systems are highly ineffective when they encounter malicious traffic. The proposed system introduced OSF protocol, which helps to improve the efficiency of the firewall and filters based on the user rule. The proposed filtering scheme provides TFS false filtering when the flash crowd occurred. The protocol verifies users and firewall rules and policies with the data priority model, which makes the filtering process more robust and fastest manner. The Proposed spam detection project identifies and eliminates unwanted messages by monitoring outgoing messages. The spam detection is the main challenging task in the network. In the existing system spam detection has implemented after the data received. According to the user rule and request the current system identifies the spam and zombies by monitoring every outgoing message from the sender.
Francois J; Cholez T.; Engel T.
International audience Content-Centric Networking (CCN) recently received a lot of attention thanks to its elegant way to optimize content diffusion at the scale of Internet. However, communications occurring at the edge of Internet, in particular the Internet of Things (IoT), are also a vivid research topic. Even if CCN was not initially designed to optimize the specific traffic pattern of the IoT, it can be improved to better support these new applications. In this paper, we propose to o...
Barlovic, Robert; Brockfeld, Elmar; Schreckenberg, Michael; Schadschneider, Andreas
The impact of global traffic light control strategies for city networks is analyzed in a recently proposed cellular automaton model. The model combines basic ideas of the Biham-Middleton-Levine model for city traffic and the Nage-Schreckenberg model for highway traffic. The city network has a simple square lattice geometry. All streets and intersections are treated equally, i.e., there are no dominant streets.
separately for each locality from the available data set. For efficient control in mobility of vehicles an advanced dynamic digital board is introduced, which displays the speed limit set by the central node time to time. The normalized speed could be used to estimate the effective time taken between destinations precisely. By comparing normalized speed with real time values anomalies in the locality like congestion and presence of uneven roads is predicted. Accident detection model is integrated with the central node which sends a message to dynamic board indicating location of the accident along with the time taken. It even improves traffic flow around the accident occurred location. Central node together with navigation tools could provide re-routed path to the drivers during congestion or accident.
A traffic flow is one of the main transportation issues in nowadays industrialized agglomerations. Configuration of traffic lights is among the key aspects in traffic flow management. This paper proposes an evolutionary optimization tool that utilizes multiagent simulator in order to obtain accurate model. Even though more detailed studies are still necessary, a preliminary research gives an expectation for promising results.
Florin Pop; Ciprian Dobre
The cities are not static environments. They change constantly. When we talk about traffic in the city, the evolution of traffic lights is a journey from mindless automation to increasingly intelligent, fluid traffic management. In our approach, presented in this paper, reinforcement-learning mechanism based on cost function is introduced to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999)). O...
Objective:To briefly introduce the increase in the number of motor vehicles in our country and main research advances of traffic medicine.Methods:To collect the relative data issued by government and the papers pulished in the newspapers or medical journals,and analyze them with combination of our own research work. Results:1.The number of motor vehicles in our country in 1997 was 680.02 times more than that in 1951,and increases t 42.0932 million from 1.5887 million over the past two decades(1978-1997)since the reform and opening,with net increase of 40.5045 million,increasing about 25 times.During the same period,the number of motorcycles increased to 20.2221 million from 104.3 thousand,increasing about 193 times.There were 4.4 hundred million bicycles,accounting for one third or the total world wide,Over 30% to 50% of eople in cities used bicycles as their transport tool when they go out.2.In the 1990's (9190 to 1997),the number of motor vehicles increased 1.85 times,while road traffic accidents(RATs) only increased 0.22 times,the deaths and the injuries 0.5 and 0.23 times only,respectively,indicating that the increasing tendency of RTAs and casualties was controlled to some extent.3.The prople of 21 to 45 years old were dominant among all casualties.The sequence of deaths in order was pedestrians(26.5%),vehicle drivers(24.8%),passengers(24.3%),bicyclists(18.4%)and others (6.1%).4.Concerning the accident causes,human faults accounted for 92.9%,83.6% of RTAs wre due to the faults of motor vehicle drivers,and 1.5% of RTAs were due to driving after drinking with deaths occupying 2.9% of the total.5.Proneness to RTSs:6%-8% of motor vehical drivers had proneness to RTA,causing 35%-40% fo the totoal RTAs.6.Various bio-impact machines were developed.The maximum impact velocity could reach 324 km/h.They can be used to induce impact injuries on different animals,at different patterns and even on different regions of body.7.The inflicting mechanisms for cranioserebral and
Chow, A. H. F.
This thesis investigates analytical dynamic system optimal assignment with departure time choice in a rigorous and original way. Dynamic system optimal assignment is formulated here as a state-dependent optimal control problem. A fixed volume of traffic is assigned to departure times and routes such that the total system travel cost is minimized. Although the system optimal assignment is not a realistic representation of traffic, it provides a bound on performance and shows how...
Full Text Available Analysis of Speed Optimization Technique in Traffic is a very promising research problem. Searching foran efficient optimization method to increase the degree of speed optimization and thereby increasing thetraffic flow in a lane is a widely concerning issue. However, there has been a limited research effort on theoptimization of the lane usage with speed optimization. This paper presents a novel technique to solve theproblem optimally using the knowledge base analysis of speeds of vehicles, population of lanes , usingpartial modification of Swarm Intelligence which, in turn will act as a guide for design of lanes optimally toprovide better optimized traffic with less number of transitions of vehicles between lanes..
Full Text Available Analysis of Speed Optimization Technique in Traffic is a very promising research problem. Searching for an efficient optimization method to increase the degree of speed optimization and thereby increasing the traffic flow in a lane is a widely concerning issue. However, there has been a limited research effort on the optimization of the lane usage with speed optimization. This paper presents a novel technique to solve the problem optimally using the knowledge base analysis of speeds of vehicles, population of lanes , using partial modification of Swarm Intelligence which, in turn will act as a guide for design of lanes optimally to provide better optimized traffic with less number of transitions of vehicles between lanes..
Full Text Available Transport forms one of the primary needs in all categories of the population in modern society; it is of paramount concern for traffic engineers, transport planners, and policy makers to understand and evaluate the quality of service being provided by the transport facilities designed by them. This paper presents an investigation in profile geometric design and traffic flow operation on two-lane two-way highways and provides analyses that will help in a better understanding of traffic operation on these facilities to select the optimum profile configuration. The effects of influencing parameters consisting of grade, length of grade, traffic composition, and traffic volume are evaluated and finally a systematic procedure to evaluate flow rate under the base condition is presented. Finally, based on these achievements an algorithm is introduced to select optimum Finished Ground of profile view. Results show that the percentage of heavy vehicles has a contributing effect on traffic operation so that the optimum profile configuration is incredibly affected by this factor. Source data have been obtained from Highway Capacity Manual (HCM as a pioneer document in respect of quantifying the concept of capacity for a transport facility.
This book is a summary of more than a decade of research in the area of backend optimization. It contains the latest fundamental research results in this field. While existing books are often more oriented toward Masters students, this book is aimed more towards professors and researchers as it contains more advanced subjects.It is unique in the sense that it contains information that has not previously been covered by other books in the field, with chapters on phase ordering in optimizing compilation; register saturation in instruction level parallelism; code size reduction for software pipe
Tamas-Selicean, Domitian; Pop, Paul
This paper focuses on the optimization of the TTEthernet communication protocol, which offers three traffic classes: time-triggered (TT), sent according to static schedules, rate-constrained (RC) that has bounded end-to-end latency, and best-effort (BE), the classic Ethernet traffic, with no timing...... guarantees. In our earlier work we have proposed an optimization approach named DOTTS that performs the routing, scheduling and packing / fragmenting of TT and RC messages, such that the TT and RC traffic is schedulable. Although backwards compatibility with classic Ethernet networks is one of TTEthernet......’s strong points, there is little research on this topic. However, in this paper, we extend our DOTTS optimization approach to optimize TTEthernet networks, such that not only the TT and RC messages are schedulable, but we also maximize the available bandwidth for BE messages. The proposed optimization has...
Fedrigo, Enrico; Granelli, Fabrizio
TCP/IP represents the reference standard for the implementation of interoperable communication networks. Nevertheless, the layering principle at the basis of interoperability severely limits the performance of data communication networks, thus requiring proper configuration and management in order to provide effective management of traffic flows. This paper presents a brief survey related to network optimization using Traffic Engineering algorithms, aiming at providing additional insight to t...
Growing concerns over the scalability of air traffic operations, air transportation fuel emissions and prices, as well as the advent of communication and sensing technologies motivate improvements to the air traffic management system. To address such improvements, in this thesis a hybrid dynamical model as an abstraction of the air traffic system is considered. Wind and hazardous weather impacts are included using a stochastic model. This thesis focuses on the design of algorithms for verification and control of hybrid and stochastic dynamical systems and the application of these algorithms to air traffic management problems. In the deterministic setting, a numerically efficient algorithm for optimal control of hybrid systems is proposed based on extensions of classical optimal control techniques. This algorithm is applied to optimize the trajectory of an Airbus 320 aircraft in the presence of wind and storms. In the stochastic setting, the verification problem of reaching a target set while avoiding obstacles (reach-avoid) is formulated as a two-player game to account for external agents' influence on system dynamics. The solution approach is applied to air traffic conflict prediction in the presence of stochastic wind. Due to the uncertainty in forecasts of the hazardous weather, and hence the unsafe regions of airspace for aircraft flight, the reach-avoid framework is extended to account for stochastic target and safe sets. This methodology is used to maximize the probability of the safety of aircraft paths through hazardous weather. Finally, the problem of modeling and optimization of arrival air traffic and runway configuration in dense airspace subject to stochastic weather data is addressed. This problem is formulated as a hybrid optimal control problem and is solved with a hierarchical approach that decouples safety and performance. As illustrated with this problem, the large scale of air traffic operations motivates future work on the efficient
Full Text Available We propose a more practical spectrum sensing optimization problem in cognitive radio networks (CRN, by considering the data traffic of second user (SU. Compared with most existing work, we do not assume that SU always has packets to transmit; instead, we use the actual data transmitted per second rather than the channel capacity as the achievable throughput, to reformulate the Sensing-Throughput Tradeoff problem. We mathematically analyze the problem of optimal sensing time to maximize the achievable throughput, based on the data traffic of SU. Our model is more general because the traditional Sensing-Throughput Tradeoff model can be seen as a special case of our model. We also prove that the throughput is a concave function of sensing time and there is only one optimal sensing time value which is determined by the data traffic. Simulation results show that the proposed approach outperforms existing methods.
Praha: ÚTIA AV ČR, 2006 - (Přikryl, J.; Šmídl, V.). s. 43-44 [International PhD Workshop on Interplay of Societal and Technical Decision - Making , Young Generation Viewpoint /7./. 25.09.2006-30.09.2006, Hrubá Skála] Grant ostatní: MD ČR(CZ) 1F43A/003/120 Institutional research plan: CEZ:AV0Z10750506 Keywords : linear programming * traffic flow control * control on horizon Subject RIV: BC - Control Systems Theory
Salvador IBARRA-MARTÍNEZ; José A. CASTÁN-ROCHA; Julio LARIA-MENCHACA
This paper is devoted to developing and evaluating a set of technologies with the objective of designing a method-ology for the implementation of sophisticated traffic lights by means of rational agents. These devices would be capable of op-timizing the behavior of a junction with multiple traffic signals, reaching a higher level of autonomy without losing reliability, accuracy, or efficiency in the offered services. In particular, each rational agent in a traffic signal will be able to analyze the requirements and constraints of the road, in order to know its level of demand. With such information, the rational agent will adapt its light cycles with the view of accomplishing more fluid traffic patterns and minimizing the pollutant environmental emissions produced by vehicles while they are stopped at a red light, through using a case-based reasoning (CBR) adaptation. This paper also integrates a microscopic simulator developed to run a set of tests in order to compare the presented methodology with traditional traffic control methods. Two study cases are shown to demonstrate the efficiency of the introduced approach, increasing vehicular mobility and reducing harmful activity for the environment. For instance, in the first scenario, taking into account the studied traffic volumes, our approach increases mobility by 23%and reduces emissions by 35%. When the roads are managed by sophisticated traffic lights, a better level of service and considerable environmental benefits are achieved, demon-strating the utility of the presented approach.
Xu, Ke; Liu, Jiangchuan; Shen, Meng
Traffic Engineering (TE) leverages information of network traffic to generate a routing scheme optimizing the traffic distribution so as to advance network performance. However, optimize the link weights for OSPF to the offered traffic is an known NP-hard problem. In this paper, motivated by the fairness concept of congestion control, we firstly propose a new generic objective function, where various interests of providers can be extracted with different parameter settings. And then, we model the optimal TE as the utility maximization of multi-commodity flows with the generic objective function and theoretically show that any given set of optimal routes corresponding to a particular objective function can be converted to shortest paths with respect to a set of positive link weights. This can be directly configured on OSPF-based protocols. On these bases, we employ the Network Entropy Maximization(NEM) framework and develop a new OSPF-based routing protocol, SPEF, to realize a flexible way to split traffic ove...
Jack HADDAD; David MAHALEL; Ilya IOSLOVICH; Per-Olof GUTMAN
The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered. The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max-plus model. Two steady-state control problems are formulated: optimal steady-state with green duration constraints, and optimal steady-state control with lost time. In the case when the criterion is a strictly increasing, linear function of the queue lengths, the steady-state control problems can be solved analytically. The structure of constrained optimal steady-state traffic control is revealed, and the effect of the lost time on the optimal solution is illustrated.
Grunwald, Arthur J.; Shaviv, G. E.
This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.
Changhua Yao; Qihui Wu; Linfang Zhou
We propose a more practical spectrum sensing optimization problem in cognitive radio networks (CRN), by considering the data traffic of second user (SU). Compared with most existing work, we do not assume that SU always has packets to transmit; instead, we use the actual data transmitted per second rather than the channel capacity as the achievable throughput, to reformulate the Sensing-Throughput Tradeoff problem. We mathematically analyze the problem of optimal sensing time to maximize the ...
The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model
Scellato, S.; Fortuna, L.; Frasca, M.; Gómez-Gardeñes, J.; Latora, V.
Congestion in transport networks is a topic of theoretical interest and practical importance. In this paper we study the flow of vehicles in urban street networks. In particular, we use a cellular automata model on a complex network to simulate the motion of vehicles along streets, coupled with a congestion-aware routing at street crossings. Such routing makes use of the knowledge of agents about traffic in nearby roads and allows the vehicles to dynamically update the routes towards their destinations. By implementing the model in real urban street patterns of various cities, we show that it is possible to achieve a global traffic optimization based on local agent decisions.
Yeong, Kim Ming
Let us look at these social insects, which are relatively simple however, they can perform effective strategy following the simple, adaptive to local rules, which allows them to change according to the environment for survival. This uniqueness of the insect world helps us to understand that complex situation does have solution. The study of ant colonies behavior is an interesting issue that provides good modeling solution for difficult optimization and distributed control problems. Transporta...
Wei Zhang; Guozhen Tan; Nan Ding; Guangyuan Wang
This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the ...
Tomer, Elad; Safonov, Leonid; Madar, Nilly; Havlin, Shlomo
We study traffic flow on roads with a localized periodic inhomogeneity such as traffic signals, using a stochastic car-following model. We find that in cases of congestion, traffic flow can be optimized by controlling the inhomogeneity's frequency. By studying the wavelength dependence of the flux in stop-and-go traffic states, and exploring their stability, we are able to explain the optimization process. A general conclusion drawn from this study is, that the fundamental diagram of traffic ...
Soldo, Fabio; Markopoulou, Athina
In this paper, we consider the problem of blocking malicious traffic on the Internet, via source-based filtering. In particular, we consider filtering via access control lists (ACLs): these are already available at the routers today but are a scarce resource because they are stored in the expensive ternary content addressable memory (TCAM). Aggregation (by filtering source prefixes instead of individual IP addresses) helps reduce the number of filters, but comes also at the cost of blocking legitimate traffic originating from the filtered prefixes. We show how to optimally choose which source prefixes to filter, for a variety of realistic attack scenarios and operators' policies. In each scenario, we design optimal, yet computationally efficient, algorithms. Using logs from Dshield.org, we evaluate the algorithms and demonstrate that they bring significant benefit in practice.
This chapter deals with passenger and freight traffic, public and private transportation, traffic related environmental impacts, future developments, traffic indicators, regional traffic planning, health costs due to road traffic related air pollution, noise pollution, measures and regulations for traffic control and fuels for traffic. In particular energy consumption, energy efficiency, pollutant emissions ( CO2, SO2, NOx, HC, CO, N2O, NH3 and particulates) and environmental effects of the different types of traffic and different types of fuels are compared and studied. Legal regulations and measures for an effective traffic control are discussed. (a.n.)
Yit Kwong Chin
Full Text Available Congestions of the traffic flow within the urban traffic network have been a challenging task for all the urban developers. Many approaches have been introduced into the current system to solve the traffic congestion problems. Reconfiguration of the traffic signal timing plan has been carried out through implementation of different techniques. However, dynamic characteristics of the traffic flow increase the difficulties towards the ultimate solutions. Thus, traffic congestions still remain as unsolvable problems to the current traffic control system. In this study, artificial intelligence method has been introduced in the traffic light system to alter the traffic signal timing plan to optimize the traffic flows. Q-learning algorithm in this study has enhanced the traffic light system with learning ability. The learning mechanism of Q-learning enables traffic light intersections to release itself from traffic congestions situation. Adjacent traffic light intersections will work independently and yet cooperate with each others to a common goal of ensuring the fluency of the traffic flows within the traffic network. The simulated results show that the Q-Learning algorithm is able to learn from the dynamic traffic flow and optimize the traffic flow accordingly.
Bin He; Qiang Lu
In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the p...
Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.
Rao, R Venkata
Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational ...
Berg, Peter; Woods, Andrew
Car-following models provide both a tool to describe traffic flow and algorithms for autonomous cruise control systems. Recently developed optimal velocity models contain a relaxation term that assigns a desirable speed to each headway and a response time over which drivers adjust to optimal velocity conditions. These models predict traffic breakdown phenomena analogous to real traffic instabilities. In order to deepen our understanding of these models, in this paper, we examine the transition from a linear stable stream of cars of one headway into a linear stable stream of a second headway. Numerical results of the governing equations identify a range of transition phenomena, including monotonic and oscillating travelling waves and a time- dependent dispersive adjustment wave. However, for certain conditions, we find that the adjustment takes the form of a nonlinear traveling wave from the upstream headway to a third, intermediate headway, followed by either another traveling wave or a dispersive wave further downstream matching the downstream headway. This intermediate value of the headway is selected such that the nonlinear traveling wave is the fastest stable traveling wave which is observed to develop in the numerical calculations. The development of these nonlinear waves, connecting linear stable flows of two different headways, is somewhat reminiscent of stop-start waves in congested flow on freeways. The different types of adjustments are classified in a phase diagram depending on the upstream and downstream headway and the response time of the model. The results have profound consequences for autonomous cruise control systems. For an autocade of both identical and different vehicles, the control system itself may trigger formations of nonlinear, steep wave transitions. Further information is available [Y. Sugiyama, Traffic and Granular Flow (World Scientific, Singapore, 1995), p. 137].
Zaborovski, V.; Yegorov, S.; Podgurski, Y.; Shemanin, Y.
The main steps of automatic control methodology include the hierarchical representation of management system and the formal definitions of input variables, object and goal of control of each management level. A Petri net model of individual traffic source is presented. It is noted that the current set of traffic parameters recommended by ATM-forum is not enough to synthesize optimal traffic control system. The feature of traffic self-similarity can be used to effectively solve optimal control...
Baye, Michael R.; Babur De los Santos; Matthijs R. Wildenbeest
The lion’s share of retail traffic through search engines originates from organic (natural) rather than sponsored (paid) links. We use a dataset constructed from over 12,000 search terms and 2 million users to identify drivers of the organic clicks that the top 759 retailers received from search engines in August 2012. Our results are potentially important for search engine optimization (SEO). We find that a retailer’s investments in factors such as the quality and brand awareness of its site...
Optimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency. Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization. This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc...
Rios, Joseph Lucio; Sheth, Kapil S.; Guiterrez-Nolasco, Sebastian Armardo
The effectiveness of future decision support tools for Traffic Flow Management in the National Airspace System will depend on two major factors: computational burden and collaboration. Previous research has focused separately on these two aspects without consideration of their interaction. In this paper, their explicit combination is examined. It is shown that when user preferences are incorporated with an optimal approach to scheduling, runtime is not adversely affected. A benefit-cost ratio is used to measure the influence of user preferences on an optimal solution. This metric shows user preferences can be accommodated without inordinately, negatively affecting the overall system delay. Specifically, incorporating user preferences will increase delays proportionally to increased user satisfaction.
L. Abramova; Chernobaev, N.
A short review of main methods of traffic flow control is represented, great attention is paid to methods of coordinated control and quality characteristics of traffic control. The problem of parameter optimization of traffic coordinated control on the basis of vehicle delay minimizing at highway intersections has been defined.
Jin, Yanfei; Hu, Haiyan
Traffic jams may occur due to various reasons, such as traffic accidents, lane reductions and on-ramps. In order to suppress the traffic congestion in an optimal velocity traffic model without any driver's delay taken into account, a delayed-feedback control of both displacement and velocity differences is proposed in this study. By using the delay-independent stability criteria and the H∞-norm, the delayed-feedback control can be determined to stabilize the unstable traffic flow and suppress the traffic jam. The numerical case studies are given to demonstrate and verify the new control method. Furthermore, a comparison is made between the new control method and the method proposed by Konishi et al. [K. Konishi, M. Hirai, H. Kokame, Decentralized delayed-feedback control of an optimal velocity traffic model, Eur. Phys. J. B 15 (2000) 715-722]. The results show that the new control method makes the traffic flow more stable and improves the control performance.
Sutarto, Herman; Boel, René
Coordination of traffic streams in an urban network, controllable by switching traffic lights, requires a global macroscopic model of the evolution of the flows of vehicle. We propose the use fluid petri nets as modeling tools. For the design of on-line controllers for traffic lights we study the network-wide effects of different local perturbations of the traffic light switching times via fast simulation. The infinitesimal perturbation analysis can under certain conditions lead to optimal cl...
This dissertation presents dynamic stochastic optimization models for Air Traffic Flow Management (ATFM) that enables decisions to adapt to new information on evolving capacities of National Airspace System (NAS) resources. Uncertainty is represented by a set of capacity scenarios, each depicting a particular time-varying capacity profile of NAS resources. We use the concept of a scenario tree in which multiple scenarios are possible initially. Scenarios are eliminated as possibilities in a succession of branching points, until the specific scenario that will be realized on a particular day is known. Thus the scenario tree branching provides updated information on evolving scenarios, and allows ATFM decisions to be re-addressed and revised. First, we propose a dynamic stochastic model for a single airport ground holding problem (SAGHP) that can be used for planning Ground Delay Programs (GDPs) when there is uncertainty about future airport arrival capacities. Ground delays of non-departed flights can be revised based on updated information from scenario tree branching. The problem is formulated so that a wide range of objective functions, including non-linear delay cost functions and functions that reflect equity concerns can be optimized. Furthermore, the model improves on existing practice by ensuring efficient use of available capacity without necessarily exempting long-haul flights. Following this, we present a methodology and optimization models that can be used for decentralized decision making by individual airlines in the GDP planning process, using the solutions from the stochastic dynamic SAGHP. Airlines are allowed to perform cancellations, and re-allocate slots to remaining flights by substitutions. We also present an optimization model that can be used by the FAA, after the airlines perform cancellation and substitutions, to re-utilize vacant arrival slots that are created due to cancellations. Finally, we present three stochastic integer programming
Zaborovski, V; Podgurski, Y; Shemanin, Y
The main steps of automatic control methodology include the hierarchical representation of management system and the formal definitions of input variables, object and goal of control of each management level. A Petri net model of individual traffic source is presented. It is noted that the current set of traffic parameters recommended by ATM-forum is not enough to synthesize optimal traffic control system. The feature of traffic self-similarity can be used to effectively solve optimal control task. An example of an optimal control scheme for cell discarding algorithm is presented.
S H Melouk; B B Keskin; C Armbrester; M. Anderson
Traffic congestion has grown considerably in the United States over the past 20 years. In this paper, we develop a robust decision support tool based on simulation optimization to evaluate and recommend congestion mitigation strategies to transportation system decision-makers. A tabu search-based optimizer determines different network design strategies on the road network while a traffic simulator evaluates the goodness of fit. The tool is tested with real-world traffic data.
Shaoxin Yuan; Xiangmo Zhao; Yisheng An
In urban transportation network, traffic congestion is likely to occur at traffic bottlenecks. The signal timing at intersections together with static properties of left-turn and straight-through lanes of roads are two significant factors causing traffic bottlenecks. A discrete-time model of traffic bottleneck is hence developed to analyze these two factors, and a bottleneck indicator is introduced to estimate the comprehensive bottleneck degree of individual road in regional transportation n...
赵晓华; 陈阳舟; 崔平远
A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.
Full Text Available Battery life is a major issue for any mobile equipment, and reducing energy consumption via energy management in 3G LTE user equipment (UE will be essential for the delivery of a variety of services. Discontinuous transmission (DTX and reception (DRX have been designed to facilitate power management, but they can provide energy savings only via proper tuning. Relevant work in the literature mainly pertains only to discontinuous reception mode (DRX for downlink data. However, today’s increasingly powerful UEs can generate and upload significant amount of data. This paper proposes an energy management framework applicable to both discontinuous transmission (DTX and DRX power saving modes. In particular, in DTX mode it can reduce UE energy consumption for uplink intensive applications like telemedicine or social networking. The proposed novel energy management framework is based on jointly using a-priori analytical evaluation of a M/G/1/K finite uplink queue system for mixed traffic with an optimized DTX/DRX algorithm. DTX mode is modeled by an expression, through which the impact of quality of service (QoS parameters on the UE’s mean energy consumption for uplink transfer is determined. The model extracts and operates on the values computed for the M/G/1/K queue. Finally, a dynamic energy management algorithm for DRX/DTX modes is proposed for energy consumption optimization based on an integrated Analytical Hierarchy Process (AHP and Grey Relational Analysis (GRA. Analytical evaluation has shown that using our algorithm to tune DTX can achieve 49-73% energy saving over not using DTX.
R.A. Newby; G.J. Bruck; M.A. Alvin; T.E. Lippert
Reliable, maintainable and cost effective hot gas particulate filter technology is critical to the successful commercialization of advanced, coal-fired power generation technologies, such as IGCC and PFBC. In pilot plant testing, the operating reliability of hot gas particulate filters have been periodically compromised by process issues, such as process upsets and difficult ash cake behavior (ash bridging and sintering), and by design issues, such as cantilevered filter elements damaged by ash bridging, or excessively close packing of filtering surfaces resulting in unacceptable pressure drop or filtering surface plugging. This test experience has focused the issues and has helped to define advanced hot gas filter design concepts that offer higher reliability. Westinghouse has identified two advanced ceramic barrier filter concepts that are configured to minimize the possibility of ash bridge formation and to be robust against ash bridges should they occur. The ''inverted candle filter system'' uses arrays of thin-walled, ceramic candle-type filter elements with inside-surface filtering, and contains the filter elements in metal enclosures for complete separation from ash bridges. The ''sheet filter system'' uses ceramic, flat plate filter elements supported from vertical pipe-header arrays that provide geometry that avoids the buildup of ash bridges and allows free fall of the back-pulse released filter cake. The Optimization of Advanced Filter Systems program is being conducted to evaluate these two advanced designs and to ultimately demonstrate one of the concepts in pilot scale. In the Base Contract program, the subject of this report, Westinghouse has developed conceptual designs of the two advanced ceramic barrier filter systems to assess their performance, availability and cost potential, and to identify technical issues that may hinder the commercialization of the technologies. A plan for the Option I, bench
Gimenez, Lucas Chavarria; Kovacs, Istvan Z.; Wigard, Jeroen;
The objective of this paper is to propose traffic steering solutions that aim at optimizing the end-user throughput. Two different implementations of an active mode throughput-based traffic steering algorithm for Heterogeneous Networks (HetNet) are introduced. One that always forces handover of the...
Rajesh Kumar Ahirwar
Full Text Available Network operators often need to deal with events that compromise their networks. One approach to find these events is to monitor the aggregate traffic in one or several network links and then look for significant deviations from some statistical model of normal behavior. This problem, known as traffic anomaly diagnosis, involves two steps: anomaly detection and root cause analysis. Anomaly detection methods have to define first what constitutes normal traffic behavior. Given the large variability in Internet traffic behavior, current techniques learn their parametric models from traces that are assumed to contain no anomalies. Besides the computational overhead of periodically re-training the model, real traces are never guaranteed to be anomaly-free; anomalies in the training data can contaminate the detector’s definition of normal traffic behavior. Another problem with current anomaly detectors is that, by aggregating traffic before detection, they lose information about which specific flows cause the anomaly. Root cause analysis is the process of recovering this information, by going back to the original traffic traces looking for events that could explain the alarm. Currently, there are few automated techniques that can help with root cause analysis; operators often rely on ad-hoc manual procedures, which are both time-consuming and error-prone. In a large network with hundreds of links, the number of events that can trigger alarms may easily overload the Network Operations Center, making anomaly detection tools useless. In this thesis we design an anomaly diagnosis system (i.e., detection and root cause analysis that exposes a broad range of anomalies and automatically explains their causes. We design an anomaly detection method that uses a non-parametric model of normal traffic behavior, and thus is simple to compute and immune to data contamination. It also makes it easier to identify the flows responsible for an anomaly. Second, we
Fowdur, S. C.; Rughooputh, S. D. D. V.
Expansion of a road network has often been observed to cause more congestion and has led researchers to the formulation of traffic paradoxes such as the Pigou-Downs and the Braess paradoxes. In this paper, we present an application of advanced traffic signal control (ATSC) to overcome the Pigou-Downs paradox. Port Louis, the capital city of Mauritius is used to investigate the effect of using a harbor bridge to by-pass the city center. Using traffic cellular automata (TCA) simulations it has been shown how, if traffic is only gradually deviated along the by-pass, an overall longer travel time and decreased flux would result. By making use of ATSC, which involves traffic lights that sense the number of vehicles accumulated in the queue, better travel times and fluxes are achieved.
Haldors, Bruce; Bozzini, Anna; May, Adolf D.
The purpose of the Symposium on Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) was to allow researchers involved in ATM/ATIS work to become familiar with other research in those areas in the state of California. This document provides a brief summary outlining the presentations made at the symposium.
Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.
Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.
Panaggio, Mark J; Hu, Peiguang; Abrams, Daniel M
Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counter-intuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive dens...
Shu, Y; Daamen, W.; Ligteringen, H.; Hoogendoorn, S.P.
Due to the ever-increasing economic globalization, the scale of transportation through ports and waterways has increased sharply. As the capacity of maritime infrastructure in ports and inland waterways is limited, it is important to simulate vessel behavior to balance safety and capacity in restricted waterways. Currently many existing vessel simulation models focus mainly on vessel dynamics and maritime traffic in the open ocean. These models are, however, inapplicable to simulating vessel ...
Wang, Tiane; Niu, Taiyang; Wan, Baocheng; Li, Jian
This article is based on the traffic and patrol police service platform settings and scheduling, in order to achieve the main purpose of rapid containment for the suspect in an emergency event. Proposing new boundary definition based on graph theory, using 0-1 programming, Dijkstra algorithm, the shortest path tree (SPT) and some of the related knowledge establish a containment model. Finally, making a combination with a city-specific data and using this model obtain the best containment plan.
Habibi Aghdam, Hamed; Jahani Heravi, Elnaz; Puig, Domenec
Convolutional Neural Networks (CNN) beat the human performance on German Traffic Sign Benchmark competition. Both the winner and the runner-up teams trained CNNs to recognize 43 traffic signs. However, both networks are not computationally efficient since they have many free parameters and they use highly computational activation functions. In this paper, we propose a new architecture that reduces the number of the parameters 27% and 22% compared with the two networks. Furthermore, our network uses Leaky Rectified Linear Units (ReLU) as the activation function that only needs a few operations to produce the result. Specifically, compared with the hyperbolic tangent and rectified sigmoid activation functions utilized in the two networks, Leaky ReLU needs only one multiplication operation which makes it computationally much more efficient than the two other functions. Our experiments on the Gertman Traffic Sign Benchmark dataset shows 0:6% improvement on the best reported classification accuracy while it reduces the overall number of parameters 85% compared with the winner network in the competition.
Sanghyun, Ahn; Seungwoong, Ha; Kim, Soo Yong
A vital challenge for many socioeconomic systems is determining the optimum use of limited information. Traffic systems, wherein the range of resources is limited, are a particularly good example of this challenge. Based on bounded information accessibility in terms of, for example, high costs or technical limitations, we develop a new optimization strategy to improve the efficiency of a traffic system with signals and intersections. Numerous studies, including the study by Chowdery and Schadschneider (whose method we denote by ChSch), have attempted to achieve the maximum vehicle speed or the minimum wait time for a given traffic condition. In this paper, we introduce a modified version of ChSch with an independently functioning, decentralized control system. With the new model, we determine the optimization strategy under bounded information accessibility, which proves the existence of an optimal point for phase transitions in the system. The paper also provides insight that can be applied by traffic engineers to create more efficient traffic systems by analyzing the area and symmetry of local sites. We support our results with a statistical analysis using empirical traffic data from Seoul, Korea.
Full Text Available Wireless sensor networks (WSN are applied in Intelligent Transport System for data collection. For the low redundancy rate of the wireless sensor networks nodes of traffic information collection, the senor nodes should be deployed reasonably for the WSN nodes to work effectively, and, thus, the base network structure and the density optimization of the sensor network are one of the main problems of WSN application. This paper establishes the wireless sensor networks design optimization model oriented to the traffic information collection, solving the design optimization model with the chemical reaction optimization (CRO algorithm. The experimental results show that CRO algorithm outperforms the traditional particle swarm optimization (PSO in solving the wireless sensor network design optimization oriented to the traffic information collection, capable of optimizing the wireless sensor network deployment of traffic information collection to contribute to the great improvement of the comprehensive value of the network performance. The reasonable design of the wireless sensor network nodes has great significance for the information collection, post-maintenance-and-extension, and cost saving of a monitoring system.
Sadovsky, Alexander V .; Swenson, Harry N.; Haskell, William B.; Rakas, Jasenka
The current operational practice in scheduling air traffic arriving at an airport is to adjust flight schedules by delay, i.e. a postponement of an aircrafts arrival at a scheduled location, to manage safely the FAA-mandated separation constraints between aircraft. To meet the observed and forecast growth in traffic demand, however, the practice of time advance (speeding up an aircraft toward a scheduled location) is envisioned for future operations as a practice additional to delay. Time advance has two potential advantages. The first is the capability to minimize, or at least reduce, the excess separation (the distances between pairs of aircraft immediately in-trail) and thereby to increase the throughput of the arriving traffic. The second is to reduce the total traffic delay when the traffic sample is below saturation density. A cost associated with time advance is the fuel expenditure required by an aircraft to speed up. We present an optimal control model of air traffic arriving in a terminal area and solve it using the Pontryagin Maximum Principle. The admissible controls allow time advance, as well as delay, some of the way. The cost function reflects the trade-off between minimizing two competing objectives: excess separation (negatively correlated with throughput) and fuel burn. A number of instances are solved using three different methods, to demonstrate consistency of solutions.
Highlights: → We develop a dynamical system with Advanced Travelers Information System (ATIS). → We use the dynamical system to study stability of the traffic network with ATIS. → It is found that some periodic attractors appear in some cases. → A road pricing is implemented to alleviate the instability of the traffic network with ATIS. - Abstract: Since the notion of user equilibrium (UE) was proposed by Wardrop , it has become a cornerstone for traffic assignment analysis. But, it is not sufficient to only ask whether equilibrium exists or not; it is equally important to ask whether and how the system can achieve equilibrium. Meanwhile, stability is an important performance in the sense that if equilibrium is unsustainable, both the equilibrium and the trajectory are sensitive to disturbances, even a small perturbation will result in the system evolution away from the equilibrium point. These incentive a growing interest in day-to-day dynamics. In this paper, we develop a dynamical system with Advanced Traveler Information System (ATIS) and study the stability of the network with ATIS. A simple network is used to simulate the model, and the results show that there exist periodic attractors in the traffic network in some cases (for example, the market penetration level of ATIS is 0.25 and traffic demand is 2 unit). It is found that the logit parameter of the dynamical model and the traffic demand can also affect the stability of the traffic network. More periodic attractors appear in the system when the traffic demand is large and the low logit parameter can delay the appearance of periodic attractors. By simulation, it can be concluded that if the range of the periodic attractors' domain of the simple network is known, the road pricing based on the range of the attraction domain is effective to alleviate the instability of the system.
In this work, we investigate aspects of building design that can be optimized. Architectural features that we explore include pillar placement in simple corridors, doorway placement in buildings, and agent placement for information dispersement in an evacuation. The metrics utilized are tuned to the specific scenarios we study, which include continuous flow pedestrian movement and building evacuation. We use Multidimensional Direct Search (MDS) optimization with an extreme barrier criteria to find optimal placements while enforcing building constraints. © 2013 IEEE.
Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing
The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle's speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073
Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing
The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073
R. J. Haines
Full Text Available Allocating bandwidth between different forms of coexisting traffic (such as web-browsing, streaming, and telephony within a wireless LAN is a challenging and interesting problem. Centralized coordination functions in wireless LANs offer several advantages over distributed approaches, having the benefit of a system overview at the controller, but obtaining a stable configuration of bandwidth allocation for the system is nontrivial. We present, review, and compare different mechanisms to achieve this end, and a number of different means of obtaining the configurations themselves. We describe an analytical model of the system under consideration and present two mathematical approaches to derive solutions for any system configuration and deployment, along with an adaptive feedback-based solution. We also describe a comprehensive simulation-based model for the problem, and a prototype that allows comparison of these approaches. Our investigations demonstrate that a self-adaptive dynamic approach far outperforms any static scheme, and that using a mathematical model to produce the configurations themselves confers several advantages.
Full Text Available Allocating bandwidth between different forms of coexisting traffic (such as web-browsing, streaming, and telephony within a wireless LAN is a challenging and interesting problem. Centralized coordination functions in wireless LANs offer several advantages over distributed approaches, having the benefit of a system overview at the controller, but obtaining a stable configuration of bandwidth allocation for the system is nontrivial. We present, review, and compare different mechanisms to achieve this end, and a number of different means of obtaining the configurations themselves. We describe an analytical model of the system under consideration and present two mathematical approaches to derive solutions for any system configuration and deployment, along with an adaptive feedback-based solution. We also describe a comprehensive simulation-based model for the problem, and a prototype that allows comparison of these approaches. Our investigations demonstrate that a self-adaptive dynamic approach far outperforms any static scheme, and that using a mathematical model to produce the configurations themselves confers several advantages.
Musong Gu; Lei You; Jun Hu; Lintao Duan; Zhen Zuo
Wireless sensor networks (WSN) are applied in Intelligent Transport System for data collection. For the low redundancy rate of the wireless sensor networks nodes of traffic information collection, the senor nodes should be deployed reasonably for the WSN nodes to work effectively, and, thus, the base network structure and the density optimization of the sensor network are one of the main problems of WSN application. This paper establishes the wireless sensor networks design optimization model...
This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.
Full Text Available Despite the flow fluctuations and increased traffic demand in Macedonian cities in the last fifteen years, Republic of Macedonia is one of those countries which still employ only the traditional systems of traffic management and control. A general call for “…something has to be done…” becomes obvious. The best practices have shown that this can be realized through unconventional solutions, i.e. by means of advanced traffic management (ATM. A very reasonable example of such a system is the vehicle actuated control system that we have found to be quite challenging to do our research. It was concluded that the overall intersection performance could be improved both by adequate inductive loop detector placement and by interaction with signal parameters.
Nakayama, Akihiro; Kikuchi, Macoto; Shibata, Akihiro; Sugiyama, Yuki; Tadaki, Shin-ichi; Yukawa, Satoshi
We have experimentally confirmed that the occurrence of a traffic jam is a dynamical phase transition (Tadaki et al 2013 New J. Phys. 15 103034, Sugiyama et al 2008 New J. Phys. 10 033001). In this study, we investigate whether the optimal velocity (OV) model can quantitatively explain the results of experiments. The occurrence and non-occurrence of jammed flow in our experiments agree with the predictions of the OV model. We also propose a scaling rule for the parameters of the model. Using this rule, we obtain critical density as a function of a single parameter. The obtained critical density is consistent with the observed values for highway traffic.
Davoodi, M.; Mesgari, M. S.
Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.
A well-known approach to intradomain traffic engineering consists in finding the set of link weights that minimizes a network-wide objective function for a given intradomain traffic matrix. This approach is inadequate because it ignores a potential impact on interdomain routing. Indeed, the resulting set of link weights may trigger BGP to change the BGP next hop for some destination prefixes, to enforce hot-potato routing policies. In turn, this results in changes in the intradomain traffic matrix that have not been anticipated by the link weights optimizer, possibly leading to degraded network performance. We propose a BGP-aware link weights optimization method that takes these effects into account, and even turns them into an advantage. This method uses the interdomain traffic matrix and other available BGP data, to extend the intradomain topology with external virtual nodes and links, on which all the well-tuned heuristics of a classical link weights optimizer can be applied. A key innovative asset of our ...
Yang, Wei; Yang, Oliver W.
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
T.Karthikeyan , S.Sujatha
Full Text Available Based on Agent Technology, Service Oriented Architecture and RFID,this paper puts forward a ‘real time paradigm’ traffic congestion control strategy in metropolitan cities. This strategy uses TCL algorithm in order to provide optimal traffic performance evaluation considering the parameter, velocity of vehicles by implementing RMI & SOAP interfaces. This building block of traffic and transportation system is more suited for the proposed mobile agents FMSA(Fixed Monitor Stationary Agent & IMAC(Interactive Mobile Agent for Client because this model works on the Agent technology that can be developed using Java and JADE Agent platform under dynamic changing environments. The developed FMSA & IMAC agents makes real time decisions for choosing the best path in road traffic network to avoid congestion by considering the parameters for optimization like mainly the velocity of vehicles in the existing lane. This paper also compares the experimental results obtained by the system before and after the implementation of FMSA & IMAC agents to prove the significant performance for finding the best path by confirming the better efficiency & scalability improvement of our framework.
H. G. Visser
Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.
Yang, Wei; Sun, Wanlu
Energy-efficient communication is an important requirement for mobile relay networks due to the limited battery power of user terminals. This paper considers energy-efficient relaying schemes through selection of mobile relays in cooperative cellular systems with asymmetric traffic. The total energy consumption per information bit of the battery-powered terminals, i.e., the mobile station (MS) and the relay, is derived in theory. In the Joint Uplink and Downlink Relay Selection (JUDRS) scheme we proposed, the relay which minimizes the total energy consumption is selected. Additionally, the energy-efficient cooperation regions are investigated, and the optimal relay location is found for cooperative cellular systems with asymmetric traffic. The results reveal that the MS-relay and the relay-base station (BS) channels have different influence over relay selection decisions for optimal energy-efficiency. Information theoretic analysis of the diversity-multiplexing tradeoff (DMT) demonstrates that the proposed sc...
Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria
Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.
Full Text Available Recently, vehicular networking has grown up in terms of interest and transmission capability, due to the possibility of exploiting the distributed communication paradigm in a mobile scenario, where moving nodes are represented by vehicles. In this paper, we focus our attention on the optimization of traffic flowing in a vehicular environment with vehicle-roadside capability. As shown in the next sections, the proposed idea exploits the information that is gathered by road-side units with the main aim of redirecting traffic flows (in terms of vehicles to less congested roads, with an overall system optimization, also in terms of Carbon Dioxide emissions reduction. A deep campaign of simulations has been carried out to give more effectiveness to our proposal.
Gaididei, Yuri Borisovich; Berkemer, Rainer; Caputo, Jean Guy;
A follow-the-leader model of traffic flow on a closed loop is considered in the framework of the extended optimal velocity (OV) model where the driver reacts to both the following and the preceding car. Periodic wave train solutions that describe the formation of traffic congestion patterns are...
The design, standardization and future deployment of vehicular communications systems have been driven so far by safety applications. There are two more aspects of the vehicular networking that have increased their importance in the last years: infotainment and traffic efficiency, as they can improve drivers’ experience, making vehicular communications systems more attractive to end-users. In this thesis we propose optimization mechanisms for both types of vehicular services. Infotainment ser...
Cruzado Pérez, Laura
Broadband Wireless Networking topics: 5G, wireless underground sensor networks, software defined networking The new emerging networking paradigm of Software Defined Networks, a solution that separates the network control plane from the data forwarding plane, has been the main focus of recently research works. Nevertheless, Traffic Engineering is an important problem to optimize the network performance, especially for a centralized controlled network such as the SDN, by dynamically analyzin...
Nowadays, society faces several traffic related problems, such as traffic jams, time loss, lower traffic safety, increased pollution, etc., especially in urban areas. This is caused by high traffic volumes, which often exceed the capacity of the road infrastructure, particularly in peak hours. A common way of managing traffic in urban areas is traffic light control, which plays a key role in traffic safety and efficiency. To reduce delays the traffic light controllers should adjust to changin...
The Idaho National Engineering and Environmental Laboratory (INEEL) is supporting the National Aeronautics and Space Administration in the development of advanced air traffic management (ATM) systems as part of the Advanced Air Transportation Technologies program. As part of this program INEEL conducted a survey of human-system safety methods that have been applied to complex technical systems, to identify lessons learned from these applications and provide recommendations for the development of advanced ATM systems. The domains that were surveyed included offshore oil and gas, commercial nuclear power, commercial aviation, and military. The survey showed that widely different approaches are used in these industries, and that the methods used range from very high-level, qualitative approaches to very detailed quantitative methods such as human reliability analysis (HRA) and probabilistic safety assessment (PSA). In addition, the industries varied widely in how effectively they incorporate human-system safety assessment in the design, development, and testing of complex technical systems. In spite of the lack of uniformity in the approaches and methods used, it was found that methods are available that can be combined and adapted to support the development of advanced air traffic management systems (author) (ml)
Nanda, P.; Ansu, Y.; Manuel, E. H., Jr.; Price, W. G., Jr.
The advanced cogeneration technology economic optimization study (ACTEOS) was undertaken to extend the results of the cogeneration technology alternatives study (CTAS). Cost comparisons were made between designs involving advanced cogeneration technologies and designs involving either conventional cogeneration technologies or not involving cogeneration. For the specific equipment cost and fuel price assumptions made, it was found that: (1) coal based cogeneration systems offered appreciable cost savings over the no cogeneration case, while systems using coal derived liquids offered no costs savings; and (2) the advanced cogeneration systems provided somewhat larger cost savings than the conventional systems. Among the issues considered in the study included: (1) temporal variations in steam and electric demands; (2) requirements for reliability/standby capacity; (3) availability of discrete equipment sizes; (4) regional variations in fuel and electricity prices; (5) off design system performance; and (6) separate demand and energy charges for purchased electricity.
Popovska Avramova, Andrijana; Iversen, Villy Bæk
nature of radio access networks are considered as important factors for performance improvement by multi-stream aggregation. Therefore, in our model, the networks are represented by different queueing systems in order to indicate networks with opposite quality of service provisioning, capacity and delay...... variations. Furthermore, services with different traffic characteristics in terms of quality of service requirements are considered. The simulation results show the advantages of our scheme with respect to efficient increase in data rate and delay performance compared to traditional schemes.......This paper investigates an optimal traffic rate allocation method for multi-stream aggregation over heterogeneous networks that deals with effective integration of two or more heterogeneous links for improved data throughput and enhanced quality of experience. The heterogeneity and the dynamic...
Popovska Avramova, Andrijana; Iversen, Villy Bæk
This paper investigates an optimal traffic rate allocation method for multi-stream aggregation over heterogeneous networks that deals with effective integration of two or more heterogeneous links for improved data throughput and enhanced quality of experience. The heterogeneity and the dynamic...... nature of radio access networks are considered as important factors for performance improvement by multi-stream aggregation. Therefore, in our model, the networks are represented by different queueing systems in order to indicate networks with opposite quality of service provisioning, capacity and delay...
Rios-Torres, Jackeline [ORNL; Malikopoulos, Andreas [ORNL; Pisu, Pierluigi [Clemson University
This paper addresses the problem of coordinating online connected vehicles at merging roads to achieve a smooth traffic flow without stop-and-go driving. We present a framework and a closed-form solution that optimize the acceleration profile of each vehicle in terms of fuel economy while avoiding collision with other vehicles at the merging zone. The proposed solution is validated through simulation and it is shown that coordination of connected vehicles can reduce significantly fuel consumption and travel time at merging roads.
Yit Kwong Chin; Heng Jin Tham; N.S.V. Kameswara Rao; Nurmin Bolong; Kenneth Tze Kin Teo
Congestions of the traffic flow within the urban traffic network have been a challenging task for all the urban developers. Many approaches have been introduced into the current system to solve the traffic congestion problems. Reconfiguration of the traffic signal timing plan has been carried out through implementation of different techniques. However, dynamic characteristics of the traffic flow increase the difficulties towards the ultimate solutions. Thus, traffic congestions still remain a...
Reliable, maintainable and cost effective hot gas particulate filter technology is critical to the successful commercialization of advanced, coal-fired power generation technologies, such as IGCC and PFBC. In pilot plant testing, the operating reliability of hot gas particulate filters have been periodically compromised by process issues, such as process upsets and difficult ash cake behavior (ash bridging and sintering), and by design issues, such as cantilevered filter elements damaged by ash bridging, or excessively close packing of filtering surfaces resulting in unacceptable pressure drop or filtering surface plugging. This test experience has focused the issues and has helped to define advanced hot gas filter design concepts that offer higher reliability. Westinghouse has identified two advanced ceramic barrier filter concepts that are configured to minimize the possibility of ash bridge formation and to be robust against ash bridges should they occur. The ''inverted candle filter system'' uses arrays of thin-walled, ceramic candle-type filter elements with inside-surface filtering, and contains the filter elements in metal enclosures for complete separation from ash bridges. The ''sheet filter system'' uses ceramic, flat plate filter elements supported from vertical pipe-header arrays that provide geometry that avoids the buildup of ash bridges and allows free fall of the back-pulse released filter cake. The Optimization of Advanced Filter Systems program is being conducted to evaluate these two advanced designs and to ultimately demonstrate one of the concepts in pilot scale. In the Base Contract program, the subject of this report, Westinghouse has developed conceptual designs of the two advanced ceramic barrier filter systems to assess their performance, availability and cost potential, and to identify technical issues that may hinder the commercialization of the technologies. A plan for the Option I, bench-scale test program has also been developed based
Zhang, Yue J. [Boston University; Malikopoulos, Andreas [ORNL; Cassandras, Christos G. [Boston University
We address the problem of coordinating online a continuous flow of connected and automated vehicles (CAVs) crossing two adjacent intersections in an urban area. We present a decentralized optimal control framework whose solution yields for each vehicle the optimal acceleration/deceleration at any time in the sense of minimizing fuel consumption. The solu- tion, when it exists, allows the vehicles to cross the intersections without the use of traffic lights, without creating congestion on the connecting road, and under the hard safety constraint of collision avoidance. The effectiveness of the proposed solution is validated through simulation considering two intersections located in downtown Boston, and it is shown that coordination of CAVs can reduce significantly both fuel consumption and travel time.
Full Text Available Nowadays, reducing the energy and fuel consumption of road vehicles is a key issue. Different strategies have been proposed. One of them is to promote Eco-driving behaviour among drivers. Most Eco-driving tips take into account only the road stretch where the vehicle is located. However, larger improvements could be achieved if information from subsequent stretches is used. The main objective of this work is to develop a system to warn the driver in real time of the optimal speed that should be maintained on every road segment in order to optimize the energy used and the fuel consumed while observing a time schedule. The system takes into account the road vertical profile, the fixed and variable speed limits and the traffic information retrieved using V2V and V2I communications. The system has been tested on real road sections with satisfactory results in fuel savings.
McCormack, Michael J.; Gibson, Alec K.; Dennis, Noah E.; Underwood, Matthew C.; Miller,Lana B.; Ballin, Mark G.
Abstract-Next Generation Air Transportation System (NextGen) applications reliant upon aircraft data links such as Automatic Dependent Surveillance-Broadcast (ADS-B) offer a sweeping modernization of the National Airspace System (NAS), but the aviation stakeholder community has not yet established a positive business case for equipage and message content standards remain in flux. It is necessary to transition promising Air Traffic Management (ATM) Concepts of Operations (ConOps) from simulation environments to full-scale flight tests in order to validate user benefits and solidify message standards. However, flight tests are prohibitively expensive and message standards for Commercial-off-the-Shelf (COTS) systems cannot support many advanced ConOps. It is therefore proposed to simulate future aircraft surveillance and communications equipage and employ an existing commercial data link to exchange data during dedicated flight tests. This capability, referred to as the Networked Air Traffic Infrastructure Validation Environment (NATIVE), would emulate aircraft data links such as ADS-B using in-flight Internet and easily-installed test equipment. By utilizing low-cost equipment that is easy to install and certify for testing, advanced ATM ConOps can be validated, message content standards can be solidified, and new standards can be established through full-scale flight trials without necessary or expensive equipage or extensive flight test preparation. This paper presents results of a feasibility study of the NATIVE concept. To determine requirements, six NATIVE design configurations were developed for two NASA ConOps that rely on ADS-B. The performance characteristics of three existing in-flight Internet services were investigated to determine whether performance is adequate to support the concept. Next, a study of requisite hardware and software was conducted to examine whether and how the NATIVE concept might be realized. Finally, to determine a business case
Juretić, Sandra; Cerović, Ljerka; Galović, Tomislav
The subject of the analysis in this paper is traffic in the Port of Rijeka, the largest and the most significant Croatian port for domestic and international public, predominantly cargo traffic, whose role, considering numerous plans for comprehensive modernisation and revitalisation of the Rijeka traffic route and hypercomplex traffic system, gains additional significance in terms of its impact on the general prosperity of the Rijeka area and the entire Croatia. The research in this ...
Navaravong, Leenhapat; Pasiliao, Eduardo L; Barnette, Gregory L; Dixon, Warren E
Systems of networked mobile robots, such as unmanned aerial or ground vehicles, will play important roles in future military and commercial applications. The communications for such systems will typically be over wireless links and may require that the robots form an ad hoc network and communicate on a peer-to-peer basis. In this paper, we consider the problem of optimizing the network topology to minimize the total traffic in a network required to support a given set of data flows under constraints on the amount of movement possible at each mobile robot. In this paper, we consider a subclass of this problem in which the initial and final topologies are trees, and the movement restrictions are given in terms of the number of edges in the graph that must be traversed. We develop algorithms to optimize the network topology while maintaining network connectivity during the topology reconfiguration process. Our topology reconfiguration algorithm uses the concept of prefix labelling and routing to move nodes throu...
Various different advanced stellarator configurations of the linked mirror type (LIMAS) have been investigated which differ in the magnetic mirror ratio and twist on the magnetic axis. One configuration is presented in the following. The vacuum fields are given analytically by a finite set of Dommaschk potentials. The magnetic field properties weighed in the optimization procedure are: the residue R* of two reference fixed lines (where the pressure gradient is high) which start at Z = 0 in the two symmetry planes and have the same value of the twist ι; the associated aspect ratio A; the difference ΔF of the magnetic flux F = ∫ A.dx between these two closed field lines belonging to the same rational ι-value (A is a vector potential, x is the radius vector, the line integral is performed over each of the fixed field lines); the deficit of the Hamada condition that ∫dl/B should have the same value for these two fixed lines; a condition on the magnetic well (ΔV'/V'ax ||2/j2>1/2 of the Pfirsch-Schlueter current density; the deviation of contours of B = const from contours of Q ∫dU/B2 = const (U is the scalar potential). This condition has the effect that the particles see small variations of the magnetic field along their poloidal rotation. This favours small values of the ambipolar diffusion coefficients in the long mean free path regime. The implementation of this constraint uses a Fourier decomposition of the magnetic field strength along a closed field line with respect to Q. The corresponding Bessel inequality is used as a quadratic measure (PR) of the 'amount of independency' of the Fourier coefficients as the poloidal coordinate. Some of the quoted conditions are also applied at a pair of fixed lines in the boundary region. (author) 4 refs., 11 figs
Wing, David J.; Ballin, Mark G.; Koczo, Stefan, Jr.; Vivona, Robert A.; Henderson, Jeffrey M.
The concept of Traffic Aware Strategic Aircrew Requests (TASAR) combines Automatic Dependent Surveillance Broadcast (ADS-B) IN and airborne automation to enable user-optimal in-flight trajectory replanning and to increase the likelihood of Air Traffic Control (ATC) approval for the resulting trajectory change request. TASAR is designed as a near-term application to improve flight efficiency or other user-desired attributes of the flight while not impacting and potentially benefiting ATC. Previous work has indicated the potential for significant benefits for each TASAR-equipped aircraft. This paper will discuss the approach to minimizing TASAR's cost for implementation and accelerating readiness for near-term implementation.
The approach to carrying out multi-discipline aerospace design studies in the future, especially in massively parallel computing environments, comprises of choosing (1) suitable solvers to compute solutions to equations characterizing a discipline, and (2) efficient optimization methods. In addition, for aerodynamic optimization problems, (3) smart methodologies must be selected to modify the surface shape. In this research effort, a 'direct' optimization method is implemented on the Cray C-90 to improve aerodynamic design. It is coupled with an existing implicit Navier-Stokes solver, OVERFLOW, to compute flow solutions. The optimization method is chosen such that it can accomodate multi-discipline optimization in future computations. In the work , however, only single discipline aerodynamic optimization will be included.
考虑城市交通事故与道路网结构的关系,结合交通事故导致的时间延误,提出了基于交通安全的城市路网结构优化方法.首先分析了不同等级道路之间的衔接方式对出行者选择路径行为的影响,总结了交通事故的影响因素.然后在此基础上提出了基于交通安全的路网构造原则,建立了以路网安全度最大为目标的路网结构模型,并通过求解模型确定各路段的道路等级,得到安全度和结构不同的若干个路网.通过考虑交通事故时间延误情况下,进行随机均衡分配,得到路网各路段的交通量,并计算各路网的交通事故次数.最后提出了路网的安全性评价指标,分析交通事故次数和路网结构指标的关系,提出了考虑安全性的路网结构优化措施,并用实例验证了优化措施的有效性.%Considered the relationship between urban traffic accidents and road network structure, combined with traffic accident delay, an urban road network structure optimization method based on traffic safety was advanced. At first, the influence of joining style of different grade roads on route choosing behaviors of travelers was analyzed, and influencing factors of traffic accidents were summarized. Based on which, road network constructing principles based on traffic safety were advanced, and a road network structure model with the largest safety degree as the goal was established. The road sections' grade was determined through solving the model, and several road networks with different safety degrees and structures were got. Then, a random equilibrium distribution method was used to determine all sections' traffic volumes considering the traffic accident delay, and the networks' accidents were calculated. At last, the network security evaluation indexes were proposed, the relation between accidents and network structure indexes were analyzed, the measures of road network structure optimization considering safety were
Bertsimas, Dimitris; Odoni, Amedeo
This document presents a critical review of the principal existing optimization models that have been applied to Air Traffic Flow Management (TFM). Emphasis will be placed on two problems, the Generalized Tactical Flow Management Problem (GTFMP) and the Ground Holding Problem (GHP), as well as on some of their variations. To perform this task, we have carried out an extensive literature review that has covered more than 40 references, most of them very recent. Based on the review of this emerging field our objectives were to: (i) identify the best available models; (ii) describe typical contexts for applications of the models; (iii) provide illustrative model formulations; and (iv) identify the methodologies that can be used to solve the models. We shall begin our presentation below by providing a brief context for the models that we are reviewing. In Section 3 we shall offer a taxonomy and identify four classes of models for review. In Sections 4, 5, and 6 we shall then review, respectively, models for the Single-Airport Ground Holding Problem, the Generalized Tactical FM P and the Multi-Airport Ground Holding Problem (for the definition of these problems see Section 3 below). In each section, we identify the best available models and discuss briefly their computational performance and applications, if any, to date. Section 7 summarizes our conclusions about the state of the art.
Full Text Available Traditional coupled aerostructural design optimization (ASDO of aircraft based on high-fidelity models is computationally expensive and inefficient. To improve the efficiency, the key is to predict aerostructural performance of the aircraft efficiently. The cruise shape of the aircraft is parameterized and optimized in this paper, and a methodology named reverse iteration of structural model (RISM is adopted to get the aerostructural performance of cruise shape efficiently. A new mathematical explanation of RISM is presented in this paper. The efficiency of RISM can be improved by four times compared with traditional static aeroelastic analysis. General purpose computing on graphical processing units (GPGPU is adopted to accelerate the RISM further, and GPU-accelerated RISM is constructed. The efficiency of GPU-accelerated RISM can be raised by about 239 times compared with that of the loosely coupled aeroelastic analysis. Test shows that the fidelity of GPU-accelerated RISM is high enough for optimization. Optimization framework based on Kriging model is constructed. The efficiency of the proposed optimization system can be improved greatly with the aid of GPU-accelerated RISM. An unmanned aerial vehicle (UAV is optimized using this framework and the range is improved by 4.67% after optimization, which shows effectiveness and efficiency of this framework.
Aage, Niels; Amir, Oded; Clausen, Anders;
This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities in...
Li, Zhening; Ling, Chen; Wang, Yiju; Yang, Qingzhi
Tensor analysis (also called as numerical multilinear algebra) mainly includes tensor decomposition, tensor eigenvalue theory and relevant algorithms. Polynomial optimization mainly includes theory and algorithms for solving optimization problems with polynomial objects functions under polynomial constrains. This survey covers the most of recent advances in these two fields. For tensor analysis, we introduce some properties and algorithms concerning the spectral radius of nonnegative tensors'...
Aage, Niels; Amir, Oded; Clausen, Anders;
This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities in...... frames are implemented. The developed procedures allow for the exploration of new territories in optimization of architectural structures, and offer new methodological strategies for bridging conceptual gaps between optimization and architectural practice....
National Aeronautics and Space Administration — Controlling air traffic on all temporal and spatial scales – from a single aircraft to the entire airspace – can be formally stated as a dynamic,...
Marceau, Gaétan; Savéant, Pierre; Schoenauer, Marc
With the objective of handling the airspace sector congestion subject to continuously growing air traffic, we suggest to create a collaborative working plan during the strategic phase of air traffic control. The plan obtained via a new decision support tool presented in this article consists in a schedule for controllers, which specifies time of overflight on the different waypoints of the flight plans. In order to do it, we believe that the decision-support tool shall model directly the unce...
Paz, I. M.
The optimal routing problem is defined. Progress in solving the problem during the previous decade is reviewed, with special emphasis on technical developments made during the last few years. The relationships between the routing, the throughput, and the switching technology used are discussed and their future trends are reviewed. Economic aspects are also briefly considered. Modern technical approaches for handling the routing problems and, more generally, the flow control problems are reviewed.
Fielding, Randall Sidney [Idaho National Lab. (INL), Idaho Falls, ID (United States)
Casting optimization in the GACS included three broad areas; casting of U-10Zr pins, incorporation of an integral FCCI barrier, and development of a permanent crucible coating. U-10Zr casting was improved over last year’s results by modifying the crucible design to minimize contact with the colder mold. Through these modifications casting of a three pin batch was successful. Incorporation of an integral FCCI barrier also was optimized through furnace chamber pressure changes during the casting cycle to reduce gas pressures in the mold cavities which led to three full length pins being cast which incorporated FCCI barriers of three different thicknesses. Permanent crucible coatings were tested against a base case; 1500°C for 10 minutes in a U-20Pu-10Zr molten alloy. None of the candidate coating materials showed evidence of failure upon initial visual examination. In all areas of work a large amount of characterization will be needed to fully determine the effects of the optimization activities. The characterization activities and future work will occur next year.
Within the Community, protection against the dangers of ionizing radiation is regulated in conformity with the provisions of two Council Directives. One is of general application for all activities involving a hazard arising from ionizing radiation and lays down the basic safety standards for the health protection of the general public and workers against the dangers of ionizing radiation. The other is derived from the abovementioned one and lays down the basic measures for the radiation protection of persons undergoing medical examination or treatment. The Commission, in collaboration with the Spanish Ministerio de Sanidad y Consumo, the Consejo de Seguridad Nuclear and the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas, organized on 12, 13 and 14 September 1988 in Madrid, the third scientific seminar on the optimization principle (Alara) which is a key element of the two abovementioned Council Directives. The seminar allowed an analysis of the progress made since the previous seminars of 1979 and 1983, in the practical implementation of the optimization principle, in relation to the design and operation of nuclear and industrial installations, natural radioactivity, medical practices and countermeasures. The report contains the 20 original contributions presented and some general considerations on the results of the seminar
Zakrajsek, Robert J.
The goal of the Advanced Communications for Air Traffic Management (AC/ATM) Project at the NASA Glenn Research Center at Lewis Field is to enable a communications infrastructure that provides the capacity, efficiency, and flexibility necessary to realize a mature free-flight environment. The technical thrust of the AC/ATM Project is targeted at the design, development, integration, test, and demonstration of enabling technologies for global broadband aeronautical communications. Since Ku-band facilities and equipment are readily available, one of the near-term demonstrations involves a link through a Kuband communications satellite. Two conformally mounted antennas will support the initial AC/ATM communications links. Both of these are steered electronically through monolithic microwave integrated circuit (MMIC) amplifiers and phase shifters. This link will be asymmetrical with the downlink to the aircraft (mobile vehicle) at a throughput rate of greater than 1.5 megabits per second (Mbps), whereas the throughput rate of the uplink from the aircraft will be greater than 100 kilobits per second (kbps). The data on the downlink can be narrow-band, wide-band, or a combination of both, depending on the requirements of the experiment. The AC/ATM project is purchasing a phased-array Ku-band transmitting antenna for the uplink from the test vehicle. Many Ku-band receiving antennas have been built, and one will be borrowed for a short time to perform the initial experiments at the NASA Glenn Research Center at Lewis Field. The Ku-band transmitting antenna is a 254-element MMIC phased-array antenna being built by Boeing Phantom Works. Each element can radiate 100 mW. The antenna is approximately 43-cm high by 24-cm wide by 3.3-cm thick. It can be steered beyond 60 from broadside. The beamwidth varies from 6 at broadside to 12 degrees at 60 degrees, which is typical of phased-array antennas. When the antenna is steered to 60 degrees, the beamwidth will illuminate
Calderón Martínez, Ester
The aim of this thesis was the creation of a Search Engine Optimization Plan (SEO Plan) for the commissioner, St.Lapland, a tourist services provider located in Kuusamo Finland. The plan was hoping to improve the visibility of the website in search en-gines, focusing especially in Google.com as it is the major search engine in the Web and the preferred tool of the users for information gathering. By im-proving the visibility of the website it was expected an increase on traffic and theref...
Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a
BenDor, Todd K.; Guo, Tianshu; Yates, Andrew J.
Ecosystem service markets are popular policy tools for ecosystem protection. Advanced credit releases are an important factor affecting the supply side of ecosystem markets. Under an advanced credit release policy, regulators give ecosystem suppliers a fraction of the total ecosystem credits generated by a restoration project before it is verified that the project actually achieves the required ecological thresholds. In spite of their prominent role in ecosystem markets, there is virtually no regulatory or research literature on the proper design of advanced credit release policies. Using U.S. aquatic ecosystem markets as an example, we develop a principal-agent model of the behavior of regulators and wetland/stream mitigation bankers to determine and explore the optimal degree of advance credit release. The model highlights the tension between regulators' desire to induce market participation, while at the same time ensuring that bankers successfully complete ecological restoration. Our findings suggest several simple guidelines for strengthening advanced credit release policy.
Tuononen, Ari J; Sainio, Panu
Studded tyres can significantly wear the road surface and increase particle emissions from the road surface, which has a negative impact on air quality in urban areas. However, road wear might have a positive aspect by roughening the road surface and thus preventing polishing. As a consequence, other vehicles than the ones using studded tyres might also benefit from the usage of studded tyres. The impact of the proportion of studded tyres in the traffic flow on the tyre-ice friction coefficient was studied with a fleet of real cars in a closed environment under strict procedural control. The results show that a proportion of 25-50% studded tyres in the traffic flow is enough to prevent ice from developing in a manner that is critically slippery for non-studded winter tyres. It was also observed that the visual appearance of the ice surface does not indicate if the ice has become more slippery or not. PMID:24445137
This diploma thesis presents the behavior of program, which uses the traffic light enhanced transport network to simulate the traffic flow of vehicles that behave according to the IDM model. We upgraded the program to allow, for the given network, to optimize the traffic flow. Because of the overwhelming problem of road closures or their rearrangement, we added a graphical user interface with which a user can create or modify the road network to observe changes in traffic. The objective of...
Blond, N.; Ho, B. Q.; Clappier, A.
Road traffic emissions are one of the main sources of air pollution in the cities. They are also the main sources of uncertainties in the air quality numerical models used to forecast and define abatement strategies. Until now, the available models for generating road traffic emission always required a big effort, money and time. This inhibits decisions to preserve air quality, especially in developing countries where road traffic emissions are changing very fast. In this research, we developed a new model designed to fast produce road traffic emission inventories. This model, called EMISENS, combines the well-known top-down and bottom-up approaches to force them to be coherent. A Monte Carlo methodology is included for computing emission uncertainties and the uncertainty rate due to each input parameters. This paper presents the EMISENS model and a demonstration of its capabilities through an application over Strasbourg region (Alsace), France. Same input data as collected for Circul'air model (using bottom-up approach) which has been applied for many years to forecast and study air pollution by the Alsatian air quality agency, ASPA, are used to evaluate the impact of several simplifications that a user could operate . These experiments give the possibility to review older methodologies and evaluate EMISENS results when few input data are available to produce emission inventories, as in developing countries and assumptions need to be done. We show that same average fraction of mileage driven with a cold engine can be used for all the cells of the study domain and one emission factor could replace both cold and hot emission factors.
Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh
This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...
Hong Kong : Hong Kong Society for Transportation Studies, 2006 - (Wong, S.; Hau, T.; Wang, J.), s. 697-705 ISBN 978-988-98847-0-3; ISBN 988-98847-0-4. [International Conference of Hong Kong Society for Transportation Studies, Sustainable Transportation /11./. Hong Kong (HK), 09.12.2006-11.12.2006] R&D Projects: GA MDS 1F43A/003/120 Institutional research plan: CEZ:AV0Z10750506 Keywords : linear programming * traffic flow control * control on a horizon Subject RIV: BB - Applied Statistics, Operational Research
Lebouteiller, V; Bernard-Salas, J.; Sloan, G. C.; Barry, D. J.
We present new advances in the spectral extraction of point-like sources adapted to the Infrared Spectrograph onboard the Spitzer Space Telescope. For the first time, we created a super-sampled point spread function of the low-resolution modules. We describe how to use the point spread function to perform optimal extraction of a single source and of multiple sources within the slit. We also examine the case of the optimal extraction of one or several sources with a complex background. The new...
Joseph, Anito; Mehrotra, Anuj; Trick, Michael
Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high caliber of research being conducted by members of the INFORMS Computing Society. EXTENDING THE HORIZONS: Advances in Computing, Optimization, and Decision Technologies is a volume that presents the latest, leading research in the design and analysis of algorithms, computational optimization, heuristic search and learning, modeling languages, parallel and distributed computing, simulation, computational logic and visualization. This volume also emphasizes a variety of novel applications in the interface of CS, AI, and OR/MS.
In this report, the process to design an Advanced Liquid Metal Reactor (ALMR) for burning the transuranic part of nuclear waste is discussed. The influence of design parameters on ALMR burner performance is studied and the results are incorporated in a design schedule for optimizing ALMRs for burning transuranics. This schedule is used to design a metallic and an oxide fueled ALMR burner to burn as much as possible transurancis. The two designs burn equally well. (orig.)
Full Text Available This paper presents a solution to real-world delive ry problems for home delivery services where a large number of roads exist in cities and the tra ffic on the roads rapidly changes with time. The methodology for finding the shortest-travel-tim e tour includes a hybrid meta-heuristic that combines ant colony optimization with Dijkstra’s al gorithm, a search technique that uses both real-time traffic and predicted traffic, and a way to use a real-world road map and measured traffic in Japan. Experimental results using a map of central Tokyo and historical traffic data indicate that the proposed method can find a better solution than conventional methods.
Vikram Jeet Singh
Full Text Available The technological developments in the fields of multimedia clinical applications and communication networks require a specific analysis to increase the efficiency of network based healthcare services. In this work, we computed the optimum transmission parameter (data packet size for applications needed to guarantee the perceived quality of service in the proposed ubiquitous healthcare network. This has been carried out through NS2 based simulation of a state wide area network infrastructure implemented in Himachal Pradesh, a state with diverse geographical terrain situated in the Western Himalayan region of India. The various types of healthcare applications and services have been classified into different classes according to their perceived QOS requirements as per the guidelines in ITU report on network performance objectives. The infrastructure specific optimum values of data packet size for these QoS classes have been computed. Network based healthcare applications and services running on both TCP and UDP type of traffic have been presented in this paper.
Full Text Available Statistical models for estimating the safety status of transportation facilities have received great attention in the last two decades. These models also perform an important role in transportation safety planning as well as diagnoses of locations with high accident risks. However, the current methods largely rely on regression analyses and therefore they could ignore the multicollinearity characteristics of factors, which may provide additional information for enhancing the performance of forecasting models. This study seeks to develop more precise models for forecasting safety status as well as addressing the issue of multicollinearity of dataset. The proposed mathematical approach is indeed a discriminant analysis with respect to the goal of minimizing Bayes risks given multivariate distributions of factors. Based on this model, numerical analyses also perform with the application of a simulated dataset and an empirically observed dataset of traffic accidents in road segments. These examples essentially illustrate the process of Bayes risk minimization on predicating the safety status of road segments toward the objective of smallest misclassification rate. The paper finally concludes with a discussion of this methodology and several important avenues for future studies are also provided.
Obstructions caused by accidents can trigger or exacerbate traffic congestion. This paper derives the efficient traffic pattern for a rush hour with congestion and accidents and the corresponding road toll. Compared to the model without accidents, where the toll equals external costs imposed on drivers using the road at the same time, a new insight arises: An optimal toll also internalizes the expected increase in future congestion costs. Since accidents affect more drivers if traffic volumes...
Bhamber, R. S.; Fowler, Scott; Braimiotis, C.; Mellouk, A.
The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today’s data-heavy applications. However, these data-heavy applications require lots of battery power on the user equipment. To extend the user equipment battery lifetime, plus further support various services and large amount of data transmissions, the 3GPP standards for LTE/LTE-Advanced has adopted discontinuous reception (DRX). In this paper, we take an overview of various static/fixed DRX cyc...
Full Text Available This study aims to prove the effectiveness of traffic safety education program for traffic violators. Traffic violators who finished the traffic safety education programs were tracked down. In order to analyze the effectiveness of traffic safety education program, traffic violator’s data during ten-year period were used. This study analyzed how traffic violators changed their attitudes about traffic law abidance. Also predicted social benefits from traffic safety education program for traffic violators. Effectiveness of traffic accident prevention through traffic safety education program is approximately 93%. In terms of social benefits, it shows more than $12 billion Even though the effectiveness of traffic safety education program represents remarkable results, but this program is made for traffic violators who have already committed traffic offenses in the past. So in order to prevent traffic violations in advance, specific education program for potentially risky drivers is necessary.
Kanevski, Mikhail; Volpi, Michele; Copa, Loris
The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of
Carlsen, Robert W.
Many nuclear fuel cycle simulators have evolved over time to help understan the nuclear industry/ecosystem at a macroscopic level. Cyclus is one of th first fuel cycle simulators to accommodate larger-scale analysis with it liberal open-source licensing and first-class Linux support. Cyclus also ha features that uniquely enable investigating the effects of modeling choices o fuel cycle simulators and scenarios. This work is divided into thre experiments focusing on optimization, effects of modeling choices, and fue cycle uncertainty. Effective optimization techniques are developed for automatically determinin desirable facility deployment schedules with Cyclus. A novel method fo mapping optimization variables to deployment schedules is developed. Thi allows relationships between reactor types and scenario constraints to b represented implicitly in the variable definitions enabling the usage o optimizers lacking constraint support. It also prevents wasting computationa resources evaluating infeasible deployment schedules. Deployed power capacit over time and deployment of non-reactor facilities are also included a optimization variables There are many fuel cycle simulators built with different combinations o modeling choices. Comparing results between them is often difficult. Cyclus flexibility allows comparing effects of many such modeling choices. Reacto refueling cycle synchronization and inter-facility competition among othe effects are compared in four cases each using combinations of fleet of individually modeled reactors with 1-month or 3-month time steps. There are noticeable differences in results for the different cases. The larges differences occur during periods of constrained reactor fuel availability This and similar work can help improve the quality of fuel cycle analysi generally There is significant uncertainty associated deploying new nuclear technologie such as time-frames for technology availability and the cost of buildin advanced reactors
Felipe Jiménez; Wilmar Cabrera-Montiel
Nowadays, reducing the energy and fuel consumption of road vehicles is a key issue. Different strategies have been proposed. One of them is to promote Eco-driving behaviour among drivers. Most Eco-driving tips take into account only the road stretch where the vehicle is located. However, larger improvements could be achieved if information from subsequent stretches is used. The main objective of this work is to develop a system to warn the driver in real time of the optimal speed that should ...
Shikul’skaya Ol’ga Mikhaylovna
Full Text Available The choice and use of rational routes at strict observance of deliveries terms help to achieve not only minimization of operational expenses, but also to reduce commodity and production stocks in warehouses by 1,5...2 times. Therefore special relevance is gained by the works allowing precisely calculating the volumes of a cargo transportation, to count the quantity of transport units necessary for providing cargo flow, to define the rational routes of transportation, and also to reduce total costs of transportation. On the basis of the analysis of the known mathematical methods applied in transport logistics, the authors drew a conclusion that the route of freight delivery is estimated according to the distance passed by the vehicle. However the time of freight delivery depends not only on distance, but also on a set of other factors, such as vehicle type, road capacity, intensity of transport stream, weather conditions, season and others. For taking note of additional factors when optimizing a freight delivery route the method of analogy and similarity is used by the authors. The transportation parameters were estimated by analogy with an electric chain. For this purpose the authors entered the new concepts “fictitious distance” and “conductivity of the road”. The mathematical model allowing optimizing the organization of freight delivery taking into account not only distances, but also the probable speed of the vehicle movement depending on the road quality, intensity of transport stream and weather conditions is developed. Further development of the system of decision-making support while choosing the optimum route of cargo delivery is planned.
Dr. S. Meenakshi Sundaram
Full Text Available Mobile ad hoc network (MANET nodes include wireless transmitters and receivers. At a given point in time, depending on the positions of the nodes, their transmitter and receiver coverage patterns, communication power levels and co-channel interference levels, a wireless connectivity in the form of a random, multi hop graph or “ad hoc" network exists among the nodes. In this research, it is proposed to modify OLSR using swarm intelligence, Particle Swarm Optimization (PSO, to reduce end to end delay and improve throughput in the network by traffic shaping at the network layer. The PSO algorithm represents each solution as a ‘bird’ in the search space and is referred to as ‘particle’. It uses the objective function to evaluate its candidate solutions, and operates on the resultant fitness values. Candidate solution and its estimated fitness, and velocity give the position of the particle. It also remembers the best fitness value it achieved till then during the algorithm’s operation which is usually referred to as the individual best fitness, and the candidate solution that achieved this fitness, is the individual best position ‘pbest’. The best fitness value attained among all particles in the swarm which is called global best fitness, and the candidate solution that attained this fitness, which is called the global best position or global best candidate solution ‘gbest’. OLSR generates link state information through nodes elected as Multi Point Relays (MPRs. It is proposed to modify OLSR using particle swarm optimization to reduce end to end delay and improve network throughput.
This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials. Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.
Zhou, Chenn; Wang, Jichao; Tang, Guangwu; Moreland, John; Fu, Dong; Wu, Bin
The integration of simulation and visualization can provide a cost-effective tool for process optimization, design, scale-up and troubleshooting. The Center for Innovation through Visualization and Simulation (CIVS) at Purdue University Northwest has developed methodologies for such integration with applications in various manufacturing processes. The methodologies have proven to be useful for virtual design and virtual training to provide solutions addressing issues on energy, environment, productivity, safety, and quality in steel and other industries. In collaboration with its industrial partnerships, CIVS has provided solutions to companies, saving over US38 million. CIVS is currently working with the steel industry to establish an industry-led Steel Manufacturing Simulation and Visualization Consortium through the support of National Institute of Standards and Technology AMTech Planning Grant. The consortium focuses on supporting development and implementation of simulation and visualization technologies to advance steel manufacturing across the value chain.
Lu, Hua-pu; Sun, Zhi-yuan; Qu, Wen-cong; Wang, Ling
This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic ...
Full Text Available Traffic engineering is one of the major issues that has to be addressed in Metro Ethernet networks for quality of service and efficient resource utilization. This paper aims at understanding the relevant issues and outlines novel algorithms for multipoint traffic engineering in Metro Ethernet. We present an algorithmic solution for traffic engineering in Metro Ethernet using optimal multiple spanning trees. This iterative approach distributes traffic across the network uniformly without overloading network resources. We also introduce a new traffic specification model for Metro Ethernet, which is a hybrid of two widely used traffic specification models, the pipe and hose models.
Padmaraj Nair; Suku Nair; Girish Chiruvolu
Traffic engineering is one of the major issues that has to be addressed in Metro Ethernet networks for quality of service and efficient resource utilization. This paper aims at understanding the relevant issues and outlines novel algorithms for multipoint traffic engineering in Metro Ethernet. We present an algorithmic solution for traffic engineering in Metro Ethernet using optimal multiple spanning trees. This iterative approach distributes traffic across the network uniformly without overl...
Azarm, A.; Mughabghab, S.; Stock, D.
This report describes a computerized traffic forecasting model, developed by Brookhaven National Laboratory (BNL) for a portion of the Long Island INFORM Traffic Corridor. The model has gone through a testing phase, and currently is able to make accurate traffic predictions up to one hour forward in time. The model will eventually take on-line traffic data from the INFORM system roadway sensors and make projections as to future traffic patterns, thus allowing operators at the New York State Department of Transportation (D.O.T.) INFORM Traffic Management Center to more optimally manage traffic. It can also form the basis of a travel information system. The BNL computer model developed for this project is called ATOP for Advanced Traffic Occupancy Prediction. The various modules of the ATOP computer code are currently written in Fortran and run on PC computers (pentium machine) faster than real time for the section of the INFORM corridor under study. The following summarizes the various routines currently contained in the ATOP code: Statistical forecasting of traffic flow and occupancy using historical data for similar days and time (long term knowledge), and the recent information from the past hour (short term knowledge). Estimation of the empirical relationships between traffic flow and occupancy using long and short term information. Mechanistic interpolation using macroscopic traffic models and based on the traffic flow and occupancy forecasted (item-1), and the empirical relationships (item-2) for the specific highway configuration at the time of simulation (construction, lane closure, etc.). Statistical routine for detection and classification of anomalies and their impact on the highway capacity which are fed back to previous items.
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Casas Hernandez, Pedro; Fillatre, Lionel; Vaton, Sandrine
Traffic engineering (TE) has become a challenging mechanism for network management and resources optimization due to uncertain and difficult to predict traffic patterns. Recent works have proposed robust optimization techniques to cope with uncertain traffic, computing a stable routing configuration that is immune to demand variations within certain uncertainty set. However, using a single routing configuration for longtime periods can be highly inefficient. Even more, the presence of abnorma...
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
Tettamanti, Tamás; Varga, Istvan; Peni, Tamas
This chapter introduced the aspects of MPC applied in urban traffic management. As the urban traffic is a complex system having special attributes the appropriate traffic model had to be discussed in details as well. At the same time MPC technology is suitable to control such complex system optimally and real-time. The main control aim was the optimal and coordinated control which can be satisfied. The applicability was demonstrated by several simulations. Furthermore a distributed technology...
Traditional RBF neural network in the forecasting process of the network traffic convergence is slow, prone to local optima and other shortcomings, resulting in low prediction accuracy and difficult problems. In order to improve the prediction accuracy of network traffic, network traffic prediction method for an ant colony algorithm to optimize the parameters of RBF neural network. Ant colony algorithm for training RBF neural network center and the width of the basis functions to speed up the convergence, simplifying the network structure to improve the generalization capability of RBF neural networks, and optimized RBF neural network to predict the network traffic, to prevent local optimum to appear. The experimental results show that relative to the commonly used BP neural network traffic prediction model, model predictions more accurate, can be well described by the variation of the network flow. With good generalization ability, good stability and a certain practical value in the prediction of network traffic.%传统RBF神经网络在网络流量预测过程中存在收敛速度慢、极易出现局部最优等缺点,从而导致预测精度低.采用蚁群算法优化RBF神经网络参数来进行网络流量预测.利用蚁群优化算法来训练RBF神经网络的基函数宽度和中心,简化网络结构,加快收敛速度,防止局部最优的出现,改善RBF神经网络的泛化能力.实验结果表明,相对于GA-RBF以及PSO-RBF流量预测模型,模型预测准确度更高,能够很好地描述网络流的变化规律.具有泛化能力强、稳定性良好的特点,在网络流量预测中有一定的实用价值.
Han, Lee [University of Tennessee, Knoxville (UTK); Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL
Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because the degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.
陈丽佳; 邹峥嵘; 李光强
Public traffic transfer is an important problem to public traffic querying. The paper firstly describes the classical Dijkstra algorithm, and analyzes the reason that it is not fit to optimum route selection of public transportation network. Then the paper presents an advanced Dijkstra algorithm, this algorithm takes the stations which are the solution of the shortest path problem as the searched stations, and makes up of the transfer matrix with those stations and the traffic lines passing by, according to the request of the transfer time, the paper puts forward a transfer arithmetic based on Dijkstra algorithm. Finally, the paper proves the feasibility of the improved Dijkstra algorithm applying to Optimal Route Choice by an example.%公交换乘问题是公共交通信息查询的重要内容,本文首先叙述了经典Dijkstra算法,并分析了其不适合公交网络最优路径选择的原因.然后提出了一种改进的 Dijkstra 算法,该算法将求解最短路径获得的站点作为搜索站点,并将这些站点及经过这些站点的线路构成换乘矩阵,结合换乘次数的要求,给出了基于Dijkstra的智能选择换乘线路的实现算法.最后通过一个实际算例说明改进的Dijkstra算法在公交换乘路线选择中应用的可行性.
Corker, Kevin M.; Condon, Gregory W. (Technical Monitor)
NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. The core processes of control and the distribution of decision making in that control are undergoing extensive analysis. From our perspective, the human operators and the procedures by which they interact are the fundamental determinants of the safe, efficient, and flexible operation of the system. In that perspective, we have begun to explore what our experience has taught will be the most challenging aspects of designing and integrating human-centered automation in the advanced system. We have performed a full mission simulation looking at the role shift to self-separation on board the aircraft with the rules of the air guiding behavior and the provision of a cockpit display of traffic information and an on-board traffic alert system that seamlessly integrates into the TCAS operations. We have performed and initial investigation of the operational impact of "Dynamic Density" metrics on controller relinquishing and reestablishing full separation authority. (We follow the assumption that responsibility at all times resides with the controller.) This presentation will describe those efforts as well as describe the process by which we will guide the development of error tolerant systems that are sensitive to shifts in operator work load levels and dynamic shifts in the operating point of air traffic management.
As the the rapid growth of city economy, a traffic congestion has become a common sight in almost every big city. On the surface, the infrastructure construction is incompatible with the rapid expansion of the city cars. In fact,the root cause lies in the careless and easy style of management of traffic which leads to the low traffic efficiency. This study mainly describes the traffic system, the causes of traffic congestion, discussing on the optimization to ...
Within Ericsson there is a continuous activity of traffic modeling. Traffic modeling is a practice to analyze traffic patterns and determine necessary resources to handle it optimally. This activity focuses on gathering and analyzing live network measurements, implementing and presenting traffic models. One example of concept in packet traffic modeling is transmission object log which is an aggregation of packet data traces from a measured network over a transmission period. These trace l...
Ata, Baris; Sunil KUMAR
We consider a class of open stochastic processing networks, with feedback routing and overlapping server capabilities, in heavy traffic. The networks we consider satisfy the so-called complete resource pooling condition and therefore have one-dimensional approximating Brownian control problems. We propose a simple discrete review policy for controlling such networks. Assuming 2+\\epsilon moments on the interarrival times and processing times, we provide a conceptually simple proof of asymptoti...
Bakker, B.; Whiteson, S.; Kester, L.J.H.M.; Groen, F.C.A.
Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of traffi
B. Bakker; S. Whiteson; L. Kester; F.C.A. Groen
Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of traffi
Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal
The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. PMID:22561008
Delahaye, Daniel; Puechmorel, Stéphane; Dougui, Nour Elhouda
Air traffic Management Requirements : -Insure separation between aircraft. -Avoid costly manoeuvres and optionally optimize trajectories. -Insure trafic organization. Trends : -Separation delegated to aircraft. -Trajectory based air traffic management. -Introduction of decision support tools / automated conflict solvers. Workload : -Related to cognitive processes of human controllers. -Easy/Hard forecasting of conflict occurrence. -Monitoring is a non negligible part of the workload. -Relevan...
Ganguli, Ranjan; Chopra, Inderjit
Sensitivity derivatives of blade loads and aeroelastic stability of a helicopter rotor in forward flight are calculated as an integral part of a basic aeroelastic analysis using a direct analytical approach. Design variables include nonstructural mass and its placement, chordwise offset of blade center of gravity and aerodynamic center from the elastic axis, blade bending stiffnesses (flap, lag, torsion), and tip geometry (sweep, anhedral, pretwist and planform taper). By means of a sensitivity study, the importance of different design variables on oscillatory hub loads and damping of blade modes is examined. Aeroelastic and sensitivity analyses of the rotor based on a finite element method in space and time are linked with automated optimization algorithms to perform optimization studies of rotor blades. Optimum design solutions, calculated for a four-bladed, soft-inplane hingeless rotor achieved a reduction of 25-60 percent of all 4/rev loads.
Prunescu, Remus Mihail
balances with a complex conversion route. Computational fluid dynamics is used to model transport phenomena in large reactors capturing tank profiles, and delays due to plug flows. This work publishes for the first time demonstration scale real data for validation showing that the model library is suitable...... study deals with building a plantwide model-based optimization layer, which searches for optimal values regarding the pretreatment temperature, enzyme dosage in liquefaction, and yeast seed in fermentation such that profit is maximized . When biomass is pretreated, by-products are also created that...... bottlenecks and which feedstock components need to be determined for an accurate prediction. This analysis is achieved with Monte Carlo simulations and Latin Hypercube Sampling (LHS) on feedstock composition and kinetic parameters following the methodology from [5, 6, 8, 9]. In the last part of this work, two...
Hajima, Ryoichi [Univ. of Tokyo (Japan)
In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms.
Húsek, Dušan; Keyhanipour, A.; Krömer, P.; Moshiri, B.; Owais, S.; Snášel, V.
Ostrava : VŠB Technická univerzita, 2007 - (Snášel, V.; Platoš, J.), s. 82-92 ISBN 978-80-248-1332-5. [WETDAP 2007. Workshop in Conjunction with Znalosti 2007 /1./. Ostrava (CZ), 22.02.2007-22.02.2007] Institutional research plan: CEZ:AV0Z10300504 Keywords : Web search * meta-search * user modeling * evolutionary algorithms * query optimization Subject RIV: BB - Applied Statistics, Operational Research
倪仁兴; 沈婷; 胡静雅; 陈靖倩
利用交通流理论等知识,借助于SPSS和MATLAB软件,考察实际交通堵塞道路的通行能力,通过对真实事故现场数据的采集分析,受经典的logistic人口模型启发,提出并建立了阻滞增长模型,得到了拥堵时车辆排队长度与持续时间、通行能力、车流量之间的关系.建立了城市道路被占时的车辆排队长度和其影响因子探究的数学模型,给出了上游路口信号灯配时方案和交通组织方案.运用阻滞增长模型可有效优化城市道路通行能力,缓解城市交通压力,改善交通环境.%In china, traffic congestion has become a serious problem in today's increasingly prominent on growing probloms of urban traffic. But, many older urban road planning form earlier, the existing urban road construction is so far as behind the economic development at present,. Among them, the lane occupied has become the big-gest problem of the traffic congestion, including traffic problem, street parking, lane construction and so on. This paper aims to take advantage of the knowledge of traffic flow theory, by SPSS and MATLAB software, the actual traffic jam road traffic capacity is examined, using the real scene of the accident, as reflected in the video data acquisition and analysis, inspired by the classic logistic population model, a block growth model is proposed and established. The relationship about vehicle queue length, time duration, traffic capacity and traffic flow is obtained. Meanwhile, according to the people's traffic expectations, we established model about vehicle queue length and its influencing factors in response to urban road occupied, and given timing program and traffic organ-ization scheme of upstream crossing signal lights. The use of block growth model can effectively optimize urban road capacity, ease urban traffic pressure and improve the traffic environment.
of very large machines introduces new problems in the practical design, and optimization tools are necessary. These must combine the dynamic eects of both aerodynamics and structure in an integrated optimization environment. This is referred to as aeroelastic optimization. The Ris DTU optimization......During the last decades the annual energy produced by wind turbines has increased dramatically and wind turbines are now available in the 5MW range. Turbines in this range are constantly being developed and it is also being investigated whether turbines as large as 10-20MW are feasible. The design...
田中大; 李树江; 王艳红; 高宪文
为了提高网络流量的预测精确度,提出一种核主成分分析( KPCA )优化回声状态网络( ESN)的网络流量预测方法. 首先利用相空间重构对网络流量序列进行处理,提高序列的可预测性,然后对网络流量序列进行核主成分分析,提取序列中的有效信息,通过实验方法确定回声状态网络的储备池参数,最后利用回声状态网络对网络流量进行预测. 与标准回声状态网络、差分自回归滑动平均模型( ARIMA)、以及最小二乘支持向量机( LSSVM)预测模型进行了仿真对比,结果表明提出的方法具有更高的预测精确度以及更小的预测误差,同时一定程度上减少了预测时间.%In order to improve the prediction accuracy of network traffic, a network traffic prediction method based on kernel principal component analysis ( KPCA) optimized echo state network ( ESN) was proposed. Firstly, network traffic series was processed to improve the predictability by phase space recon-struction, then the effective information was extracted through kernel principal component analysis. The reservoir parameters of echo state network were determined through the experiment method. Finally, net-work traffic was predicted through the echo state network. The proposed method is compared with stand-ard echo state netowrk, auto regressive integrated moving average ( ARIMA) , and least squares support vector machine ( LSSVM) predictive model. The simulation results show that the proposed method has higher prediction accuracy with smaller predictive error, at the same time the prediction time is reduced.
Clack, C.; MacDonald, A. E.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Wilczak, J. M.
The importance of weather-driven renewable energies for the United States (and global) energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The National Energy with Weather System Simulator (NEWS) is a mathematical optimization tool that allows the construction of weather-driven energy sources that will work in harmony with the needs of the system. For example, it will match the electric load, reduce variability, decrease costs, and abate carbon emissions. One important test run included existing US carbon-free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. These results were found without the need for storage. Further, we tested the effect of changing natural gas fuel prices on the optimal configuration of the national electric power system. Another test that was carried out was an extension to global regions. The extension study shows that the same properties found in the US study extend to the most populous regions of the planet. The extra test is a simplified version of the US study, and is where much more research can be carried out. We compare our results to other model results.
This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, funded by the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.
Catalão, João P S
Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie
Venkata Rao, R.; Patel, Vivek
This study explores the use of teaching-learning-based optimization (TLBO) and artificial bee colony (ABC) algorithms for determining the optimum operating conditions of combined Brayton and inverse Brayton cycles. Maximization of thermal efficiency and specific work of the system are considered as the objective functions and are treated simultaneously for multi-objective optimization. Upper cycle pressure ratio and bottom cycle expansion pressure of the system are considered as design variables for the multi-objective optimization. An application example is presented to demonstrate the effectiveness and accuracy of the proposed algorithms. The results of optimization using the proposed algorithms are validated by comparing with those obtained by using the genetic algorithm (GA) and particle swarm optimization (PSO) on the same example. Improvement in the results is obtained by the proposed algorithms. The results of effect of variation of the algorithm parameters on the convergence and fitness values of the objective functions are reported.
Spallicci, A D; De Pacheco, J F; Frossati, G; Regimbau, T; Spallicci, Alessandro D.A.M.; Aoudia, Sofiane; Pacheco, Jose De Freitas; Frossati, Giorgio; Regimbau, Tania
Among sources, coalescing binaries appear among the most interesting and known. Thus, improvements in signal to noise ratio (S/N) by noise abatement in VIRGO, for inspiralling binaries of small chirp mass, are discussed. VIRGO detection bandwidth is divided into four sub-bands according to the dominant noise (whether seismic, thermal from pendula and mirrors, shot). Firstly, it is identified that mirror thermal noise reduction provides the highest gain increment in S/N. On the assumption that the technological challenges lying ahead, and the relative necessary budgets, are equally relevant in all sub-bands, it is recommended to gear R&D strategies to a future EURO detector operating at cryogenic temperatures. Secondly, the frequency of 50 Hz is identified as the single optimal frequency at which lies the potential largest increment in S/N for VIRGO. Thirdly, enlargement of the bandwidth, where noise is reduced, produces a shift to higher frequency of the optimal frequency (e.g. for 100 Hz band, the optima...
Lasers are among the most important experimental tools for user facilities, including synchrotron radiation and free electron lasers (FEL). In the synchrotron radiation field, lasers are widely used for experiments with Pump-Probe techniques. Especially for X-ray-FELs, lasers play important roles as seed light sources or photocathode-illuminating light sources to generate a high-brightness electron bunch. For future accelerators, laser-based techonologies such as electro-optic (EO) sampling to measure ultra-short electron bunches and optical-fiber-based femtosecond timing systems have been intensively developed in the last decade. Therefore, controls and optimizations of laser pulse characteristics are strongly required for many kinds of experiments and improvement of accelerator systems. However, people believe that lasers should be tuned and customized for each requirement manually by experts. This makes it difficult for laser systems to be part of the common accelerator infrastructure. Automatic laser tuning requires sophisticated algorithms, and the metaheuristic algorithm is one of the best solutions. The metaheuristic laser tuning system is expected to reduce the human effort and time required for laser preparations. I have shown some successful results on a metaheuristic algorithm based on a genetic algorithm to optimize spatial (transverse) laser profiles, and a hill-climbing method extended with a fuzzy set theory to choose one of the best laser alignments automatically for each machine requirement.
刘东泽; 韩丁; 朱俊骅; 肖益民
To prevent secondary damage of widening road structure in construction process ,the traffic organiza-tion optimization was implemented .The original road surface cracking and subgrade plastic deformation were simulated on the position of construction joint .The conditions and diseases in road widening of Hefei-Nanjing Expressway were analyzed .According to the values of tensile stress and plastic strain ,optimal traffic organi-zation was achieved by adjusting the values of vehicle loads ,tire edge distance away from road excavation sec-tion and the height between original pavement surface and subgrade widening excavation .The vehicle load and the distance between vehicle load position and excavation section are two important factors which determine whether the surface cracking and subgrade collapse will occur .The original subgrade excavation depth can be flexibly controlled .A reasonable traffic organization mode on widening road can be quickly determined by the comprehensive critical condition graph of two kinds of diseases .%为防止路面拼接结构在施工过程中的二次破坏，文章基于接缝位置原路表面拉裂和路基塑性变形的数值仿真进行交通组织优化；分析了合宁高速公路路面拼接中的工况和病害，通过分别调整车辆荷载的大小、轮胎边缘距开挖断面距离和原有路面结构开挖时距拼接路基高差，依据拉应力和塑性应变指标确定合理的交通组织方式。车辆轴载和荷载距开挖断面距离是确定原有沥青面层表面是否会出现拉裂及道路路基开挖后是否会出现崩塌的重要条件，原有路基的开挖深度可以机动控制。根据2种病害综合临界条件曲线图能够快速确定合理的拼接路面交通组织方式。
Sarika Baburao Kale; Gajanan P. Dhok
The use of Embedded technology has proved to be very beneficial in present Traffic Light Controller (TLC) and that will minimize waiting time of vehicle and also manage traffic load. In this paper we exploit the emergence of new technology called as Intelligent traffic light controller, This makes the use of sensor n/w along with embedded technology. Where traffic light will be intelligently decided based on the total traffic on all adjacent roads. Thus optimization of traffic light switchin...
During the last decades the annual energy produced by wind turbines has increased dramatically and wind turbines are now available in the 5MW range. Turbines in this range are constantly being developed and it is also being investigated whether turbines as large as 10-20MW are feasible. The design of very large machines introduces new problems in the practical design, and optimization tools are necessary. These must combine the dynamic effects of both aerodynamics and structure in an integrated optimization environment. This is referred to as aeroelastic optimization. The Risoe DTU optimization software HAWTOPT has been used in this project. The quasi-steady aerodynamic module have been improved with a corrected blade element momentum method. A structure module has also been developed which lays out the blade structural properties. This is done in a simplified way allowing fast conceptual design studies and with focus on the overall properties relevant for the aeroelastic properties. Aeroelastic simulations in the time domain were carried out using the aeroelastic code HAWC2. With these modules coupled to HAWTOPT, optimizations have been made. In parallel with the developments of the mentioned numerical modules, focus has been on analysis and a fundamental understanding of the key parameters in wind turbine design. This has resulted in insight and an effective design methodology is presented. Using the optimization environment a 5MW wind turbine rotor has been optimized for reduced fatigue loads due to apwise bending moments. Among other things this has indicated that airfoils for wind turbine blades should have a high lift coefficient. The design methodology proved to be stable and a help in the otherwise challenging task of numerical aeroelastic optimization. (Author)
Kuyer, Lior; Whiteson, Shimon; Bakker, Bram; Vlassis, Nikos
Since traffic jams are ubiquitous in the modern world, optimizing, the behavior of traffic lights for efficient traffic flow is a critically important goal. Though most current traffic lights use simple heuristic protocols, more efficient controllers can be discovered automatically via multiagent reinforcement learning where each agent controls a single traffic light. However, in previous work on this approach, agents select only locally optimal actions without coordinating their behavior. Th...
In the design of major nuclear facilities, it is important to protect both humans and equipment excessive radiation dose. Past experience has shown that it is very effective to apply dose reduction principles early in the design of a nuclear facility both to specific design features and to the manner of operation of the facility, where they can aid in making the facility more efficient and cost-effective. Since the appropriate choice of radiological controls and practices varies according to the case, each area of the facility must be analyzed for its radiological impact, both by itself and in interactions with other areas. For the Advanced Neutron Source (ANS) project, a large relational database will be used to collect facility information by system and relate it to areas. The database will also hold the facility dose and shielding information as it is produced during the design process. This report details how the ANS zoning scheme was established and how the calculation of doses and shielding are to be done
The Escrime program aims at defining the optimal share of tasks between humans and computers under normal or accidental plant operation. Basic principles we keep in mind are the following: human operators are likely to be necessary in the operation of future plants because we cannot demonstrate that plant design is error free, so unexpected situation can still happen; automation must not release the operators from their decisional role but only help them avoiding situations of cognitive overload which can lead to increase the risk of errors; the optimum share of tasks between human and automatic systems must be based on a critical analysis of the tasks and of the way they are handled. The last point appeared to be of major importance. The corresponding analysis of the French PWR's operating procedures enabled us to define a unified scheme for plant operation under the form of a hierarchy of goals and means. Beyond this analysis, development of a specific testing facility is under way to check the relevance of the proposed plant operation organization and to test the human-machine cooperation in different situations for various levels of automation. 7 refs, 4 figs
Pollmann, Olaf Axel.
Sustainable development and resource efficiency are the common global strategies of the 21st century. The actual global natural resource consumption of humankind went far over the limit and to cover this worldwide resource consumption the productivity of 1.5 earths is now necessary. The work “Reduction of anthropogenic environmental influences by advanced and optimized technologies” discussed the problem of advanced resource efficiencies with mining activities in South Afric...
Vishal Arora; Vadlamani Ravi
Ant Colony Optimization (ACO) is gaining popularity as data mining technique in the domain of Swarm Intelligence for its simple, accurate and comprehensive nature of classification. In this paper the authors propose a novel advanced version of the original ant colony based miner (Ant-Miner) in order to extract classification rules from data. They call this Advanced ACO-Miner (ADACOM). The main goal of ADACOM is to explore the flexibility of using a different knowledge extraction heuristic app...
Highlights: ► Definition of an optimization model for a home energy supply system. ► Optimization of the energy supply system for standard and domotic home. ► Strong improvement can be achieved adopting the optimal system in standard and domotic home. ► The improvements are consistent if supply side and demand side strategies are applied together. ► Solutions with internal combustion engines are less sensible to market price of electricity and gas. - Abstract: The paper deals with the optimization of an advanced energy supply systems for two dwellings: a standard home and an advanced domotic home, where some demand side energy saving strategies have been implemented. In both cases the optimal synthesis, design and operation of the whole energy supply system have been obtained and a sensitivity analysis has been performed, by introducing different economic constraints. The optimization model is based on a Mixed Integer Linear Program (MILP) and includes different kinds of small-scale cogenerators, geothermal heat pumps, boilers, heat storages, solar thermal and photovoltaic panels. In addition, absorption machines, supplied with cogenerated heat, can be used instead of conventional electrical chiller to face the cooling demand. The aim of the analysis is to address the question if advanced demand strategies and supply strategies have to be regarded as alternatives, or if they have to be simultaneously applied, in order to obtain the maximum energy and economic benefit.
Sean Cai; Li Mo
This special issue of ZTE Communications focuses on recent advances in mobile data communications for the ICT and telecommunications industries. The ever-increasing amount of mobile data traffic has beenthe subject of many studies. This research area is widely applicable to contemporary technology and network optimization techniques.
L. Kuyer; S. Whiteson; B. Bakker; N. Vlassis
Since traffic jams are ubiquitous in the modern world, optimizing the behavior of traffic lights for efficient traffic flow is a critically important goal. Though most current traffic lights use simple heuristic protocols, more efficient controllers can be discovered automatically via multiagent rei
Serpemen, Y.; Baumeister, K.H.; Hubel, A.; Raichel, P. (Veba Oel Entwicklungs-Gessellschaft mbH, Gelsenkirchen (DE))
Refinery profit margins increased significantly by using the on-line gasoline blend optimization system which allows considerable savings resulting from octane give-away reduction, appreciably enhanced butane utilization, optimum use of the available blend components, and increased operating flexibility by elimination of reblends. The experience with this advanced on-line blending system is described in this paper.
Casas Hernandez, Pedro; Larroca, Federico; Vaton, Sandrine
Internet traffic is highly dynamic and difficult to predict in current network scenarios. This makes of traffic engineering (TE) a very challenging task for network management and resources optimization. We study the problem of intradomain routing optimization under this traffic uncertainty. Recent works have proposed robust optimization techniques to tackle the problem, conceiving the robust routing (RR) approach. RR copes with traffic uncertainty in an off-line preemptive fashion, computing...
Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)
This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...
Full Text Available The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overcoming the premature convergence & stagnation problems as in basic PSO algorithm & Particle swarm optimization with shrinkage factor & inertia weight approach (PSO-SFIWA. In this paper SMIB system along with PID damped SVC controller is considered for study. The generator speed deviation is used as an auxiliary signal to SVC, to generate the desired damping. This controller improves the dynamic performance of power system by reducing the steady-state error. The controller parameters are optimized using basic PSO, PSO-SFIWA & Advanced Adaptive PSO. Computational results show that Advanced Adaptive based SVC controller is able to find better quality solution as compare to conventional PSO & PSO-SFIWA Techniques.
The main aim of Dynamic Traffic Management is efficient and effective use of the existing traffic infrastructure network. To reach this goal, traffic operators take measures, based on the current traffic situation, control schemes and information services at hand, that (try to) influence and distribute traffic in such a manner that it makes optimal use of the present road infrastructure. In this dissertation, the performances of models that were developed to produce accurate congestion predic...
To save traffic congestion, this report aims at the area traffic control which increasesarea. traffic capacity without expansion of traffic facilities. This method is called AREATRAFFIC CONTROL SYSTEM.Optimum solutions for the area control system are obtained by the use of operationsresearch method. But above calculation time takes too long to fit this optimumregulation to present traffic pattern.In this report, optimization is made by the approximate solution which is composedof the first op...
Based on the random distribution characteristic of link travel speed,the limitations of phase difference optimization methods for the existed arterial control systems were analyzed.Link travel time,vehicle delay and queue length were taken as evaluation indexes,the phase difference optimization algorithm of arterial control system was designed by using information entropy theory and multi-attribute synthetic decision method,and a simulation calculation was carried out.Calculation result indicates that when the variance of link travel speed increases from 5 km·h-1 to 10 km·h-1,link travel speed,vehicle delay and queue length of west-to-east traffic flow increase from 98.4 s,13.5 s·pcu-1 and 9.1 pcu to 115.5 s,15.9 s·pcu-1 and 12.3 pcu respectively.Link travel speed,vehicle delay and queue length of east-to-west traffic flow increase from 99.4 s,13.5 s·pcu-1 and 9.2 pcu to 108.7 s,14.3 s·pcu-1 and 10.8 pcu respectively.So,the random distribution characteristic of link travel speed has an obvious effect on settings of phase difference,and the optimal phase difference can be obtained by using the proposed model.2 tabs,1 fig,13 refs.%根据路段行程车速的随机分布特征,分析了已有线控系统相位差优化方法的局限性。以路段行程时间、车辆延误和排队长度为评价指标,利用信息熵理论和多属性综合决策方法设计了线控系统相位差优化算法,并进行了仿真计算。仿真结果表明：当路段行程车速的方差从5 km.h-1增大到10 km.h-1后,由西向东车流的行程时间、车辆延误和排队长度分别从98.4 s、13.5 s.pcu-1和9.1 pcu增大到115.5 s、15.9 s.pcu-1和12.3 pcu,由东向西车流的行程时间、车辆延误和排队长度分别从99.4 s
Rizk, Magdi H.
A scheme is developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The scheme updates the design parameter iterative solutions and the flow variable iterative solutions simultaneously. It is applied to an advanced propeller design problem with the Euler equations used as the flow governing equations. The scheme's accuracy, efficiency and sensitivity to the computational parameters are tested.
Rizk, Magdi H.
A scheme is developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The scheme updates the design parameter iterative solutions and the flow variable iterative solutions simultaneously. It is applied to an advanced propeller design problem with the Euler equations used as the flow governing equations. The scheme's accuracy, efficiency and sensitivity to the computational parameters are tested.
Ruimin Li; Hongliang Ma; Huapu Lu; Min Guo
As an important part of the urban Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS), short-term road traffic prediction system has received special attention in recent decades. The success of ATMS and ATIS technology deployment is heavily dependent on the availability of timely and accurate estimation or prediction of prevailing and emerging traffic conditions. We studied a real-time road traffic prediction system developed for Beijing based on variou...
Ge, Hong-Xia; Zheng, Peng-jun; Wang, Wei; Cheng, Rong-Jun
Based on optimal velocity car following model, a new model considering traffic jerk is proposed to describe the jamming transition in traffic flow on a highway. Traffic jerk means the sudden braking and acceleration of vehicles, which has a significant impact on traffic movement. The nature of the model is researched by using linear and nonlinear analysis method. A thermodynamic theory is formulated to describe the phase transition and critical phenomenon in traffic flow. The time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are derived to describe the traffic flow near the critical point and the traffic jam. In addition, the connection between the TDGL and the mKdV equations are also given.
Leifsson, Leifur; Yang, Xin-She
This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the...
Dr.V. Palanisamy#1 , K. Gowri
Traffic engineering is an important mechanism for Internet network providers seeking to optimize network performance and traffic delivery. Routing optimization plays a key role in traffic engineering, finding efficient routes so as to achieve the desired network performance. BGP is the de facto protocol used for inter-autonomous system routing in the Internet. BGP has been proven to be secure, efficient, scalable, and robust. In proposed introduced AMPLE – an efficient traffic engineering and...
K, Nagel; S, Rasmussen
We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows near-critical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making prediction...
Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.
The author advances some basic problems of planning ＆ evaluating for track traffic in the proeess of putting sustainable develop-ment strategy in practice and stresses the study of planning and evaluating methiod system for track traffic and environment strategy.sum-maries and main creative points presented in the thesis are as follows:①The changes of track traffic planning obiects cause by the concept of sustainable development are analyzed;②The theory ＆?A method of tracd planning optimal decision isset up ;③Environment im-pact assessment for track traffic planning is advanced;⑤Urbun mass transit network plannin is studied;④Planning of intrcity rail sys-tem——the alignment ofptimizattion of deicated passenger line and high speed railway line is studied;⑥An overall evaluation index sys-tem for sustainable development of track traffic planning is estahlished;⑦The track traffie building capacity for sustainable development is studied.Further more,the effect of the mehod and models with empirical studies is verified.The corresponding pplication software is re-alized to provide information service and decision-making support to traffic planning for putting theory into practice.
In order to improve the prediction accuracy of network traffic , a network traffic prediction model is proposed based on cuckoo searching algorithm optimizing the parameters of mixed kernel relevance vector machine ( CS-RVM) to solve limitations of single kernel function for relevance vector machine .Firstly, the polynomial and Gaussian kernel functions are produced to mixed kernel function for the relevance vector machine , and then the cuckoo searching algorithm is introduced to optimize the parameters of hybrid kernel function , finally network traffic prediction model is established based on the relevance vector machine using the optimal parameters .The simulation results show that , CS-RVM model is of good effect and could improve the prediction accuracy of network traffic .%为了提高网络流量的预测精度，提出一种布谷鸟算法优化混合核相关向量机的网络流量预测模型（ CS-RVM ）。首先采用多项式和高斯核函数构成混合核函数代替相关向量机的单一核函数，然后引入布谷鸟算法对混合核参数进行寻优，最后建立网络流量预测模型。仿真结果表明，CS-RVM具有良好的建模效果，可提高网络流量的预测精度。
Dimitrios V. ROVAS
Full Text Available The solution of repeated fixed-horizon trajectory optimization problems of processes that are either too difficult or too complex to be described by physics-based models can pose formidable challenges. Very often, soft-computing methods e.g. black-box modeling and evolutionary optimization are used. These approaches are ineffective or even computationally intractable for searching high-dimensional parameter spaces. In this paper, a structured iterative process is described for addressing such problems: the starting point is a simple parameterization of the trajectory starting with a reduced number of parameters; after selection of values for these parameters so that this simpler problem is covered satisfactorily, a refinement procedure increases the number of parameters and the optimization is repeated. This continuous parameter refinement and optimization process can yield effective solutions after only a few iterations. To illustrate the applicability of the proposed approach we investigate the problem of dynamic optimization of the operation of HVAC (heating, ventilation, and air conditioning systems, and illustrative simulation results are presented. Finally, the development of advanced communication and interoperability components is described, addressing the problem of how the proposed algorithm could be deployed in realistic contexts.
Vicente, Tiago; Mota, José P B; Peixoto, Cristina; Alves, Paula M; Carrondo, Manuel J T
The advent of advanced therapies in the pharmaceutical industry has moved the spotlight into virus-like particles and viral vectors produced in cell culture holding great promise in a myriad of clinical targets, including cancer prophylaxis and treatment. Even though a couple of cases have reached the clinic, these products have yet to overcome a number of biological and technological challenges before broad utilization. Concerning the manufacturing processes, there is significant research focusing on the optimization of current cell culture systems and, more recently, on developing scalable downstream processes to generate material for pre-clinical and clinical trials. We review the current options for downstream processing of these complex biopharmaceuticals and underline current advances on knowledge-based toolboxes proposed for rational optimization of their processing. Rational tools developed to increase the yet scarce knowledge on the purification processes of complex biologicals are discussed as alternative to empirical, "black-boxed" based strategies classically used for process development. Innovative methodologies based on surface plasmon resonance, dynamic light scattering, scale-down high-throughput screening and mathematical modeling for supporting ion-exchange chromatography show great potential for a more efficient and cost-effective process design, optimization and equipment prototyping. PMID:21784144
Highlights: • Propose an optimize 2-D model for CANDU lattice cell. • Propose a new 3-D simulation model for CANDU reactivity devices. • Implement other acceleration techniques for reactivity device simulations. • Reactivity device incremental cross sections for advanced CANDU fuels with thorium. - Abstract: Several 2D cell and 3D supercell models for reactivity device simulation have been proposed along the years for CANDU-6 reactors to generate 2-group cross section databases for finite core calculations in diffusion. Although these models are appropriate for natural uranium fuel, they are either too approximate or too expensive in terms of computer time to be used for optimization studies of advanced fuel cycles. Here we present a method to optimize the 2D spatial mesh to be used for a collision probability solution of the transport equation for CANDU cells. We also propose a technique to improve the modeling and accelerate the evaluation, in deterministic transport theory, of the incremental cross sections and diffusion coefficients associated with reactivity devices required for reactor calculations
Ryu, B. Y.; Jung, H. J.; Bae, S. H.; Choi, C. U.
CO2 emissions on roads in urban centers substantially affect global warming. It is important to quantify CO2 emissions in terms of the link unit in order to reduce these emissions on the roads. Therefore, in this study, we utilized real-time traffic data and attempted to develop a methodology for estimating CO2 emissions per link unit. Because of the recent development of the vehicle-to-infrastructure (V2I) communication technology, data from probe vehicles (PVs) can be collected and speed per link unit can be calculated. Among the existing emission calculation methodologies, mesoscale modeling, which is a representative modeling measurement technique, requires speed and traffic data per link unit. As it is not feasible to install fixed detectors at every link for traffic data collection, in this study, we developed a model for traffic volume estimation by utilizing the number of PVs that can be additionally collected when the PV data are collected. Multiple linear regression and an artificial neural network (ANN) were used for estimating the traffic volume. The independent variables and input data for each model are the number of PVs, travel time index (TTI), the number of lanes, and time slots. The result from the traffic volume estimate model shows that the mean absolute percentage error (MAPE) of the ANN is 18.67%, thus proving that it is more effective. The ANN-based traffic volume estimation served as the basis for the calculation of emissions per link unit. The daily average emissions for Daejeon, where this study was based, were 2210.19 ton/day. By vehicle type, passenger cars accounted for 71.28% of the total emissions. By road, Gyeryongro emitted 125.48 ton/day, accounting for 5.68% of the total emission, the highest percentage of all roads. In terms of emissions per kilometer, Hanbatdaero had the highest emission volume, with 7.26 ton/day/km on average. This study proves that real-time traffic data allow an emissions estimate in terms of the link unit
Full Text Available The research objective is rational (optimal time management in studying the course modules on Advanced Training of Health Care Administrators. Materials and methods. We conducted expert survey of 73 healthcare administrators from medical organizations of Saratov region. Branch-and-bound method was used for rescheduling the educational program. Results. Both direct and inverse problems have been solved. The direct one refers to time distribution for each module of the advanced Training of Healthcare Administrators course so that the total score is maximum and each module is marked not lower than "satisfactory". The inverse one resulted in achieving minimal time characteristics for varieties of average score. Conclusion. The offered approach allows to solve problems of managing time given for education.
Khor, E F; Sathikannan, R; Tan, K C; 10.1613/jair.842
This paper presents an evolutionary algorithm with a new goal-sequence domination scheme for better decision support in multi-objective optimization. The approach allows the inclusion of advanced hard/soft priority and constraint information on each objective component, and is capable of incorporating multiple specifications with overlapping or non-overlapping objective functions via logical 'OR' and 'AND' connectives to drive the search towards multiple regions of trade-off. In addition, we propose a dynamic sharing scheme that is simple and adaptively estimated according to the on-line population distribution without needing any a priori parameter setting. Each feature in the proposed algorithm is examined to show its respective contribution, and the performance of the algorithm is compared with other evolutionary optimization methods. It is shown that the proposed algorithm has performed well in the diversity of evolutionary search and uniform distribution of non-dominated individuals along the final trade...
Quinlan, Jesse R.; Gern, Frank H.
Hybrid Wing Body (HWB) aircraft concepts continue to be promising candidates for achieving the simultaneous fuel consumption and noise reduction goals set forth by NASA's Environmentally Responsible Aviation (ERA) project. In order to evaluate the projected benefits, improvements in structural analysis at the conceptual design level were necessary; thus, NASA researchers developed the Hybrid wing body Conceptual Design and structural optimization (HCDstruct) tool to perform aeroservoelastic structural optimizations of advanced HWB concepts. In this paper, the authors present substantial updates to the HCDstruct tool and related analysis, including: the addition of four inboard and eight outboard control surfaces and two all-movable tail/rudder assemblies, providing a full aeroservoelastic analysis capability; the implementation of asymmetric load cases for structural sizing applications; and a methodology for minimizing control surface actuation power using NASTRAN SOL 200 and HCDstruct's aeroservoelastic finite-element model (FEM).
Korfmacher, Walter A
The lead optimization paradigm includes a team of experts that has a multitude of parameters to consider when moving from an initial lead compound through the lead optimization phase to the development phase. While in the past the team may have had only a medicinal chemist and a pharmacologist, the current team would often include experts in the areas of drug metabolism and pharmacokinetics (DMPK) as well as chemical toxicity. This review provides an overview of the some of the recent advances in the areas of DMPK screening plus a discussion of some of the assays that can be used to begin to screen for toxicity issues. The focus of this review is the major potential problem areas: oral bioavailability, half-life, drug-drug interactions and metabolism and toxicity issues. PMID:19519496
Devine, Caleb; Etienne, Zachariah B.; McWilliams, Sean T.
The spinning effective-one-body–numerical relativity (SEOBNR) series of gravitational wave approximants are among the best available for advanced LIGO data analysis. Unfortunately, SEOBNR codes as they currently exist within LALSuite are generally too slow to be directly useful for standard Markov-chain Monte Carlo-based parameter estimation (PE). Reduced-order models (ROMs) of SEOBNR have been developed for this purpose, but there is no known way to make ROMs of the full eight-dimensional intrinsic parameter space more efficient for PE than the SEOBNR codes directly. So as a proof of principle, we have sped up the original LALSuite SEOBNRv2 approximant code, which models waveforms from aligned-spin systems, by nearly 300x. Our optimized code shortens the timescale for conducting PE with this approximant to months, assuming a purely serial analysis, so that even modest parallelization combined with our optimized code will make running the full PE pipeline with SEOBNR codes directly a realistic possibility. A number of our SEOBNRv2 optimizations have already been applied to SEOBNRv3, a new approximant capable of modeling sources with all eight (precessing) intrinsic degrees of freedom. We anticipate that once all of our optimizations have been applied to SEOBNRv3, a similar speed-up may be achieved.
Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.
Chevoir, François; Gondret, Philippe; Lassarre, Sylvain; Lebacque, Jean-Patrick; Schreckenberg, Michael
This book covers several research fields, all of which deal with transport. Three main topics are treated: road traffic, granular matter, and biological transport. Different points of view, i.e. modelling, simulations, experiments, and phenomenological observations, are considered. Sub-topics include: highway or urban vehicular traffic (dynamics of traffic, macro/micro modelling, measurements, data analysis, security issues, psychological issues), pedestrian traffic, animal traffic (e.g. social insects), collective motion in biological systems (molecular motors...), granular flow (dense flows, intermittent flows, solid/liquid transition, jamming, force networks, fluid and solid friction), networks (biological networks, urban traffic, the internet, vulnerability of networks, optimal transport networks) and cellular automata applied to the various aforementioned fields.
Full Text Available Traffic Engineering  broadly relates to optimization of the performance of the operational IP network. In networking, network congestion occurs when a link or node is carrying so much data that its quality of service deteriorates. Typical effects include queueing delay, packet loss or the blocking of new connections. A consequence of these latter two is that incremental increases in offered load lead either only to small increases in network throughput, or to an actual reduction in network throughput. This paper discusses methods like PNP approach  and HITS method for improving QoS , which are used for traffic engineering in MPLS. This paper will examine the two approaches; discuss solutions in both PNP approach and HITS method for improving QoS and point to topics for research and advanced development.
Erzberger, H.; Chapel, J. D.
The nation's air-traffic-control system is the subject of an extensive modernization program, including the planned introduction of advanced automation techniques. This paper gives an overview of a concept for automating terminal-area traffic management. Four-dimensional (4D) guidance techniques, which play an essential role in the automated system, are reviewed. One technique, intended for on-board computer implementation, is based on application of optimal control theory. The second technique is a simplified approach to 4D guidance intended for ground computer implementation. It generates advisory messages to help the controller maintain scheduled landing times of aircraft not equipped with on-board 4D guidance systems. An operational system for the second technique, recently evaluated in a simulation, is also described.
Ray, B; Bhattacharyya, S N
The formation of density waves in two intersecting roads, with a traffic circle at the intersection, is studied. It is found that, depending on the traffic densities in the two roads, density waves can form in the traffic circle and in one or both of the roads. Depending on the expression chosen for the optimal velocity, either the congestion moves entirely to the traffic circle or the congestion becomes confined to the traffic circle and a part of the road approaching the traffic circle. PMID:16605592
Tan, Fei; Xia, Yongxiang; Tse, Chi K
Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is yet to come. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected BA scale-free networks. We find that assortative coupling can alleviate traffic congestion better than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet AS-level graphs of Japan and South Korea and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnect...
Barceló Bugeda, Jaime; Montero Mercadé, Lídia; Bullejos, Manuel; Serch Muni, Oriol; Carmona, Carlos
Time-dependent origin–destination (OD) matrices are essential input for dynamic traffic models such as microscopic and mesoscopic traffic simulators. Dynamic traffic models also support real-time traffic management decisions, and they are traditionally used in the design and evaluation of advanced traffic traffic management and information systems (ATMS/ATIS). Time-dependent OD estimations are typically based either on Kalman filtering or on bilevel mathematical programming, which can be cons...
McLin, John L.; William T. Scherer
Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system u...
Full Text Available This paper gives a novel traffic feature for identifying abnormal variation of traffic under DDOS flood attacks. It is the histogram of the maxima of the bounded traffic rate on an interval-by-interval basis. We use it to experiment on the traffic data provided by MIT Lincoln Laboratory under Defense Advanced Research Projects Agency (DARPA in 1999. The experimental results profitably enhance the evidences that traffic rate under DDOS attacks is statistically higher than that of normal traffic considerably. They show that the pattern of the histogram of the maxima of bounded rate of attack-contained traffic greatly differs from that of attack-free traffic. Besides, the present traffic feature is simple in mathematics and easy to use in practice.
Nguyen, Thai Phu
Traffic conditions on a road network often suffer from congestion. According to sources, the traffic congestion can be classified into two categories : recurrent congestion determined by the physic laws of traffic and non-recurrent congestion due to incidents, accidents or other hazards on the road. Thanks to the advancement of technologies, including computers, communications and data processing, the traffic operator is now able to detect disturbances, to measure the effects and even to anti...
PALLAVI CHOUDEKAR,; SAYANTI BANERJEE,; M.K.MUJU
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state-of-the-art of traffic control. Traffic problems nowadays are increasing because of the growing number of vehicles and the limited resources provided by current nfrastructures. The simplest way for controlling a traffic light uses timer for each phase. Another way is to use electronic sensors in order to detect vehicles, and produce signal...
Ahmed, A.; Watling, D; Ngoduy, D
Short-term congestion caused due to traffic incidents or other road environment factors significantly reduces traffic flow capacity of a link which forms a major part of travel time delays. Accurate and reliable estimate of real-time traffic state is essential for optimizing network performance during unpredictable events. Inaccurate estimate of current traffic state produces unreliable travel-time estimations which lead to ineffective traffic management strategies during traffic incident. Th...
Du, Wen-ju; Zhang, Jian-gang; An, Xin-lei; Qin, Shuang; Yu, Jian-ning
The paper presents a new urban public traffic supernetwork model by using the existing bus network modeling method, consisting of the conventional bus traffic network and the urban rail traffic network. We investigate the synchronization problem of urban public traffic supernetwork model by using the coupled complex network’s outer synchronization theory. Analytical and numerical simulations are given to illustrate the impact of traffic dispatching frequency and traffic lines optimization to ...
Kenedy Aliila Greyson
The traffic congestion is a common event during rush-hours in big cities. Costs imposed by the traffic congestion and traffic jams to the road users include: more fuel consumption, more time spent on the road, more environmental pollution, etc. This research aims at the optimization of the available capacity of the road network (infrastructure) using coordinated traffic lights. The analysis used here is a projected outcome of the road sector status during rush hours (the worse case road situa...
Traffic on motorways can slow down for no apparent reason. Sudden changes in speed by one or two drivers can create a chain reaction that causes a traffic jam for the vehicles that are following. This kind of phantom traffic jam is called a "jamiton" and the article discusses some of the ways in which traffic engineers produce…
曹娟; 张颖淳; 苏伯洪
道路交通系统是社会物流实现的重要支撑，其中重要站点的故障可能造成交通系统的运营限于瘫痪，甚至产生重大的经济影响。针对道路交通网络中的相继故障问题，从动静结合的角度分析了道路交通网络的脆弱性。为了检测道路交通网络在相继故障下的脆弱性动态变化，首先建立了道路交通网络的级联反应动力学模型；然后提出该模型中脆弱性的优化设计方案，并利用算法进化得到网络的最优设计；最后利用复杂网络理论得到道路交通网络的网络结构图，通过该算例验证了提出的模型和优化方法的有效性和实际应用性。仿真实验表明该模型和方法能有效地降低交通网络的脆弱性。%Road traffic system is an important support for social logistics .The failure of a significant site may result in the paralysis of the w hole traffic system ,and even cause a significant economic damage .In this paper ,the dynamical vulnerability of the road traffic network has been explored according to the suc-cessive failures within the system .First ,a cascade reaction model of the road traffic network has been es-tablished for detecting dynamical changes of the network vulnerability facing successive failures .Then an optimal design of the model has been proposed based on evolutionary algorithm .Finally ,the complex net-work theory is applied to obtain the network structure of a road network .And this case study is given to verify the effectiveness and practical application of the proposed model and optimization algorithm .Simula-tion results show that the proposed method can effectively reduce the vulnerability of the road traffic net-work .
The analysis of alternate CANDU fuels along with natural uranium-based fuel was carried out from the view point of optimal in-core fuel management at approach to refuelling equilibrium. The alternate fuels considered in the present work include thorium containing oxide mixtures (MOX), plutonium-based MOX, and Pressurised Water Reactor (PWR) spent fuel recycled in CANDU reactors (Direct Use of spent PWR fuel in CANDU (DUPIC)); these are compared with the usual natural UO2 fuel. The focus of the study is on the 'Approach to Refuelling Equilibrium' period which immediately follows the initial commissioning of the reactor. The in-core fuel management problem for this period is treated as an optimization problem in which the objective function is the refuelling frequency to be minimized by adjusting the following decision variables: the channel to be refuelled next, the time of the refuelling and the number of fresh fuel bundles to be inserted in the channel. Several constraints are also included in the optimisation problem which is solved using Perturbation Theory. Both the present 37-rod CANDU fuel bundle and the proposed CANFLEX bundle designs are part of this study. The results include the time to reach refuelling equilibrium from initial start-up of the reactor, the average discharge burnup, the average refuelling frequency and the average channel and bundle powers relative to natural UO2. The model was initially tested and the average discharge burnup for natural UO2 came within 2% of the industry accepted 199 MWh/kgHE. For this type of fuel, the optimization exercise predicted the savings of 43 bundles per full power year. In addition to producing average discharge burnups and other parameters for the advanced fuels investigated, the optimisation model also evidenced some problem areas like high power densities for fuels such as the DUPIC. Perturbation Theory has proven itself to be an accurate and valuable optimization tool in predicting the time between
Nagel, Kai; Stretz, Paula; Pieck, Martin; Donnelly, Rick; Barrett, Christopher L.
Knowledge of fundamental traffic flow characteristics of traffic simulation models is an essential requirement when using these models for the planning, design, and operation of transportation systems. In this paper we discuss the following: a description of how features relevant to traffic flow are currently under implementation in the TRANSIMS microsimulation, a proposition for standardized traffic flow tests for traffic simulation models, and the results of these tests for two different ve...
By analyzing the influence factors of railway passenger traffic from 1997 to 2007, partial least-squares regression model were established, then actual and predicted values of railway passenger traffic were compared, and the model prediction error was relatively high. In order to improve the prediction accuracy of the model, PSO optimization algorithm was adopted to optimize the regression coefficients, then a new model was got. Upon examination, the prediction error of the model dropped to 1.01%from original 3.04%. Finally the railway passenger traffic from 2013 to 2014 which we use this model to predict were 2 109.705 million and 2 273.688 million.%通过对1997-2012年铁路客运量的影响因素进行分析，建立偏最小二乘回归模型，并用实际的铁路客运量与预测值进行比较，检验出模型的预测误差较大.为了提高模型的预测精度，采取粒子群优化算法优化回归系数，得到一个新的模型.经检验，该模型的预测误差由原模型的3.04%降到1.01%.最后用该模型预测出2013-2014年的铁路客运量分别为210.9705千万人和227.3688千万人.
Guzzi, Donatella; Pippi, Ivan; Aiazzi, Bruno; Baronti, Stefano; Carlà, Roberto; Lastri, Cinzia; Nardino, Vanni; Raimondi, Valentina; Santurri, Leonardo; Selva, Massimo; Alparone, Luciano; Garzelli, Andrea; Lopinto, Ettore; Ananasso, Cristina; Barducci, Alessandro
PRISMA is an Earth observation system that combines a hyperspectral sensor with a panchromatic, medium-resolution camera. OPTIMA is one of the five independent scientific research projects funded by the Italian Space Agency in the framework of PRISMA mission for the development of added-value algorithms and advanced applications. The main goal of OPTIMA is to increase and to strengthen the applications of PRISMA through the implementation of advanced methodologies for the analysis, integration and optimization of level 1 and 2 products. The project is comprehensive of several working packages: data simulation, data quality, data optimization, data processing and integration and, finally, evaluation of some applications related to natural hazards. Several algorithms implemented during the project employ high-speed autonomous procedures for the elaboration of the upcoming images acquired by PRISMA. To assess the performances of the developed algorithms and products, an end-to-end simulator of the instrument has been implemented. Data quality analysis has been completed by introducing noise modeling. Stand-alone procedures of radiometric and atmospheric corrections have been developed, allowing the retrieval of at-ground spectral reflectance maps. Specific studies about image enhancement, restoration and pan-sharpening have been carried out for providing added-value data. Regarding the mission capability of monitoring environmental processes and disasters, different techniques for estimating surface humidity and for analyzing burned areas have been investigated. Finally, calibration and validation activities utilizing the CAL/VAL test site managed by CNR-IFAC and located inside the Regional Park of San Rossore (Pisa), Italy have been considered.
Mobile sensing technology based on smartphones is an emerging direction and a hot spot in the field of urban traffic information detection, and it is also an important part of the big traffic data. Relying on the powerful mobile communication technology of smartphones and the environmental perception ability of various embedded sensors, we can obtain microcosmic information,such as real-time position, attitude dynamics of traffic participants, and even traffic scene. In this paper, we reviewed the advances in smartphones based on traffic information acquisition, parameter detection, and information service. We Also discussed the challenges and solutions that the smartphones faced in this field, like energy dissipation, detection data deviation, as well as user's personal privacy and security. We also elaborated several future research directions in this field.%基于智能手机应用的移动传感技术是城市交通信息检测领域的一个新兴方向和研究热点,也是交通大数据研究的重要组成部分.依靠智能手机强大的移动通讯技术,以及各种嵌入式传感器的环境感知能力,就能够实时获取到交通参与者的位置、姿态、动态、甚至交通场景等各种微观信息.本文结合当前智能手机传感器件的标准配置状况,综述了智能手机应用在交通信息获取、交通参数检测、交通信息服务等方面的研究进展.同时分析了智能手机在能量损耗、检测数据偏差以及用户个人隐秘与安全等应用中面临的挑战,并讨论了对应的解决方法.最后,对未来的研究发展趋势进行展望.
Nark, Douglas M.; Jones, Michael G.; Sutliff, Daniel L.; Ayle, Earl; Ichihashi, Fumitaka
The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more desirable. This paper describes improvements to a previously established broadband acoustic liner optimization process using the Advanced Noise Control Fan rig as a demonstrator. Specifically, in-duct attenuation predictions with a statistical source model are used to obtain optimum impedance spectra over the conditions of interest. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Constant-depth, double-degree of freedom and variable-depth, multi-degree of freedom designs are carried through design, fabrication, and testing to validate the efficacy of the design process. Results illustrate the value of the design process in concurrently evaluating the relative costs/benefits of these liner designs. This study also provides an application for demonstrating the integrated use of duct acoustic propagation/radiation and liner modeling tools in the design and evaluation of novel broadband liner concepts for complex engine configurations.
The present design for FBR fuel rods includes usually MOX fuel pellets cladded into stainless steel tubes, together with UO2 axial blanket and stainless steel hexagonal wrappers. Mixed carbide, nitride and metallic fuels have been tested as alternative fuels in test reactors. Among others, the objectives to develop these alternative fuels are to gain a high breeding ratio, short doubling time and high linear ratings. Fuel rod and assembly designers are now concentrating on finding the combination of optimized fuel, cladding and wrapper materials which could result in improvement of fuel operational reliability under high burnups and load-follow mode of operation. The purpose of the meeting was to review the experience of advanced FBR fuel fabrication technology, its properties before, under and after irradiation, peculiarities of the back-end of the nuclear fuel cycle, and to outline future trends. As a result of the panel discussion, the recommendations on future Agency activities in the area of advanced FBR fuels were developed. A separate abstract was prepared for each of the 10 presentations of this meeting. Refs, figs and tabs
Devine, Caleb; McWilliams, Sean T
The Spinning Effective One Body-Numerical Relativity (SEOBNR) series of gravitational wave approximants are among the best available for Advanced LIGO data analysis. Unfortunately, SEOBNR codes as they currently exist within LALSuite are generally too slow to be directly useful for standard Markov-Chain Monte Carlo-based parameter estimation (PE). Reduced-Order Models (ROMs) of SEOBNR have been developed for this purpose, but there is no known way to make ROMs of the full eight-dimensional intrinsic parameter space more efficient for PE than the SEOBNR codes directly. So as a proof of principle, we have sped up the original LALSuite SEOBNRv2 approximant code, which models waveforms from aligned-spin systems, by about 280x. Our optimized code shortens the timescale for conducting PE with this approximant to months, assuming a purely serial analysis, so that even modest parallelization combined with our optimized code will make running the full PE pipeline with SEOBNR codes directly a realistic possibility. A n...
Yang, Da; Gan, Chock; Chidambaram, P. R.; Nallapadi, Giri; Zhu, John; Song, S. C.; Xu, Jeff; Yeap, Geoffrey
How to maintain the Moore's Law scaling beyond the 193 immersion resolution limit is the key question semiconductor industry needs to answer in the near future. Process complexity will undoubtfully increase for 14nm node and beyond, which brings both challenges and opportunities for technology development. A vertically integrated design-technologymanufacturing co-optimization flow is desired to better address the complicated issues new process changes bring. In recent years smart mobile wireless devices have been the fastest growing consumer electronics market. Advanced mobile devices such as smartphones are complex systems with the overriding objective of providing the best userexperience value by harnessing all the technology innovations. Most critical system drivers are better system performance/power efficiency, cost effectiveness, and smaller form factors, which, in turns, drive the need of system design and solution with More-than-Moore innovations. Mobile system-on-chips (SoCs) has become the leading driver for semiconductor technology definition and manufacturing. Here we highlight how the co-optimization strategy influenced architecture, device/circuit, process technology and package, in the face of growing process cost/complexity and variability as well as design rule restrictions.
This work proposes advances in the implementation of a flexible genetic algorithm (GA) for fuel loading pattern optimization for Boiling Water Reactors (BWRs). In order to avoid specific implementations of genetic operators and to obtain a more flexible treatment, a binary representation of the solution was implemented; this representation had to take into account that a little change in the genotype must correspond to a little change in the phenotype. An identifier number is assigned to each assembly by means of a Gray Code of 7 bits and the solution (the loading pattern) is represented by a binary chain of 777 bits of length. Another important contribution is the use of a Fitness Function which includes a Heuristic Function and an Objective Function. The Heuristic Function which is defined to give flexibility on the application of a set of positioning rules based on knowledge, and the Objective Function that contains all the parameters which qualify the neutronic and thermal hydraulic performances of each loading pattern. Experimental results illustrating the effectiveness and flexibility of this optimization algorithm are presented and discussed.
Tsz Leung Yip
A model is developed for studying marine traffic flow through classical traffic flow theories, which can provide us with a better understanding of the phenomenon of traffic flow of ships. On one hand, marine traffic has its special features and is fundamentally different from highway, air and pedestrian traffic. The existing traffic models cannot be simply extended to marine traffic without addressing marine traffic features. On the other hand, existing literature on marine traffic focuses on...
Linawati Linawati; I Made Suartika
Network traffic generator can be produced using OPNET. OPNET generates the traffic as explicit traffic or background traffic. This paper demonstrates generating traffic in OPNET 7.0 as background traffic. The traffi generator that was simulated is self-similar traffic with different Hurst parameter. The simulation results proved that OPNET with background traffic function can be as a qualified self-similar traffic generator. These results can help in investigating and analysing network perfor...
Full Text Available Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.
Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei
Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183
Ebrahim Fouladvand, M.; Sadjadi, Zeinab; Reza Shaebani, M.
We construct a stochastic cellular automata model for the description of vehicular traffic at a roundabout designed at the intersection of two perpendicular streets. The vehicular traffic is controlled by a self-organized scheme in which traffic lights are absent. This controlling method incorporates a yield-at-entry strategy for the approaching vehicles to the circulating traffic flow in the roundabout. Vehicular dynamics is simulated and the delay experienced by the traffic at each individual street is evaluated. We discuss the impact of the geometrical properties of the roundabout on the total delay. We compare our results with traffic-light signalization schemes, and obtain the critical traffic volume over which the intersection is optimally controlled through traffic-light signalization schemes.
Gaciarz, Matthis; Aknine, Samir; BHOURI, Neila
Urban congestion is a major problem in our society for quality of life and for productivity. The increasing communication abilities of vehicles and recent advances in artificial intelligence allow new solutions to be considered for traffic regulation, based on real-time information and distributed cooperative decision-making models. The paper presents a mechanism allowing a distributed regulation of the right-of-way of the vehicles at an intersection. The decision-making relies on an automati...
Improved Disturbance Observer （DOB） Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process%Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process
周平; 向波; 柴天佑
Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.
Nagel, K. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., Santa Fe, NM (United States)]|[Koeln Univ. (Germany). Zentrum fuer Paralleles Rechnen; Rasmussen, S. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., Santa Fe, NM (United States)
We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows near-critical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making predictions much harder. A simulation of a simplified transportation network supports our argument.
Chuan-Fei, Dong; Guan-Wen, Wang; Xiao-Yan, Sun; Bing-Hong, Wang
The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we studied dynamics of traffic flow with real-time information provided and the influence of a feedback strategy named prediction feedback strategy is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux.
Maerivoet, Sven; De Moor, Bart
The scientific field of traffic engineering encompasses a rich set of mathematical techniques, as well as researchers with entirely different backgrounds. This paper provides an overview of what is currently the state-of-the-art with respect to traffic flow theory. Starting with a brief history, we introduce the microscopic and macroscopic characteristics of vehicular traffic flows. Moving on, we review some performance indicators that allow us to assess the quality of traffic operations. A f...
Herrmann, Hans; Schreckenberg, Michael; Wolf, Dietrich; Social, Traffic and Granular Dynamics
"Are there common phenomena and laws in the dynamic behavior of granular materials, traffic, and socio-economic systems?" The answers given at the international workshop "Traffic and Granular Flow '99" are presented in this volume. From a physical standpoint, all these systems can be treated as (self)-driven many-particle systems with strong fluctuations, showing multistability, phase transitions, non-linear waves, etc. The great interest in these systems is due to several unexpected new discoveries and their practical relevance for solving some fundamental problems of today's societies. This includes intelligent measures for traffic flow optimization and methods from "econophysics" for stabilizing (stock) markets.
Bando, M; Nakanishi, K; Nakayama, A; Bando, Masako; Hasebe, Katsuya; Nakanishi, Ken; Nakayama, Akihiro
We demonstrate that in Optimal Velocity Model (OVM) delay times of vehicles coming from the dynamical equation of motion of OVM almost explain the order of delay times observed in actual traffic flows without introducing explicit delay times. Delay times in various cases are estimated: the case of a leader vehicle and its follower, a queue of vehicles controlled by traffic lights and many-vehicle case of highway traffic flow. The remarkable result is that in most of the situation for which we can make a reasonable definition of a delay time, the obtained delay time is of order 1 second.
To evaluate the potential of advanced modeled iterative reconstruction (ADMIRE) for optimizing radiation dose of high-pitch coronary CT angiography (CCTA). High-pitch 192-slice dual-source CCTA was performed in 25 patients (group 1) according to standard settings (ref. 100 kVp, ref. 270 mAs/rot). Images were reconstructed with filtered back projection (FBP) and ADMIRE (strength levels 1-5). In another 25 patients (group 2), high-pitch CCTA protocol parameters were adapted according to results from group 1 (ref. 160 mAs/rot), and images were reconstructed with ADMIRE level 4. In ten patients of group 1, vessel sharpness using full width at half maximum (FWHM) analysis was determined. Image quality was assessed by two independent, blinded readers. Interobserver agreements for attenuation and noise were excellent (r = 0.88/0.85, p < 0.01). In group 1, ADMIRE level 4 images were most often selected (84 %, 21/25) as preferred data set; at this level noise reduction was 40 % compared to FBP. Vessel borders showed increasing sharpness (FWHM) at increasing ADMIRE levels (p < 0.05). Image quality in group 2 was similar to that of group 1 at ADMIRE levels 2-3. Radiation dose in group 2 (0.3 ± 0.1 mSv) was significantly lower than in group 1 (0.5 ± 0.3 mSv; p < 0.05). In a selected population, ADMIRE can be used for optimizing high-pitch CCTA to an effective dose of 0.3 mSv. (orig.)