Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.

A RECOGNITION PROBLEM IN CONVERTING LINEAR PROGRAMMING TO NETWORK FLOW MODELS

The main goal of this paper is to study the following combinatorial problem : given a finite set E = (e1, e2, ...,em} and a subset family a - [S1,S2, ... ,Sk} of E , does there exist a tree T with the edge set E such that each induced subgraph T[Si] of Si is precisely a path (1≤i≤k) ?

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.

THE APPLICATION OF THE BRANCH AND BOUND METHOD FOR DETERMINING THE MINIMUM FLOW OF A TRANSPORT NETWORK

Blockage is a kind of phenomenon frequently occurred in a transport network, in which the human beings are the moving subjects. The minimum flow of a network defined in this paper means the maximum flow quantity through the network in the seriously blocked situation. It is an important parameter in designing and operating a transport network, especially in an emergency evacuation network. A branch and bound method is presented to solve the minimum flow problem on the basis of the blocking flow theory and the algorithm and its application are illustrated by examples.

Flow Cytometric Evidence for Hydroxyl Radical-induced Apoptosis in Tobacco Protoplasts

Protoplasts prepared from tobacco (Nicotiana tabacum L., cultivar BY-2) suspension cells have similar morphological characteristics to those in animal cells. The hallmarks of apoptosis such as condensation and peripheral distribution of nuclei, TUNEL positive reaction, and DNA ladders were observed when tobacco protoplasts were treated with the hydroxyl radical generating system (1.0 mmol/L FeSO4/0.5 mmol/L H2O2). In animals, the loss of transmembrane potential (DeltaPsi(m)) and the exposure of phospholipid phosphatidylserine (PS) are believed to be the main apoptosis events. To test whether these significant processes take place in plants, flow cytometry was used to detect annexin V binding and changes in DeltaPsi(m). Results showed that the PS turned out from inner membrane and DeltaPsi(m) gradually decreased during the apoptosis. All these apoptotic characteristics proved that hydroxyl radicals can cause typical programmed cell death (PCD) in tobacco protoplasts and this design can be served as an effective experiment system to explore the mechanism of plant apoptosis.

不确定条件下的零等待Flow shop生产调度问题

研究了处理时间不确定条件下,含零等待模块的模糊Flowshop生产调度问题;采用三角模糊数描述处理时间的不确定性,用零等待策略对加工过程进行约束,建立了基于模糊规划理论的零等待Flowshop调度模型,通过中间值最大隶属度的方法,将原有的模糊调度模型转化为清晰的调度模型;最后应用改进的模拟退火算法对模型进行仿真优化,制定了适用于实际排产过程中的GANTT图,仿真结果说明了调度模型的正确性和改进算法的有效性。

柔性Flow Shop调度问题的研究现状及发展趋势

许多实际生产环境如石油、化工、钢铁等流程工业都是柔性FlowShop环境 .文中对柔性FlowShop调度问题的研究现状进行了评述 。

Incremental Static Analysis of 2D Flow by Inter-Colliding Point-Particles and Use of Incompressible Rhombic Element

A simple method is proposed, for incremental static analysis of a set of inter-colliding particles, simulating 2D flow. Within each step of proposed algorithm, the particles perform small displacements, proportional to the out-of-balance forces, acting on them. Numerical experiments show that if the liquid is confined within boundaries of a set of inter-communicating vessels, then the proposed method converges to a final equilibrium state. This incremental static analysis approximates dynamic behavior with strong damping and can provide information, as a first approximation to 2D movement of a liquid. In the initial arrangement of particles, a rhombic element is proposed, which assures satisfactory incompressibility of the fluid. Based on the proposed algorithm, a simple and short computer program (a “pocket” program) has been developed, with only about 120 Fortran instructions. This program is first applied to an amount of liquid, contained in a single vessel. A coarse and refined discretization is tried. In final equilibrium state of liquid, the distribution on hydro-static pressure on vessel boundaries, obtained by proposed computational model, is found in satisfactory approximation with corresponding theoretical data. Then, an opening is formed, at the bottom of a vertical boundary of initial vessel, and the liquid is allowed to flow gradually to an adjacent vessel. Almost whole amount of liquid is transferred, from first to second vessel, except of few drops-particles, which remain, in equilibrium, at the bottom of initial vessel. In the final equilibrium state of liquid, in the second vessel, the free surface level of the liquid confirms that the proposed rhombing element assures a satisfactory incompressibility of the fluid.

RESEARCH ON THE BLOCKING FLOW IN A TRANSPORTATION NETWORK──THE GENERAL CONCEPTS AND THEORY OF THE BLOCKING FLOW

Blockage is a kind of phenomenon occurring frequently in modern transportation network. This paper deals with the research work on the blocking now in a network with the help of network flow theory. The blockage phenomena can be divided intO local blockage and network blockage. In this paper, which deals mainly with the latter, the fundamental concepts and definitions of network blocking flow, blocking outset are presented and the related theorems are proved. It is proved that the sufficient and necessary condition for the emergence of a blocking now in a network is the existence of the blocking outset. The necessary conditions for the existence of the blocking outset in a network are analysed and the characteristic cutset of blockage which reflects the all possible situation of blocking nows in the network is defined.In the last part of the paper the mathematical model of the minimum blocking now is developed and the solution to a small network is given.

Optimization model of truck flow at open-pit mines and standards for feasibility test

In order to increase production efficiency at open-pit mines, on the basis oflinear programming, a practical mathematical model for optimizing truck flow was developed, whichimproved the traditional fixed manual schedule method. The model has advantages from linearprogramming and objective programming, makes most handling points working at full capacity and keepsan optimized ratio between trucks and excavators. For ensuring feasibility of the model inpractical production, four standards for feasibility test were proposed. The model satisfied all thestandards. The application in a large scale open-pit iron mine indicated that the model reduced thenumber of required trucks by 10 percent compared with the fixed manual schedule method.

RESEARCH ON THE LOCAL BLOCKAGE OF A TRANSPORTATION NETWORK AND ITS MINIMUM FLOW CAPACITY

This paper deals with the research work on the phenomena of local blockage in a transportation network. Onthe basis of introducing the research results in [1], theminimum now capacity problem of a network in the mostseriously blocked situation is studied. With the conceptof complete outset presented in [1], the relationship between the minimum now capacity of a network and its minimum complete cut capacity is discussed, and the reasons for the difference betweent the minimum now capacity of a network and its minimum complete cut capa-city are analysed. In order to get the solution to the problem, the concepts of normalization of a network and its blocking path graph are presented. In the paper it is proved that the necessary and sufficient conditions for the equality between the minumum now capacity and its minumum complete cut capacity are the existence of a feasible flow in the blocking path graph. For the reason that there are some dependent production points in the blocking path graph of a network, the proof about the tenability of the Gale's Theorm for the planat normalized network without circuit is made.

Multi-Reservoir Optimization for Maximization of Releases for Hydropower Generation Considering Environmental Flow

Water is the soul of the world. It is the most important element for the survival of humans, animals, birds, plants and all other living things on earth. Water is essential for the beginning of life as well as regular availability of water ensuring the survival, growth and overall nourishment. Thus, proper planning and use of reservoir water are essential for all. To tackle this issue different optimization techniques underline their need and importance in the reservoir operations. In the present study, multi-reservoir optimization model is developed using Python programing language considering the objective of maximization of total annual release for hydropower generation. Model is applied to 3 reservoirs from Godavari River basin from Maharashtra state India. Water essential for conservation of environment has also been made available in river as environmental flow as per the recommendations of Central Water Commission (CWC) India. Developed optimization model provides optimal monthly operation policies.

Enhance Information Flow Tracking with Function Recognition

With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Thus the function recognition is introduced to improve the information flow tracking. Function recognition is a helpful technique recognizing the function body from the software binary to analyze the binary code. And that no false positive and no false negative in our experiments strongly proves that our approach is effective.

Sustainable Multi-Objective Multi-Reservoir Optimization Considering Environmental Flow

Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.

An ECN-based Optimal Flow Control Algorithm for the Internet

According to the Wide Area Network model, we formulate Internet flow control as a constrained convex programming problem, where the objective is to maximize the total utility of all sources over their transmission rates. Based on this formulation, flow control can be converted to a normal unconstrained optimization problem through the barrier function method, so that it can be solved by means of a gradient projection algorithm with properly rate iterations. We prove that the algorithm converges to the global optimal point, which is also a stable proportional fair rate allocation point, provided that the step size is properly chosen. The main difficulty facing the realization of iteration algorithm is the distributed computation of congestion measure. Fortunately, Explicit Congestion Notification (ECN) is likely to be used to improve the performance of TCP in the near future. By using ECN, it is possible to realize the iteration algorithm in IP networks. Our algorithm is divided into two parts, algorithms in the router and in the source. The router marks the ECN bit with a probability that varies as its buffer occupancy varies, so that the congestion measure of links can be communicated to the source when the marked ECN bits are reflected back from its destination. Source rates are then updated by all sessions according to the received congestion measure. The main advantage of our scheme is its fast convergence ability and robustness; it can also provide the network with zero packet loss by properly choosing the queue threshold and provide differentiated service to users by applying different utility functions.

Asymptotically Optimal Scenario Analysis and Wait-and-See Model for Optimal Power Flow With Wind Power

精确模拟风功率分布的场景,有效求解反映风电随机性的最优潮流模型,对大规模风电并网的经济调度、质量控制及安全运行均具有重要意义。引入风电随机变量,建立最优潮流的＂wait-and-see＂（WS-OPF）模型;采用优于其他指标的瓦瑟斯坦（Wasserstein）距离为衡量指标,形成与风功率概率分布最优近似的场景模型,生成渐近最优场景,获得潮流分布及机组最优出力等指导调度安全经济运行的重要信息。最后,以IEEE 30和IEEE 300系统为例,对比各种距离指标的模拟精度,验证Wasserstein距离的优良性;同时,与不考虑风电随机性的模型相比,WS-OPF模型能更好地模拟风功率随机特性,提供与实际发生的风功率相近的调度方案,从而合理地规避风电接入电网的风险,提高风电的消纳能力。

Convexification of Hybrid AC-DC Optimal Power Flow with Line-Commutated Converters

Line-commutated converter (LCC)-based high-voltage DC (HVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.

An Algorithm of Programming Data Flow Analysis Based on Data Flow Expression

This paper states the basic principle of program data flow analysis in a formal way and gives the concept of data flow expression. On the basis of this concept, an algorithm of finding data flow exceptions is rendered. This algorithm has great generality, with which it is easy to develop a tool for program test. So it is practical in application.

Optimal configuration of distributed power flow controller to enhance system loadability via mixed integer linear programming

The increase of energy consumption has caused power systems to operate close to the limit of their capacity.The distributed power flow controller(DPFC),as a new member of distributed flexible AC transmission systems,is introduced to remove this barrier.This paper proposes an optimal DPFC configuration method to enhance system loadability considering economic performance based on mixed integer linear programming.The conflicting behavior of system loadability and DPFC investment is analyzed and optimal solutions are calculated.Thereafter,the fuzzy decision-making method is implemented for determining the most preferred solution.In the most preferred solution obtained,the investment of DPFCs is minimized to find the optimal number,locations and set points.Simulation results on the IEEERTS79 system demonstrate that the proposed method is effective and reasonable.

Voltage Stability Constrained Optimal Power Flow for Unbalanced Distribution System Based on Semidefinite Programming

This paper proposes a voltage stability constrained optimal power flow(VSC-OPF)for an unbalanced distribution system with distributed generators(DGs)based on semidefinite programming(SDP).The AC optimal power flow(ACOPF)for unbalanced distribution systems is formulated as a chordal relaxation-based SDP model.The minimal singular value(MSV)of the power flow Jacobian matrix is adopted to indicate the voltage stability margin.The Jacobian matrix can be explicitly expressed by ACOPF state variables.The nonlinear constraint on the Jacobian MSV is then replaced with its maximal convex subset using linear matrix inequality(LMI),which can be incorporated in the SDP-based ACOPF formulation.A penalty technique is leveraged to improve the exactness of the SDP relaxation.Case studies performed on several IEEE test systems validate the effectiveness of the proposed method.