Competitive analysis of price online inventory problem with cost function

In this paper,a new price is given to the online decision maker at the beginning of each day.The trader must decide how many items to purchase according to the current price.We present three variants and an online algorithm based on cost function.The competitive ratio of the online algorithm is given for each variant,which is a performance measure of an online algorithm.More importantly,we show that the online algorithm is optimal.

Functional Sustainability of a Flight Dynamics Control System for Stable Hovering Flight of an Unmanned Aerial Vehicle(UAV),such as in Agricultural Applications:Mathematical Modeling and Simulation

The simulation of a control system for the longitudinal axis of the rotary or fixed-wing unmanned aerial vehicles(UAVs)is demonstrated in this study.The control unit includes design considerations of two controllers to provide robust stability,tracking of the proposed linear dynamics,an adequate set of proportional-integral-derivative(PID)controller gains,and a minimal cost function.The PID control and linear quadratic regulator(LQR)with or without full-state-observer were evaluated.An optimal control system is assumed to provide fast rise and settling time,minimize overshoot,and eliminate the steady-state error.The effectiveness of this approach was verified by a linear model of the UAV aircraft in the semi-dynamic simulation platform of Matlab/Simulink,in which the open-loop system was assessed in terms of flight robustness and reference tracking.The experimental results show that the proposed controllers effectively improve the configuration of the control system of the plant,maintain the sustainability of the dynamic flight model stability,and diminish the flight controller errors.The LQR provides robust stability,but it is not optimal in the transient phase of particular plant output.The PID control system can adjust the controller’s gains for optimal hovering(or stable slow flight)and is especially useful for the tracking system.Finally,comparing aircraft stability using PID and LQR controllers shows that the latter has less overshoot and a shorter settling time;in addition,all proposed controllers can be practically deployed as one UAV’s system,which can be handled as an exemplary model of the UAV flight management system.

Time-inconsistent stochastic linear-quadratic control problem with indefinite control weight costs

A time-inconsistent linear-quadratic optimal control problem for stochastic differential equations is studied.We introduce conditions where the control cost weighting matrix is possibly singular.Under such conditions,we obtain a family of closed-loop equilibrium strategies via multi-person differential games.This result extends Yong’s work(2017) in the case of stochastic differential equations,where a unique closed-loop equilibrium strategy can be derived under standard conditions(namely,the control cost weighting matrix is uniformly positive definite,and the other weighting coefficients are positive semidefinite).

Success probability orientated optimization model for resource allocation of the technological innovation multi-project system

A success probability orientated optimization model for resource allocation of the technological innovation multi-project system is studied. Based on the definition of the technological innovation multi-project system, the leveling optimization of cost and success probability is set as the objective of resource allocation. The cost function and the probability function of the optimization model are constructed. Then the objective function of the model is constructed and the solving process is explained. The model is applied to the resource allocation of an enterprise's technological innovation multi-project system. The results show that the proposed model is more effective in rational resource allocation, and is more applicable in maximizing the utility of the technological innovation multi-project system. ? 2016 Beijing Institute of Aerospace Information.

Optimal obstacle avoidance via distributed consensus algorithms with communication delay

A consensus problem of multi-agent system subject to the communication delay with fixed and switching topologies as well as optimal obstacle avoidance is investigated. An innovative non-quadratic obstacle avoidance cost function is designed from an inverse optimal control perspective and a novel dynamic potential field whose vectors are rotating around the obstacle is introduced to avoid obstacles. The asymptotic stability condition of dynamical networks based on the Lyapunov-Krasovskii function is obtained via a linear matrix inequality (LMI) formulation. Finally, numerical examples are presented to show the effectiveness of the proposed theoretical results. ? 2016 Beijing Institute of Aerospace Information.

基于遗传算法的指纹方向图分区

In this work, we introduce a method of fingerprint directional image partitioning based on GA. According to the fingerprint topology, A set of dynamic partition masks and a cost estimating function are designed to guide the partitioning procedure. Finding best fitted mask application is converted to an functional optimizing problem, and we give out a GA solution to the problem. At last, we discuss the application of the proposed method in Fingerprint Classification.

Effective path planning method for low detectable aircraft

To utilizing the characteristic of radar cross section （RCS） of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS changing model of low detectable aircraft, then establishes a threat model of a ground-based air defense system according to the relations between RCS and the radar range coverage. By the new cost functions of the flight path, which consider both factors of the survival probability and the distance of total route, this path planning method is simulated based on the Dijkstra algorithm, and the planned route meets the flight capacity constraints. Simulation results show that using the effective path planning algorithm, the low detectable aircraft can give full play to its own advantage of stealth to achieve the purpose of silent penetration.

A novel modeling approach for vertical handover based on dynamic k-partite graph in heterogeneous networks

The future network world will be embedded with different generations of wireless technologies,such as 3G,4G and 5G.At the same time,the development of new devices equipped with multiple interfaces is growing rapidly in recent years.As a consequence,the vertical handover protocol is developed in order to provide ubiquitous connectivity in the heterogeneous wireless environment.Indeed,by using this protocol,the users have opportunities to be connected to the Internet through a variety of wireless technologies at any time and anywhere.The main challenge of this protocol is how to select the best access network in terms of Quality of Service(QoS)for users.For that,many algorithms have been proposed and developed to deal with the issue in recent studies.However,all existing algorithms permit only the selection of one access network from the available networks during the vertical handover process.To cope with this problem,in this paper we propose a new approach based on k-partite graph.Firstly,we introduce k-partite graph theory to model the vertical handover problem.Secondly,the selection of the best path is performed by a robust and lightweight mechanism based on cost function and Dijkstra’s algorithm.The experimental results show that the proposed approach can achieve better performance of QoS than the existing algorithms for FTP traffic and video streaming.

Anisotropic Total Variation Regularization Based NAS-RIF Blind Restoration Method for OCT Image

Based on anisotropic total variation regularization(ATVR), a nonnegativity and support constraints recursive inverse filtering(NAS-RIF) blind restoration method is proposed to enhance the quality of optical coherence tomography(OCT) image. First, ATVR is introduced into the cost function of NAS-RIF to improve the noise robustness and retain the details in the image.Since the split Bregman iterative is used to optimize the ATVR based cost function, the ATVR based NAS-RIF blind restoration method is then constructed. Furthermore, combined with the geometric nonlinear diffusion filter and the Poisson-distribution-based minimum error thresholding, the ATVR based NAS-RIF blind restoration method is used to realize the blind OCT image restoration. The experimental results demonstrate that the ATVR based NAS-RIF blind restoration method can successfully retain the details in the OCT images. In addition, the signal-to-noise ratio of the blind restored OCT images can be improved, along with the noise robustness.

On-line blind source separation algorithm based on second order statistics

An on-line blind source separation （BSS） algorithm is presented in this paper under the assumption that sources are temporarily correlated signals. By using only some of the observed samples in a recursive calculation, the whitening matrix and the rotation matrix could be approximately obtained through the measurement of only one cost function. SimNations show goad performance of the algorithm.

A computational model of the human glucose-insulin regulatory system

Objective：A computational model of insulin secretion and glucose metabolism for assisting the diagnosis of diabetes mellitus in clinical research is introduced.The proposed method for the estimation of parameters for a system of ordinary differential equations（ODEs）that represent the time course of plasma glucose and insulin concentrations during glucose tolerance test（GTT）in physiological studies is presented.The aim of this study was to explore how to interpret those laboratory glucose and insulin data as well as enhance the Ackerman mathematical model.Methods：Parameters estimation for a system of ODEs was performed by minimizing the sum of squared residuals（SSR）function,which quantifies the difference between theoretical model predictions and GTT＇s experimental observations.Our proposed perturbation search and multiple-shooting methods were applied during the estimating process.Results：Based on the Ackerman＇s published data,we estimated the key parameters by applying R-based iterative computer programs.As a result,the theoretically simulated curves perfectly matched the experimental data points.Our model showed that the estimated parameters,computed frequency and period values,were proven a good indicator of diabetes.Conclusion：The present paper introduces a computational algorithm to biomedical problems,particularly to endocrinology and metabolism fields,which involves two coupled differential equations with four parameters describing the glucose-insulin regulatory system that Ackerman proposed earlier.The enhanced approach may provide clinicians in endocrinology and metabolism field insight into the transition nature of human metabolic mechanism from normal to impaired glucose tolerance.

Research of NO_(2) vertical profiles with look-up table method based on MAX-DOAS

Obtaining the vertical distribution profile of trace gas is of great significance for studying the diffusion procedure of air pollution.In this article,a look-up table method based on multi-axis differential optical absorption spectroscopy(MAX-DOAS)technology is established for retrieving the tropospheric NO_(2) vertical distribution profiles.This method retrieves the aerosol extinction profiles with minimum cost function.Then,the aerosol extinction profiles and the atmospheric radiation transfer model(RTM)are employed to establish the look-up table for retrieving the NO_(2) vertical column densities(VCDs)and profiles.The measured NO_(2) differential slant column densities(DSCDs)are compared with the NO_(2) DSCDs simulated by the atmospheric RTM,and the NO_(2) VCDs,the weight factor of NO_(2) in the boundary layer,and the boundary layer height are obtained by the minimization process.The look-up table is established to retrieve NO_(2) VCDs based on MAX-DOAS measurements in Huaibei area,and the results are compared with the data from Copernicus Atmospheric Monitoring Service(CAMS)model.It is found that there are nearly consistent and the correlation coefficient R2 is more than 0.86.The results show that this technology provides a more convenient and accurate retrieval method for the stereoscopic monitoring of atmospheric environment.

Distributed Optimization for Heterogenous Second⁃Order Multi⁃Agent Systems

A continuous⁃time distributed optimization was researched for second⁃order heterogeneous multi⁃agent systems.The aim of this study is to keep the velocities of all agents the same and make the velocities converge to the optimal value to minimize the sum of local cost functions.First,an effective distributed controller which only uses local information was designed.Then,the stability and optimization of the systems were verified.Finally,a simulation case was used to illustrate the analytical results.

A Markov Model for Production and Maintenance Decision

In this paper,we consider a production machine which may fail and it is necessary to repair the machine after each failure and there are two statuses for each repair;in one case,we should replace the machine because of catastrophic failure and in the other case,only small repairs are needed.Times between failures and repair and replace times are random and demands are satisfied by inventory during repairing and replacing the machine;shortage level is limited.We model described system as a Markov chain and develop an algorithm to compute the expected number of transitions among states.

Research on the Method of Implementing Named Data Network Interconnection Based on IP Network

In order to extend the application scope of NDN and realize the transmission of different NDNs across IP networks,a method for interconnecting NDN networks distributed in different areas with IP networks is proposed.Firstly,the NDN data resource is located by means of the DNS mechanism,and the gateway IP address of the NDN network where the data resource is located is found.Then,the transmission between different NDNs across the IP network is implemented based on the tunnel technology.In addition,in order to achieve efficient and fast NDN data forwarding,we have added a small number of NDN service nodes in the IP network,and proposed an adaptive probabilistic forwarding strategy and a link cost function-based forwarding strategy to make NDN data obtaining the cache service provided by the NDN service node as much as possible.The results of analysis and simulation experiments show that,the interconnectionmethod of NDN across IP network proposed is generally effective and feasible,and the link cost function forwarding strategy is better than the adaptive probability forwarding strategy.

Product Form Solution of a Queuing-Inventory System with Lost Sales and Server Vacation

In this study,the authors consider an M/M/1 queuing system with attached inventory under an(s,S)control policy.The server takes multiple vacations whenever the inventory is depleted.It is assumed that the lead time and the vacation time follow exponential distributions.The authors formulate the model as a quasi-birth-and-dearth(QBD)process and derive the stability condition of the system.Then,the stationary distribution in product form for the joint process of the queue length,the inventory level,and the server’s status is obtained.Furthermore,the conditional distributions of the inventory level when the server is on and operational,and when it is off due to a vacation,are derived.Using the stationary distribution,the authors obtain some performance measures of the system.The authors investigate analytically the effect of the server’s vacation on the performance measures.Finally,several numerical examples are presented to investigate the effects of some parameters on the performance measures,the optimal policy,and the optimal cost.

A cloud-edge-device collaborative offloading scheme with heterogeneous tasks and its performance evaluation

How to collaboratively offload tasks between user devices,edge networks(ENs),and cloud data centers is an interesting and challenging research topic.In this paper,we investigate the offoading decision,analytical modeling,and system parameter optimization problem in a collaborative cloud-edge device environment,aiming to trade off different performance measures.According to the differentiated delay requirements of tasks,we classify the tasks into delay-sensitive and delay-tolerant tasks.To meet the delay requirements of delay-sensitive tasks and process as many delay-tolerant tasks as possible,we propose a cloud-edge device collaborative task offoading scheme,in which delay-sensitive and delay-tolerant tasks follow the access threshold policy and the loss policy,respectively.We establish a four-dimensional continuous-time Markov chain as the system model.By using the Gauss-Seidel method,we derive the stationary probability distribution of the system model.Accordingly,we present the blocking rate of delay-sensitive tasks and the average delay of these two types of tasks.Numerical experiments are conducted and analyzed to evaluate the system performance,and numerical simulations are presented to evaluate and validate the effectiveness of the proposed task offloading scheme.Finally,we optimize the access threshold in the EN buffer to obtain the minimum system cost with different proportions of delay-sensitive tasks.

Droop Control for Micro-grid Operations Including Generation Cost and Demand Side Management

A new cost-based droop control method based upon generation cost and demand side cost management of the microgrid is proposed in this paper.At present,many droop control methods have been developed based on either the power rating or the generation cost of the distributed generation(DG)unit,without consideration of the demand side participation in the operation and control.This exclusion might not be appropriate,if different types of consumers are connected in the micro-grid systems.This study proposes a droop control method considering both DG and load operating cost characteristics in order to minimize the generation cost of the micro-grid.

Optimal Secondary Control of Islanded AC Microgrids with Communication Time-delay Based on Multi-agent Deep Reinforcement Learning

In this paper,an optimal secondary control strategy is proposed for islanded AC microgrids considering communi-cation time-delays.The proposed method is designed based on the data-driven principle,which consists of an offine training phase and online application phase.For offline training,each control agent is formulated by a deep neural network(DNN)and trained based on a multi-agent deep reinforcement learning(MA-DRL)framework.A deep deterministic policy gradient(DDPG)algorithm is improved and applied to search for an optimal policy of the secondary control,where a global cost function is developed to evaluate the overall control performance.In addition,the communication time-delay is introduced in the system to enrich training scenarios,which aims to solve the time-delay problem in the secondary control.For the online stage,each controller is deployed in a distributed way which only requires local and neighboring information for each DG.Based on this,the well-trained controllers can provide optimal solutions under load variations,and communication time-delays for online applications.Several case studies are conducted to validate the feasibility and stability of the proposed secondary control.Index Terms-Communication time-delay,global cost function,islanded AC microgrid,multi-agent deep reinforcement learning(MA-DRL),secondary control.

Novel iteration-free blind phase noise estimation for coherent optical OFDM

We propose a novel iteration-free blind phase noise estimation scheme for coherent optical orthogonal frequency division multiplexing （CO-OFDM） systems. In the new algorithm, the cost function is selected as the similar expression with real and imaginary parts as that in the modified constant modulus algorithm, and the new cost function is derived under some assumptions, where it is infinitely approximated by the sine and cosine functions. By means of the analytical formula of the cost function, the initial coarse common phase error can be obtained with only some samples, where the algorithm avoids computational complexity of conventional blind phase noise compensation scheme. In CO-OFDM systems with high-order modulation format （32 quadrature amplitude modulation） and narrow linewidth lasers, it is proved by the simulation results that the nhase noise can be effectively compensated with the proposed blind estimation method.