K-DSA for the multiple traveling salesman problem

Aimed at a multiple traveling salesman problem(MTSP)with multiple depots and closed paths,this paper proposes a k-means clustering donkey and a smuggler algorithm(KDSA).The algorithm first uses the k-means clustering method to divide all cities into several categories based on the center of various samples;the large-scale MTSP is divided into multiple separate traveling salesman problems(TSPs),and the TSP is solved through the DSA.The proposed algorithm adopts a solution strategy of clustering first and then carrying out,which can not only greatly reduce the search space of the algorithm but also make the search space more fully explored so that the optimal solution of the problem can be more quickly obtained.The experimental results from solving several test cases in the TSPLIB database show that compared with other related intelligent algorithms,the K-DSA has good solving performance and computational efficiency in MTSPs of different scales,especially with large-scale MTSP and when the convergence speed is faster;thus,the advantages of this algorithm are more obvious compared to other algorithms.

Traffic Engineering Based on Deep Reinforcement Learning in Hybrid IP/SR Network

Segment Routing(SR)is a new routing paradigm based on source routing and provide traffic engineering(TE)capabilities in IP network.By extending interior gateway protocol(IGP),SR can be easily applied to IP network.However,upgrading current IP network to a full SR one can be costly and difficult.Hybrid IP/SR network will last for some time.Aiming at the low flexibility problem of static TE policies in the current SR networks,this paper proposes a Deep Reinforcement Learning(DRL)based TE scheme.The proposed scheme employs multi-path transmission and use DRL to dynamically adjust the traffic splitting ratio among different paths based on the network traffic distribution.As a result,the network congestion can be mitigated and the performance of the network is improved.Simulation results show that our proposed scheme can improve the throughput of the network by up to 9%than existing schemes.

A Fuzzy Clustering Algorithm Based on Multipath Component Trajectory for Millimeter Wave Radio Channels

Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution properties.In this paper,a fuzzy clustering algorithm based on multipath component(MPC)trajectory is proposed.Firstly,both the distance and velocity similarities of the MPCs in different snapshots are taken into account to track the MPC trajectory,in which the fuzzy scheme and a kernel function are used to calculate the distance and velocity similarities,respectively.Secondly,a fuzzy MPC trajectory clustering algorithm is proposed to cluster the MPCs in multiple snapshots.The MPCs in a snapshot are clustered according to the membership,which is defined as the probability that a MPC belongs to different clusters.Finally,time-varying channels at 28 GHz are simulated to validate the performance of our proposed algorithm.The results show that our proposed algorithm is able to accurately identify the clusters in time-varying channels compared with the existing clustering algorithms.

Bifurcation,Several Equilibria and Multiple Growth Paths in the Solow Model with Endogenous Demographic Transition

In this paper,the endogenous demographic transition function is integrated into the classical Solow model. It is proven that the differential equation which describes the model at least has a nonzero equilibrium. The differential equation has several equilibria when the technological level or the saving rate is not high enough and undergoes bifurcation at some specified parame-ter values. Therefore,the economy described by the model pre-sents multiple growth paths and ＂Malthusian Poverty Trap＂ when the technological level or the saving rate is low.

An Improved Cass-Koopmans Model with Endogenous Fertility under the CES Production Technology

Under the CES production technology, an improved Cass Coopmans model with solvable endogenous fertility is given. We prove that there are multiple growth paths and multiple steady states when CES 0<σ<1 and the technology level is high enough; the growth path and the steady state is unique when σ>1 and the ratio of capital is smaller than a constant. So, the dynamic system which describes the model undergoes a bifurcation when σ=1 . We discuss the economic sense of the main results we give.

Generating test data for both paths coverage and faults detection using genetic algorithms： multi-path case

Generating test data that can expose the faults of the program is an important issue in software testing. Al- though previous methods of covering path can generate test data to traverse target path, the test data generated by these methods are difficult in detecting some low-probabilistic faults that lie on the covered paths. We present a method of generating test data for covering multiple paths to detect faults in this study. First, we transform the problem of cover- ing multiple paths and detecting faults into a multi-objective optimization problem with constraint, and construct a mathe- matical model for it. Then, we give a strategy of solving the model based on a weighted genetic algorithm. Finally, we ap- ply our method to several real-world programs, and compare it with several methods. The experimental results confirm that the proposed method can more efficiently generate test data that not only traverse the target paths but also detect faults lying in them than other methods.

M3FEC:Joint Multiple Description Coding and Forward Error Correction for Interactive Multimedia in Multiple Path Transmission

The best-effort internet has inherent limitations on the end-to-end performance for interactive multimedia communications. This paper presents a multiple description coding （MDC） and forward error correction （FEC） based multiple path transmission schemes for interactive multimedia （M3FEC）, which improves the end users’ experience by maximizing a rate-distortion （R-D） based optimization problem. The proposed model considers both the network diversity and the application’s stringent requirements, and combines the individual merits of the three promising technologies of multiple path overlay routing, MDC and FEC. Extensive numerical analysis and PlanetLab experiments demonstrate that M3FEC successfully combats packet losses, error propagation, and unpredictable network dynamics. This method also significantly increases distortion for interactive multimedia by over 10 dB than traditional IP-layer single path transmission in poor network environments, and outperforms the performance achieved by using MDC or FEC alone.

In-situ EXAFS study on the thermal decomposition of TiH_2

Thermal decomposition behaviors of TiH_2 powder under a flowing helium atmosphere and in a low vacuum condition have been studied using an in situ EXAFS technique.By an EXAFS analysis containing the multiple scattering paths including H atoms,the changes of the hydrogen stoichiometric ratio and the phase transformation sequence are obtained.The results demonstrate that the initial decomposition temperature is dependent on experimental conditions,which occurs,respectively,at about 300 and 400℃ in a low vacuum condition and under a flowing helium atmosphere.During the decomposition process of TiH_2 in a low vacuum condition,the sample experiences a phase change process：δ（TiH_2）→δ（TiH_x）→δ（TiH_1）＋β（TiH_x）→δ（TiH_x）＋β（TiH_x）＋α（Ti）→β（TiH_x）＋α（Ti）→α（Ti）＋β（Ti）.This study offers a way to detect the structural information of hydrogen.A detailed discussion about the decomposition process of TiH_2 is given in this paper.