Research on Logistics Distribution Vehicle Path Optimization Based on Simulated Annealing Algorithm by Li Yang

“…The simulated annealing algorithm is an effective approximation algorithm for solving optimization problems, and the application of this algorithm to path optimization problems can be of practical value in solving problems in urban road traffic and logistics distribution. …”
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Function approximation method based on weights gradient descent in reinforcement learning by Xiaoyan QIN, Yuhan LIU, Yunlong XU, Bin LI

“…Function approximation has gained significant attention in reinforcement learning research as it effectively addresses problems with large-scale, continuous state, and action space.Although the function approximation algorithm based on gradient descent method is one of the most widely used methods in reinforcement learning, it requires careful tuning of the step size parameter as an inappropriate value can lead to slow convergence, unstable convergence, or even divergence.To address these issues, an improvement was made around the temporal-difference (TD) algorithm based on function approximation.The weight update method was enhanced using both the least squares method and gradient descent, resulting in the proposed weights gradient descent (WGD) method.The least squares were used to calculate the weights, combining the ideas of TD and gradient descent to find the error between the weights.And this error was used to directly update the weights.By this method, the weights were updated in a new manner, effectively reducing the consumption of computing resources by the algorithm enhancing other gradient descent-based function approximation algorithms.The WGD method is widely applicable in various gradient descent-based reinforcement learning algorithms.The results show that WGD method can adjust parameters within a wider space, effectively reducing the possibility of algorithm divergence.Additionally, it achieves better performance while improving the convergence speed of the algorithm.…”
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Designing Constrained Trajectory Based on Maximizing Energy Reduction in Large-Scale Wireless Sensor Networks by Jia Xu, Chuan Ping Wang, Hua Dai, Da Qiang Zhang, Jing Jie Yu

“…We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of the Mobile Sink by maximizing the effective average energy reduction . …”
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A Novel Access Control and Energy-Saving Resource Allocation Scheme for D2D Communication in 5G Networks by Ning Du, Kaishi Sun, Changqing Zhou, Xiyuan Ma

“…According to the monotonicity of objective function and constraint conditions, a monotone optimization problem is established, which is solved by reverse polyblock approximation algorithm. In order to reduce the complexity of this algorithm, a solution algorithm based on iterative convex optimization is proposed. …”
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Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs by Shan Wang, Huiling Shan, Chi Zhang, Yuexing Wang, Chunxiang Shi

“…In this paper, we applied the Douglas–Peucker curve approximation algorithm to approximate the CDFs and found that three nonuniformly spaced samples can achieve the same reduction in standard deviation. …”
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Emergency Medical Resources Allocation of Periphery for Epidemic Areas: Based on Infectious Diseases Spatial-Temporal Transmission Path by Xuan Zhao, Benhong Peng, Chaoyu Zheng, Anxia Wan

“…First of all, the epidemic spatial-temporal transmission path (STTP) network describing the geographic spread of disease is obtained using a first-order conditional dependence approximation algorithm in a dynamic Bayesian network (DBN). …”
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Optimal Topology Management for Software-Defined Networks Minimizing Latency and Using Network Slicing by Andrés Viveros, Pablo Adasme, Ali Dehghan Firoozabadi

“…Similarly, our proposed approximation algorithm achieves near-optimal solutions in significantly shorter CPU times, for all the input graph networks, when compared to the proposed exact models which allows for finding the optimal solutions.…”
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Spreading Social Influence with both Positive and Negative Opinions in Online Networks by Jing (Selena) He, Meng Han, Shouling Ji, Tianyu Du, Zhao Li

“…Subsequently, we present a greedy approximation algorithm to address the MPINS selection problem. …”
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A Computable Measure of Algorithmic Probability by Finite Approximations with an Application to Integer Sequences by Fernando Soler-Toscano, Hector Zenil

“…We introduce and justify finite approximations mk that have been used in some applications as an alternative to lossless compression algorithms for approximating algorithmic (Kolmogorov-Chaitin) complexity. …”
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An Approximate Cone Beam Reconstruction Algorithm for Gantry-Tilted CT Using Tangential Filtering by Ming Yan, Cishen Zhang, Hongzhu Liang

“…FDK algorithm is a well-known 3D (three-dimensional) approximate algorithm for CT (computed tomography) image reconstruction and is also known to suffer from considerable artifacts when the scanning cone angle is large. …”
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A Double Inequality for the Trigamma Function and Its Applications by Zhen-Hang Yang, Yu-Ming Chu, Xiao-Jing Tao

“…As applications, some new approximation algorithms for the circumference ratio π and Catalan constant G=∑n=0∞-1n/(2n+1)2 are given. …”
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Researches on the problem of link disjoint paths pair with QoS constraints by ZHANG Pin 1, ZHANG Jian-wu1, LI Le-min 2, WANG Sheng2

“…The problem of link disjoint paths pair with QoS constraints was discussed.Two routing models about link dis-joint optimal paths pair with QoS constraints were constructed.First it proved that the problem of link disjoint paths pair in the undirected graph without end to end QoS constraints counld be converted to the correspond problem in its link split graph,while the problem with end to end QoS constraints counld not be converted.Then it’s proved that both of these questions are NP complete.Finally the approximation algorithms is given and simulation on them is made.…”
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On coding over the spatial-temporal diversity for reliable transmission scheme in low-duty-cycle WSN by Yu-bo YAN, Pan-long YANG, Lei ZHANG, Zheng-lun QIU, Shan-lin HONG

“…A reliable data delivery scheme for low-duty-cycle wireless sensor networks(WSN)was proposed.Using this scheme,the unique spatial-temporal diversity in low-duty-cycle WSN was explored and exploited.Combining with coding schemes,the proposed scheme could achieve higher energy efficiency and lower delivery delay.The coding block allocation problem over multiple paths was formulated.As it was NP-hard,an approximate algorithm to tackle this difficulty was proposed.The impact of network parameters was further analyzed with experimental methods.Extensive simulations also show that,the coding over the spatial-temporal diversity scheme could achieve relatively reliable and low delay delivery with relatively less energy.…”
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Influence of Engagement Algorithm and Structure Parameter on Harmonic Drive by Luo Ji, Sha Chun

“…The results demonstrate that two CEDs and double conjugated phenomenon are found,and the approximate algorithm,the coefficient of radial displacement,the WG have little effect on the CED,CTP,engagement deviation for the CED one,but obviously influence on the CED,CTP,engagement deviation for the CED two.…”
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Study on Single Cycle Production Allocation and Supply Strategy for DCEs Based on the CVaR Criterion by Leiyan Xu, Zhiqing Meng, Gengui Zhou, Yunzhi Mu, Minchao Zheng

“…Subsequently, an approximate algorithm for solving the optimal total production amount is presented. …”
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Hyperbolic Metric Spaces and Stochastic Embeddings by Chris Gartland

“…Stochastic embeddings of finite metric spaces into graph-theoretic trees have proven to be a vital tool for constructing approximation algorithms in theoretical computer science. In the present work, we build out some of the basic theory of stochastic embeddings in the infinite setting with an aim toward applications to Lipschitz free space theory. …”
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Suppressing the Endogenous Negative Influence Through Node Intervention in Social Networks by Satoshi Furutani, Tatsuhiro Aoshima, Toshiki Shibahara, Mitsuaki Akiyama, Masaki Aida

“…We prove that this problem is NP-hard and propose approximation algorithms to identify optimal intervention nodes that minimize the negative influence. …”
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