Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…The average optimal value is 6.83745935e-001. After 789 iterations, the genetic algorithm obtains the optimal value of 6.83921100e-001, and the average optimal value is 6.84410765e-001. …”
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A Collaborative Transit Signal Priority Method Considering Gaming among Traffic Participants by Bing Wu, Haishan Wang, Yanli Wang, Ben Zhai, TanXing Xue

“…The core of Co-TSP is a two-objective optimization problem which takes the expected delays of buses and the average delays of nontransit vehicles as the objectives. …”
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Caching strategy based on transmission delay for D2D cooperative edge caching system by Yan CAI, Fan WU, Hongbo ZHU

“…To meet the requirements of 5G system with low delay and high reliability, for a single-caching D2D cooperative edge caching system, an optimization of the caching strategy based on transmission delay was proposed.The dynamic distributions of requesting users and idle users were modeled as the independent homogeneous poisson point process (HPPP) utilizing the stochastic geometry theory.Comprehensively considering the content popularity, user location information, device transmission power and interference, the relationship between the average transmission delay of user and the cache probability distribution was derived.Taking the average transmission delay as the objective function, the optimization problem was established, and a low complexity iterative algorithm was proposed to obtain the cache strategy with sub-optimal average transmission delay.Simulation results demonstrate that the proposed optimization cache strategy is superior to several common cache strategies in terms of transmission delay.…”
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Dynamic QoS-aware intelligent edge computing resource management algorithm for body area networks by MU Siqi, WEN Shuo, LU Yang, AI Bo

“…A dynamic QoS-aware stochastic optimization problem on computation offloading decisions and edge computing resource allocation was studied. …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…To this end, it is necessary to model the total training time minimization problem, optimize the quantization series and bandwidth allocation, and design an alternate optimization algorithm to solve this problem. 2. …”
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Cellular-free RAN slicing resource allocation algorithm based on multi-timescale collaboration by XIA Weiwei, WANG Boye, XIA Yaxing, MIAO Weiwei, WANG Dayang, JING Dongsheng, YAN Feng, SHEN Lianfeng

“…To address the issue of ensuring user quality of service in resource allocation for 6G cell-free radio access network slicing under dynamic service variations, a resource allocation algorithm based on multi-timescale collaborative optimization was proposed. Firstly, the large time-scale slice-oriented resource allocation problem was formulated as a mean square error-minimization-based resource demand prediction model with average user latency constraints, and the accurate allocation of slice resources was achieved by a long and short-term memory time-series prediction network. …”
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Joint user association and power control scheme based on energy consumption and QoE in heterogeneous network by Shiyu JI, Liangrui TANG, Shuxian LI, Shimo DU

“…Based on multi-objective optimization,a joint user association and power control scheme was proposed in heterogeneous network environment,aiming to reduce the system energy consumption and improve user quality of experience.The scheme took the system energy consumption minimum and the average user quality of experience maximum as objective functions and translated the joint user association and power control to multi-objective problem.Then,the differential evolution optimization algorithm and TOPSIS algorithm was used to solve the multi-objective problem.Simulation results show that the scheme can efficiently reduce the system energy consumption and improve the user quality of experience.…”
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A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process by Tolga Kudret Karaca, Funda Samanlioglu, Ayca Altay

“…The stochastic skiving stock problem (SSP), a relatively new combinatorial optimization problem, is considered in this paper. …”
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Application of improved ant-lion algorithm for power systems. by Wenjing Wang, Renjun Zhou

“…An improved ant-lion algorithm is proposed to solve the load allocation problem to improve the efficiency of load allocation in the power system. …”
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Indoor Visible Light 3D Localization System Based on Black Wing Kite Algorithm by Jiahui Wang, Xiangqing Wang, Chaochuan Jia, Cui Yang

“…The indoor visible light localization problem can be transformed into a problem of solving the optimal coordinates of the receiver globally. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

“…In this article, we present a network model of the multi-community delay-tolerant networks and formulate a dynamic quota-controlled routing problem of minimizing the average number of copies of a message that satisfies the required delivery probability under the given time-to-live of the message as a nonlinear optimization problem. …”
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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Samar Hussni Anbarkhan, Laith Abualigah

“…It is challenging to find the best PEMFC parameters because the model is complex and the problem is nonlinear; not all optimization algorithms can solve this problem. …”
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A LEO Satellite Handover Strategy Based on Graph and Multiobjective Multiagent Path Finding by Zhiyun Jiang, Wei Li, Xiangtong Wang, Binbin Liang

“…Therefore, the handover strategy problem is transformed into a path planning problem. …”
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Adaptive SDN switch migration mechanism based on coalitional game by Lan YAO, Julong LAN

“…The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.…”
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Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

“…It is shown that phasic policy gradient achieves an average of 9% better reward compared to proximal policy optimization and the total time decreases by 7–10% when EV owner cost is considered.…”
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Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints by Tingting Qu

“…With the transformation of manufacturing towards intelligence and flexibility, the workshop scheduling problem, as a typical combinatorial optimization problem, is facing increasingly complex constraints and requirements. …”
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Energy-Saving Control Method of Building Central Air Conditioning Based on Genetic Algorithm by Lihui Wang

“…On the one hand, the feasibility of the optimized algorithm to solve the energy-saving problem of central air conditioning was proved through the optimization of genetic algorithm. …”
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Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

“…Thus, we redefine the problem of multi-step-ahead prediction as a two-objective optimization problem: on one hand, we aim to minimize the number of nonpredictable points and the average error among the predictable ones. …”
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Dynamics of a Flat Rigid Body on a Horizontal Plane by A. I. Munitsyn, V. E. Tsoy

“…The results of the conducted research allowed us to determine the optimal values of the problem parameters in order to reach the required value of the average velocity of a solid body. …”
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Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. …”
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