Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…Cloud can accomplish this using efficient scheduling algorithm. This article focuses on task scheduling policy which aims to improve the performance in real-time with the least execution time, network cost and execution cost-effective at the same time. …”
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Research on 3D Obstacle Avoidance Path Planning for Apple Picking Robotic Arm by Xinyan Chen, Chun Lu, Ziliang Guo, Chengkai Yin, Xuanbo Wu, Xiaolan Lv, Qing Chen

“…The experimental results show that compared to RRT* and IRRT*, the average path cost of the optimization algorithm is reduced by 31.565 mm and 14.935 mm and the average search time is reduced by 7.18 s and 4.33 s. …”
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Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

“…To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization（ GA- CO） based on the inverse reliability strategy（ IRS） is proposed（ IRS- GA- CO）. …”
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Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

“…Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. …”
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Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

“…In a data sharing system including transportation network, an electric vehicle (EV) and EV charging stations (EVCSs), it is aimed to determine the most convenient EVCS and the optimal path for reducing the travel, charging and waiting costs. …”
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Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

“…Finally, extensive simulation experiments were conducted to validate the effectiveness of the proposed algorithm. The experimental results demonstrate that, compared with other algorithms, our algorithm significantly improves user response time, optimizes resource utilization, and reduces the total cost.…”
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Distributed Multi-Energy Trading in Energy Internet: An Aggregative Game Approach by Jingwei Hu, Enhui An, Qiuye Sun, Bonan Huang

“…Since each WE only needs to communicate with its neighbors to exchange information, this distributed process reduces communication burden and improves information security. Furthermore, a multi-energy transmission optimization model is established to determine the transmission path of the transmission energy, which can minimize the transmission cost. …”
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Reoptimization Heuristic for the Capacitated Vehicle Routing Problem by Rodrigo Linfati, John Willmer Escobar

“…Next, the local search procedure is executed to improve the solution. A classic optimization is performed on all instances using the original and new customers’ information for later comparison to minimize distance. …”
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Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty by Rongcai Wang, Zhonghua Cheng, Enzhi Dong, Chiming Guo, Liqing Rong

“…A simulated annealing (SA) algorithm is proposed to determine the optimal maintenance cost of the system and the optimal OM threshold under BW. …”
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Manufacturing engineering production line scheduling management technology integrating availability constraints and heuristic rules by Gu Yun

“…In comparing the performance of heuristic algorithms with other algorithms, the optimization rates of heuristic algorithms with SHPSO, QLINSGA-II, and Q-Learning-Sarsa-K-mes-GA were 96.7, 90, 78.6, and 84.7%, respectively. …”
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Advanced day-ahead scheduling of HVAC demand response control using novel strategy of Q-learning, model predictive control, and input convex neural networks by Rahman Heidarykiany, Cristinel Ababei

“…More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. …”
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Joint Allocation of Power and Subcarrier for Low Delay and Stable Power Line Communication by Zhixiong Chen, Zhihui Yang, Zeng Dou

“…Finally, the performance of the algorithm is compared and analyzed by simulation. The results show that the proposed algorithm can reduce the rate fluctuation and improve the system delay performance and deterministic transmission ability under the condition of ensuring the average rate optimization.…”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. …”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…The NC process decision efficiency is improved by 84.6%. On the other hand, the manufacturing cost of the optimal NC process scheme is 16.6% lower.Conclusions The experimental results showed that the proposed approach can generate optimal NC process schemes for parts effectively and automatically, decrease production costs, and shorten the development cycle. …”
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Towards load adaptive routing based on link critical degree for delay-sensitive traffic in IP networks by Yang YANG, Jia-hai YANG, Hui WANG, Chen-xi LI, Yu-ding WANG

“…Firstly, an optimization objective function has been put forward; and then decomposed into several sub-functions by using convex optimization theory; finally, the optimization objective function and sub-functions were transformed into a simple distributed protocol. …”
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Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

“…As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. The effectiveness of the proposed method is analyzed and verified by first using a small-scale example and then investigating a regional multidepot petrol distribution network in Chongqing, China. …”
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Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose. by Jia Liu, Jinglei Zhang, Shaoqi Zhang, Kaiwei Li, Xiang Li, Shuo Zhang, Hang Gu, Zhen Chen, Chao Liu, Nan Zhang, Tong Sun

“…As the precise odor-sensing equipment, the electronic nose integrates multiple advanced and sensitive sensors that can identify wound infections non-invasively and rapidly by analyzing wound characteristic odor. To reduce the cost of sensors and improve or maintain e-nose's performance, efficient optimization of sensor arrays is required. …”
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Integrated Planning for Shared Electric Vehicle System Considering Carbon Emission Reduction by Xiaohui Sun, Yumei Mi, Askar Ahtam, Zhi Zuo

“…By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. …”
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Research on the cooperative offloading strategy of sensory data based on delay and energy constraints by Peiyan YUAN, Saike SHAO, Ran WEI, Junna ZHANG, Xiaoyan ZHAO

“…The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center, which protects data privacy and improves user experience.In the process of cooperative offloading, the transmission of the sensing data and the information exchange among edge servers will consume system resources, resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently, a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally, simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA), the distributed optimization algorithm (DOA), and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.…”
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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…However, the new transformer attention-based approach to MOT has removed the need for complex post-processing steps, such as graph optimization, allowing for end-to-end query tracking across frames. …”
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