Manufacturing engineering production line scheduling management technology integrating availability constraints and heuristic rules by Gu Yun

“…The above results indicate that the proposed model and hybrid algorithm have good performance and effectiveness, which can help improve the quality of engineering production line scheduling management.…”
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An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

“…To improve the prediction accuracy and reduce parameter adjustment time of SVM model, artificial bee colony algorithm (ABC) is employed to optimize internal parameters of SVM model. …”
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Power Allocation for 5G Mobile Multiuser Cooperative Networks by Fagen Yin, Wencai Du

“…To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). …”
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Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

“…Finally, optimization results of a real-world logistics network from Chongqing confirm the applicability of the mathematical model and the designed solution algorithm. …”
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A New Method for Solving Supervised Data Classification Problems by Parvaneh Shabanzadeh, Rubiyah Yusof

“…To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. …”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…MethodsTo address these issues, Multi-Way Improved Whale Optimization Algorithm (MWIWOA) was proposed to optimize the SVM-based prediction model for the internal corrosion rate of long-distance submarine pipelines. …”
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Intelligent Assessment of Personal Credit Risk Based on Machine Learning by Chuansheng Wang, Hang Yu

“…Then, the XGBoost algorithm is used to evaluate the credit risk level of customers, and the traditional Sparrow Search Algorithm is improved by using Tent chaotic mapping, sine and cosine search, reverse learning, and Cauchy mutation strategy to improve the optimization performance of algorithm parameters. …”
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A Bicriteria Approach Identifying Nondominated Portfolios by Javier Pereira, Broderick Crawford, Fernando Paredes, Ricardo Soto

“…In order to improve the former algorithm, a process finding an optimal solution of a monocriteria version of this problem is proposed, which is further used as a first feasible solution aiding to find nondominated solutions more rapidly. …”
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Study on the Speed Ratio Control of Fuzzy PID Control for EM- CVT based on PSO by Zhang Lanchun, Liu Sen, Wang Wei, Shen Hongsheng, Wang Shanfeng

“…The Fuzzy PID speed ratio controller model is set up,whose parameter factors are optimized by the PSO algorithm to realize the optimization of the speed ratio control system. …”
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Power Allocation Technology of Long Time Multi-Star Hopping Beam for LEO Satellite by Ziyi LIU, Xiaoning ZHANG, Zesong FEI

“…LEO satellites have superior development prospects due to their low cost, low latency and small path loss, and are widely used in IoT, B5G and other fields.For the LEO satellite and its coverage area will be in a moving state, a convex optimization-based long-time multi-star beam hopping power allocation algorithm was proposed to maximize the system capacity.Focused on the multi-star hopping beam scenario over a period of time, a system model was developed based on the long-time co-orbital multi-star hopping beam scenario and the long-time heterodyne multi-star hopping beam scenario respectively.The resource allocation algorithm was designed for the two long-time multi-star hopping beams with the weighted objective function as the optimization objective, considered the influence factors of inter-star interference, load balancing and inter-star resource allocation priority, a long-time skipping beam resource allocation algorithm based on convex optimization was proposed.The simulation results showed that the proposed scheme could improve the resource utilization of the system compared with the conventional schemes.…”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…The network structure optimization is mainly achieved by increasing the number of neurons in the hidden layer, and the BP algorithm and gradient descent method are used to iteratively calculate until the model converges, so as to improve the model’s ability to capture the dynamic features of incremental data. …”
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LIGHTWEIGHT OF THE VEHICLE B PILLAR BASED ON SIX SIGMA ROBUST DESIGN UNDER SIDE IMPACT by QIU RuiBin, CHEN Yuan, LEI Fei, YANG ShaoYong, LI YongJun

“…In this paper,by considering uncertainty factors,taking side impact of a car as an example,first of all,an accurate finite element model is established and verified according to relevant crash regulations,then,after building an approximate model and a deterministic optimization model,the optimal solution is obtained by sequential quadratic programming algorithm and the reliability analysis is used,finally the original vehicle B pillar is accomplished lightweight research and improvement by using six sigma robust design method. …”
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Deep Reinforcement Learning for UAV Intelligent Mission Planning by Longfei Yue, Rennong Yang, Ying Zhang, Lixin Yu, Zhuangzhuang Wang

“…Then, the SEAD intelligent planning model based on the proximal policy optimization (PPO) algorithm is established and a general intelligent planning architecture is proposed. …”
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Research on collaborative scheduling strategies of multi-agent agricultural machinery groups by Ziyi Wang, Fan Zhang, Shiji Ma, Hailong Wang, Shunyao Zhang, Xiaozhong Gao

“…Subsequently, the network model is trained to improve its solution capabilities using the policy gradient algorithm (REINFORCE). …”
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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. …”
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基于进化计算的多任务可调机构刚体导引综合 by 杨志刚, 徐礼钜, 林光春, 张均富

“…The method of rigid-body guidance synthesis of adjustable mechanisms for multiple alternation tasks based on evolutionary computation is proposed.The mechanism optimization model of multi-tasks is established,and the global optimization solution will be gained easily by using evolutionary computation.The algorithm of evolutionary computation is improved.A method that can adaptively adjust mutation rate and mutation value according to fitness of individual is proposed,which can effectively improve the evolutionary speed and the accuracy of the solutions.Two numeric examples are given to illustrate the method.…”
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考虑润滑状态的摆动活齿传动多目标优化设计 by 邓志平, 张均富

“…The global optimal solution is obtained based on chaotic particle swarm optimization algorithm. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
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基于遗传-二次规划法的封闭差动人字齿轮传动系统混合优化设计 by 朱增宝, 朱如鹏, 尹敏

“…Using the positive transmission way of modified gear,a mathematical optimization model of the encased differential herringbone gear transmission system is set up by taking the lightest gear weight of this transmission system as the optimization objective.Taking the advantage of its optimization function of genetic algorithm and quadratic programming algorithm in MATLAB toolbox,the compound optimization design is carried out.The research results show that the problem of which the initial value of quadratic programming is difficult to determine is solved well by using the results of the genetic algorithm as the initial value of quadratic programming optimization.Compared with the genetic algorithm or quadratic programming,the optimization design variables of this compound optimization are obviously improved and the gear weight of the system is markedly reduced.The compound optimization method provides a simple and practical solution to obtain precise global optimal solution of the large-scale nonlinear constraint optimization.…”
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