Optimization Model and Algorithm of Empty Pallets Dispatching under the Time-Space Network of Express Shipment by Kang Zhou, Shiwei He, Rui Song, Xiaole Guo, Kaiming Li

“…Therefore, the efficiency of the improved cloud clonal selection operation is higher than genetic algorithm.…”
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Neurogenetic Algorithm for Solving Combinatorial Engineering Problems by M. Jalali Varnamkhasti, Nasruddin Hassan

“…Diversity of the population in a genetic algorithm plays an important role in impeding premature convergence. …”
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Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario by Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG

“…With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed，and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.…”
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Combining Interval Branch and Bound and Stochastic Search by Dhiranuch Bunnag

“…Moreover, the idea of both algorithms suggests a structure for an integrated interval branch and bound and genetic algorithm for constrained problems in which the algorithm is described and tested. …”
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Virtual machine placement algorithm based on cuckoo search by Donghan JIANG, Haitao LIN

“…A cuckoo search algorithm was introduced for virtual machine placement.Firstly,the virtual machine placement program was mapped to the nest,and according to the level,the fitness would be divided into top and bottom nest.Secondly,the bottom nest and the top nest were disturbed by the disturbance function.Finally,by selecting,iterations got the best placement scheme.The algorithm was used for physical integration of cloud data centers,minimizing the number of physical machines placed.The algorithm is simulated by Cloudsim and the results show that the proposed method not only avoids the local optimum,but also has higher performance advantages than the reordered grouping genetic algorithm,the group genetic algorithm,the improved least load algorithm and the improved first fit decrease algorithm.…”
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Spectrum allocation algorithm of elastic optical networks in power distribution system by Biyou ZHAO, Shanhui ZHANG, Jinshuai WANG

“…In order to effectively improve the resource utilization of information transmission network in reality,the spectrum allocation problem in flexible optical network in smart grid environment was analyzed,and a spectrum allocation method was proposed.Combining the advantages of genetic algorithm and ant colony algorithm,the genetic algorithm was used to generate the initial solution.Finally,the optimal solution of the spectrum allocation problem was obtained by the characteristics of positive feedback of ant colony algorithm and efficient convergence.The performance of the optimization algorithm mentioned was verified by software simulation.The proposed algorithm can optimize the use of idle spectrum resources to meet the needs of mass data transmission in distribution network,and improve the reliability of distribution network communication system,which is of great significance to the safe and reliable operation of smart grid.…”
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Multiobjective Location Routing Problem considering Uncertain Data after Disasters by Keliang Chang, Hong Zhou, Guijing Chen, Huiqin Chen

“…The goals are the total costs of the transportation, the satisfaction rates of disaster nodes, and the path transport capacities which are denoted by vehicle velocities. Finally, the genetic algorithm is applied to solve a number of numerical examples, and the results show that the genetic algorithm is very stable and effective for this problem.…”
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Modeling and Simulation of Real Estate Valuation Based on Genetic Neural Network Model by Shuli Shen

“…At the same time, genetic algorithm is used to screen the specific values. …”
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A Dual-Thread Method for Time-Optimal Trajectory Planning in Joint Space Based on Improved NGA by Kaipeng Zhang, Ning Liu, Gao Wang

“…To solve the problem that the time-consuming optimization process of Genetic Algorithm (GA) can erode the expected time-saving brought by the algorithm, time-optimal trajectory planning based on cubic spline was used, after the modification to classical fitness sharing function of NGA, a dual-threaded method utilizing elite strategy characteristic was designed which was based on Niche Genetic Algorithm (NGA) with the fitness sharing technique. …”
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Prediction of Chaotic Time Series Based on BEN-AGA Model by LiYun Su, Fan Yang

“…Aiming at the prediction problem of chaotic time series, this paper proposes a brain emotional network combined with an adaptive genetic algorithm (BEN-AGA) model to predict chaotic time series. …”
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Production scheduling with multi-robot task allocation in a real industry 4.0 setting by Zohreh Shakeri, Khaled Benfriha, Mohsen Varmazyar, Esma Talhi, Anthony Quenehen

“…Based on the data, the Proposed Genetic Algorithm (PGA), with an average Relative Deviation (ARD) of 0.25%, performed approximately 34% better compared to the Basic Genetic Algorithm (BGA), with an average ARD of 0.38%. …”
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TDoA localization-refused area analysis and node placement strategy research by Yue ZHAO, Zan LI, Bing LI, Benjian HAO

“…Regarding the Cramer-Rao lower bound (CRLB) as a localization accuracy metric, the sufficient conditions of the LRA in the time difference of arrival (TDoA)-based localization scenario were discussed and the influence of different factors on the LRA were analyzed.Furthermore, the node placement problem for wireless sensor network (WSN) was investigated by formulating an optimization problem with the objective as average CRLB, which was solved by a genetic algorithm based on LRA pre-judgment.Simulation validates the properties of the CRLB in a single-source scenario and verifies the sufficient condition and the spatial range of the LRA.The simulation also shows that the localization accuracy determined by the proposed algorithm is improved by 33.92% higher than the uniform angle array placement scheme, 13.74% compared to the regional vertex placement scheme, and 9.65% compared to the direct genetic algorithm.…”
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A Hybrid Algorithm of GA + Simplex Method in the WSN Localization by Feng Wang, Cong Wang, ZiZhong Wang, Xue-ying Zhang

“…In the third phase, a hybrid genetic algorithm with the simplex method was proposed to optimize the coordinates of the unknown nodes. …”
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Epistasis-Based Basis Estimation Method for Simplifying the Problem Space of an Evolutionary Search in Binary Representation by Junghwan Lee, Yong-Hyuk Kim

“…The basis search method is based on a genetic algorithm and the fitness evaluation is based on the epistasis, which is an indicator of the complexity of a genetic algorithm. …”
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Research on LRP Integration of E-Commerce Logistics under the Background of Integration of Collection and Distribution by Jiali Li, Zhijie Zhao, Tao Cheng

“…Finally, the effectiveness of the optimized genetic algorithm was verified by Matlab tools and the existing bench-marking data set of the location-routing problem, which provided reference for the planning and decision-making of logistics enterprises.…”
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5D Parameter Estimation of Near-Field Sources Using Hybrid Evolutionary Computational Techniques by Fawad Zaman, Ijaz Mansoor Qureshi

“…The performance of the proposed hybrid scheme is compared not only with the individual responses of genetic algorithm, interior point algorithm, and pattern search, but also with the existing traditional techniques. …”
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Scheduling strategy for science workflow with deadline constraint on multi-cloud by Bing LIN, Wenzhong GUO, Guolong CHEN

“…In view of the deadline-constrained scientific workflow scheduling on multi-cloud,an adaptive discrete particle swarm optimization with genetic algorithm (ADPSOGA) was proposed,which aimed to minimize the execution cost of workflow while meeting its deadline constrains.Firstly,the data transfer cost,the shutdown and boot time of virtual machines,and the bandwidth fluctuations among different cloud providers were considered by this method.Secondly,in order to avoid the premature convergence of traditional particle swarm optimization (PSO),the randomly two-point crossover operator and randomly one-point mutation operator of the genetic algorithm (GA) was introduced.It could effectively improve the diversity of the population in the process of evolution.Finally,a cost-driven strategy for the deadline-constrained workflow was designed.It both considered the data transfer cost and the computing cost.Experimental results show that the ADPSOGA has better performance in terms of deadline and cost reducing in the fluctuant environment.…”
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Enhancing Intelligent Control Strategies for UAVs: A Comparative Analysis of Fuzzy Logic, Fuzzy PID, and GA-Optimized Fuzzy PID Controllers by Nigatu Wanore Madebo

“…The GAFPID controller employs evolutionary computation through a genetic algorithm to optimize parameter tuning, offering superior control performance. …”
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Kinematics Analysis and Simulation of Line-driven Hedge Trimming Manipulator by Xue Zan, Luo Tianhong, Chen Cai

“…The simulation results show that the genetic algorithm has high accuracy and fast solution. …”
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Research and development of intelligent bypass ring net cage and collaborative control technology of multi-source power supply system in flooded environment by Zhanhua Huang, Liang He

“…The improved non-dominated sorting genetic algorithm optimizes multi-source power supply systems. …”
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