A robust multi-objective multi-priodic planning approach to the problem of locating the allocation of organ transplant centers under conditions of uncertainty by Elham Nejati, Mahdi Yousefi Nejad Attari, Asgar Hajibadali

“…On the other hand, due to the rapid growth of the demand for organ transplantation and the lack of resources, the patient's waiting time to complete the transplantation process plays a vital role in the organ transplantation system.Methodology: This study presents a robust bi-objective mathematical model for the location problem of allocating organ transplant centers under uncertainty, which includes the total costs of the organ transplant system as well as the average patient waiting time for organ transplantation, which follows a G/G/m queuing system.Findings: To solve this model, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been used. Finally, the applicability of this model and the efficiency of the mentioned algorithm compared to the defined indicators have been shown through numerical experiments.Originality/Value: Since each organ can spend a certain amount of time outside the body and there is a possibility of corruption or a decrease in the quality of the transplant, the time between the organ leaving the body and the completion of the transplant operation plays an essential role in the transplant system.…”
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A Group-Based Signal Timing Optimization Model Considering Safety for Signalized Intersections with Mixed Traffic Flows by Fen Wang, Keshuang Tang, Keping Li, Zhigang Liu, Lin Zhu

“…Then, the multiobjective optimization issue was formulated as a nonlinear program and solved by a Nondominated Sorting Genetic Algorithm. A numerical study was performed to demonstrate the applicability and performance of the proposed model. …”
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An interval Type-2 fuzzy Fractional-Order PD-PI controller for frequency stabilization of islanded microgrids optimized with CO algorithm by Siavash Shirali, Saeed Zolfaghari Moghaddam, Mortaza Aliasghary

“…Additionally, optimizing the controller parameters in dynamic systems is another critical issue, where traditional algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and sine cosine algorithm (SCA) often struggle with premature convergence and suboptimal solutions. …”
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Bearing Fault Diagnosis Using a Support Vector Machine Optimized by an Improved Ant Lion Optimizer by Dalian Yang, Jingjing Miao, Fanyu Zhang, Jie Tao, Guangbin Wang, Yiping Shen

“…In these experiments, the two most important parameters for the support vector machine—the Gaussian kernel parameter σ and the penalty factor C—were optimized using the EALO algorithm, ALO algorithm, genetic algorithm (GA), and particle swarm optimization (PSO) algorithm. …”
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Dynamic Service Placement in Edge Computing: A Comparative Evaluation of Nature-Inspired Algorithms by Aqeel H. Kazmi, Alessandro Staffolani, Tianhao Zhang, Christian Cabrera, Siobhan Clarke

“…In our analysis, the Genetic Algorithm shows superior performance in achieving lower average distance and the average number of servers selected. …”
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Study on Global Parameters Optimization of Dual-Drive Powertrain System of Pure Electric Vehicle Based on Multiple Condition Computer Simulation by Yong Wang, Hongguo Cai, Yinghua Liao, Jun Gao

“…As for such differences, this paper adopts intelligent algorithm to design the parameters of the transmission system and introduces the genetic algorithm into the optimization design of parameters to obtain the optimal vital parameters of the power transmission system based on computer simulation. …”
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Toward Pleomorphic Reconfigurable Robots for Optimum Coverage by S. M. Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, Mohan R. Elara, Selva kumaran

“…The optimum size for reconfiguration is determined by the genetic algorithm based on the arrangement of the environment. …”
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Intelligent Time-Domain Parameters Matching for Shock Response Spectrum and Its Experimental Validation in Active Vibration Control Systems by Jinxin Liu, Liangdong Yang, Xingwu Zhang, Ruqiang Yan, Xuefeng Chen

“…A variable-weight method has been introduced to combine the effects of hundreds objective functions so that the optimization problem can be solved by using the genetic algorithm. The frequency response function of the shaking system has been taken into consideration in the calculation of the objective function, so the synthesized TSW can be applied directly to the SRS test. …”
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Application of Energy Saving and Environmental Protection Materials in Architectural Design by Zixiang Yan

“…Building energy saving has become a major trend of global development, and then the optimal design of reinforcement selection for reinforced concrete beams based on a multiobjective genetic algorithm is discussed. The area of reinforcement required for the member control section is obtained according to the structural analysis program, the main purpose of reinforcement selection is to select safe, economical, and reasonable reinforcement on the premise of meeting the provisions of the code and the requirements of reinforcement structure. …”
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Two-Stage Optimization Method for the Bearing Layout of Isolated Structure by Yu Dang, GenXiong Zhao, HongTu Tian, Guobao Li

“…The isolation devices are simplified as a kind of lead-rubber bearing. The genetic algorithm is used to find the optimal parameters of the isolated layer. …”
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A Balanced Strategy for the FFBS Operator Integrating Dispatch Area, Route, and Depot Based on Multimodel Technologies by Qingfeng Zhou, Jun Zhou, Chun Janice Wong

“…We proposed a feasible framework including bike trip network segmentation, mean-shift clustering based on the point position, VRP model, genetic algorithm, and TOPSIS evaluation method. The effectiveness and superiority of the division of the dispatch area are verified. …”
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Encrypted and obfuscation WebShell detection for high-speed network traffic by Yihuai CAO, Wei CHEN, Fan ZHANG, Lifa WU

“…With the gradual development of traffic encryption and text obfuscation technologies, it is increasingly difficult to prevent complicated and malicious WebShell attack events in production environment using traditional detection methods based on text content and network flow features, especially for adversarial samples, variant samples and 0Day vulnerability samples.With the established network traffic collection environment, DPDK technology was used to capture network traffic in the high-speed network environment, and a dataset was marked with label.The dataset consisted of more than 24,000 normal traffic and more than 10,000 malicious WebShell traffic under different platforms, different languages, different tools, different encryption and obfuscation methods.Then Asynchronous traffic analysis system framework and lightweight log collection components were used to efficiently parse raw traffic.Expert knowledge was integrated to analyze HTTP data packets during the communication process of several popular WebShell management tools, and the effective feature set for encrypted and obfuscation WebShell was obtained.Support Vector Machine (SVM) algorithm was used to realize offline training and online detection of complicated WebShell malicious traffic based on the effective feature set.Meanwhile, improving the parameter search method with the genetic algorithm promoted the model training efficiency furthermore.The experimental results showed that the detection efficiency can be guaranteed based on the self-built WebShell attack traffic dataset.Besides, the detection model has a precision rate of 97.21% and a recall rate of 98.01%, and it performed well in the comparative experiments of adversarial WebShell attacks.It can be concluded from the results that the proposed method can significantly reduce the risk of WebShell attack, effectively supplement the existing security monitoring system, and be applied in real network environments.…”
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On the Search for Supersingular Elliptic Curves and Their Applications by Ismel Martinez-Diaz, Rashad Ali, Muhammad Kamran Jamil

“…As our main result, we define for the first time an objective function to measure the supersingularity in ordinary curves, and we apply local search and a genetic algorithm using that function. The study not only finds these supersingular elliptic curves but also investigates possible uses for them. …”
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Parametric Evaluation of Simultaneous Effects of Damaged Zone Parameters and Rock Strength Properties on GRC by Ali Ghorbani, Hadi Hasanzadehshooiili, Amin Eslami

“…Besides, effects of intermediate principal stress and the exponential decaying dilation parameter are taken into account thanks to adoption of the unified strength criterion (USC) as the material strength criteria. To do so, genetic algorithm (GA) via the method of evolutionary polynomial regression (EPR) is used to find a relationship between a number of 19 affecting parameters on the GRC as the input, and the internal support pressure as the target of prediction. …”
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Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer by Abdullrahman A. Al-Shamma’a, Hassan M. Hussein Farh, Abdullah M. Noman, Abdullah M. Al-Shaalan, Abdulaziz Alkuhayli

“…The efficacy of HHO is investigated, and its performance was compared with seven metaheuristic techniques, grasshopper optimization algorithm (GOA), cuckoo search optimizer (CSO), genetic algorithm (GA), Big Bang–Big Crunch (BBBC), coyote optimizer, crow search, and butterfly optimization algorithm (BOA), to attain the HRE microgrid optimal sizing based on annualized system cost (ASC) reduction. …”
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Design and Development of Polymer-Based Optical Fiber Sensor for GAIT Analysis by Mamidipaka Hema, Jami Venkata Suman, Boddepalli Kiran Kumar, Adisu Haile

“…Using the sensor data, gait recognition is performed using genetic algorithm (GA) and particle swarm optimization (PSO) technique. …”
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Crashworthiness Design and Multiobjective Optimization for Hexagon Honeycomb Structure with Functionally Graded Thickness by Ruixian Qin, Junxian Zhou, Bingzhi Chen

“…In addition, three surrogate models, including radial basis function (RBF), response surface method (RSM), and kriging (KRG), are compared in the accuracy of predicting SEA and PCF and capacity for optimization design of FGT honeycomb structure; the Nondominated Sorting Genetic Algorithm (NSGA-II) is applied to obtain the Pareto optimal solutions for the maximum thickness, minimum thickness, and thickness variation gradient exponent of a honeycomb wall. …”
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Parameter Acquisition Study of Mining-Induced Surface Subsidence Probability Integral Method Based on RF-AGA-ENN Model by Jinman Zhang, Liangji Xu, Jiewei Li, Yueguan Yan, Ruirui Xu

“…To obtain more accurate PIM parameters in the absence of observational data, we propose a combined machine learning model (RF-AGA-ENN)—random forest (RF) extracts the best combination of features as the input layer of Elman neural network (ENN); ant colony algorithm (ACO) and genetic algorithm (GA) are combined (called AGA) for the weights and thresholds of ENN optimization. …”
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A GA-Based BP Artificial Neural Network for Estimating Monthly Surface Air Temperature of the Antarctic during 1960–2019 by Miao Fang

“…This study proposed a backpropagation artificial neural network (BPANN) optimized by a genetic algorithm (GA) to estimate the monthly SAT fields of the Antarctic continent for the period 1960–2019. …”
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An Iterative Heuristic Optimization Method for the Optimum Sizing of Battery Energy Storage System to Augment the Dispatchability of Wind Generators by Shubham Kashyap, Tirthadip Ghose

“…Validation using Genetic Algorithm (GA) is done by comparing the costs of BESSs, emphasizing the suitability of the proposed technique.…”
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