A T-cell algorithm for solving dynamic economic power dispatch problems by Victoria Aragón, Carlos A. Coello Coello, Mario A. Leguizamón

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A Knowledge Sharing and Individually Guided Evolutionary Algorithm for Multi-Task Optimization Problems by Xiaoling Wang, Qi Kang, Mengchu Zhou, Zheng Fan, Aiiad Albeshri

“…Multi-task optimization (MTO) is a novel emerging evolutionary computation paradigm. It focuses on solving multiple optimization tasks concurrently while improving optimization performance by utilizing similarities among tasks and historical optimization knowledge. …”
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Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios by Ryoji Tanabe, Hisao Ishibuchi, Akira Oyama

“…Recently, a large number of multi-objective evolutionary algorithms (MOEAs) for many-objective optimization problems have been proposed in the evolutionary computation community. However, an exhaustive benchmarking study has never been performed. …”
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Performance Comparison Of Evolutionary Algorithms For Image Clustering by P. Civicioglu, U. H. Atasever, C. Ozkan, E. Besdok, A. E. Karkinli, A. Kesikoglu

“…Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. …”
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Multi-Layer Blockchain-Based Security Architecture for Internet of Things by Houshyar Honar Pajooh, Mohammad Rashid, Fakhrul Alam, Serge Demidenko

“…The K-unknown clusters are defined within the IoT network by applying techniques that utillize a hybrid Evolutionary Computation Algorithm while using Simulated Annealing and Genetic Algorithms. …”
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Decentralized Multi-Layered Architecture to Strengthen the Security in the Internet of Things Environment Using Blockchain Technology by Ahmed Alhusayni, Vijey Thayananthan, Aiiad Albeshri, Saleh Alghamdi

“…IoT networks define unknown clusters with applications that utilize the evolutionary computation method coupled with anatomy simulation and genetic methodologies. …”
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Improved SparseEA for sparse large-scale multi-objective optimization problems by Yajie Zhang, Ye Tian, Xingyi Zhang

“…In recent years, sparse LSMOPs have attracted increasing attentions in the evolutionary computation community. However, all the recently tailored algorithms for sparse LSMOPs put the sparsity detection and maintenance in the first place, where the nonzero variables can hardly be optimized sufficiently within a limited budget of function evaluations. …”
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An opposition theory enabled moth flame optimizer for strategic bidding in uniform spot energy market by Pooja Jain, Akash Saxena

“…First OB-MFO algorithm is tested on 22 benchmark and Congress on Evolutionary Computation (CEC-2017) functions, then it is applied to bidding problem of standard IEEE-14 bus (Test Case-1) and 7 generator power system (Test Case-2). …”
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An Efficient Large-Scale Sensor Deployment Using a Parallel Genetic Algorithm Based on CUDA by Jae-Hyun Seo, Yourim Yoon, Yong-Hyuk Kim

“…We have employed evolutionary computation to solve the optimization problem of sensor deployment in battlefield environments. …”
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Forecasting Stock Exchange Data using Group Method of Data Handling Neural Network Approach by Marzieh Faridi Masouleh, Ahmad Bagheri

“…Nature-inspired problem-solving approaches include meta-heuristic methods that are focused on evolutionary computation and swarm intelligence. One of these problems significantly impacting information is forecasting exchange index, which is a serious concern with the growth and decline of stock as there are many reports on loss of financial resources or profitability. …”
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Using the Jensen-Shannon, Density Power, and Itakura-Saito Divergences to Implement an Evolutionary-Based Global Localization Filter for Mobile Robots by Fernando Martin, Juan Carballeira, Luis Moreno, Santiago Garrido, Pavel Gonzalez

“…This task is addressed applying evolutionary computation concepts (Differential Evolution). …”
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Optimizing boiler combustion parameters based on evolution teaching-learning-based optimization algorithm for reducing NO_x emission concentration by Yunpeng Ma, Shilin Liu, Shan Gao, Chenheng Xu, Wenbo Guo

“…To verify the effectiveness of ETLBO, 20 IEEE congress on Evolutionary Computation benchmark test functions are applied to test its convergence speed and convergence accuracy. …”
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Two reference vector sets based evolutionary algorithm for many‐objective optimization by Cifeng Qin, Fei Ming, Wenyin Gong

“…Abstract Solving many‐objective optimization problems (MaOPs) by means of evolutionary algorithms obtains considerable attention in the community of evolutionary computation. However, it is a difficult task to effectively handle MaOPs with both regular and irregular Pareto front (PF) shapes. …”
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Multi-Scale Memetic Image Registration by Cătălina Lucia Cocianu, Cristian Răzvan Uscatu

“…The proposed method combines bio-inspired and evolutionary computation techniques with clustered search and implements a procedure specially tailored to address the premature convergence issue in various scaled representations. …”
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A Self-adaptive Coevolutionary Algorithm by Hevia Fajardo, Mario, Hemberg, Erik, Toutouh, Jamal, O'Reilly, Una-May, Lehre, Per Kristian

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Evolving tactical plans for strategy games using automated red teaming by Hingston, P., Decraene, James, Low, Malcolm Yoke Hean

“…In typical ART experiments, agent-based simulations of military scenarios are repeatedly and automatically generated, varied and executed. Evolutionary Computation techniques are utilized to drive the exploration of simulation models to exhibit pre-specified and desired behaviour (e.g., evolve the adversary to best defeat defensive tactics). …”
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Evolutionary multitasking via explicit autoencoding by Feng, Liang, Zhou, Lei, Zhong, Jinghui, Gupta, Abhishek, Ong, Yew-Soon, Tan, Kay-Chen, Qin, A. K.

“…Evolutionary multitasking (EMT) is an emerging research topic in the field of evolutionary computation. In contrast to the traditional single-task evolutionary search, EMT conducts evolutionary search on multiple tasks simultaneously. …”
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MemeWar’s map editor with terrain evolver integration by Ang, Edwin Yew Leng

“…Terrain Evolver is designed for user to generate terrains with minimum technical knowledge through the application of Evolutionary Computation. Through a number of iterations and a pool of initially randomly generated terrain solutions, evolution process will aid users to converge to a design suitable to their needs through crossover and mutation. …”
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Study of adaptive frequency notched radar waveform by Guo, Yitong

“…PSO (Particle Swarm Optimization), as the stochastic evolutionary computation optimization technique is also introduced in this report. …”
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Augmented feedforward and feedback control of a twin rotor system using real-coded MOGA by Toha, Siti Fauziah, Tokhi, M. O.

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