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Evolutionary Computation, Metaheuristics, Nature-Inspired Algorithms, and Symmetry

Computational intelligence is an important branch of artificial intelligence. Nowadays, evolutionary computation as a part of computational intelligence is widely used to solve various numerical problems and real-world engineering problems. Its application and development bring a great contribution...

Whakaahuatanga katoa

I tiakina i:
Hōputu: Online
Reo:Ingarihi
I whakaputaina: MDPI - Multidisciplinary Digital Publishing Institute 2026
Ngā marau:
Electrical load forecasting
Machine learning
Extreme learning machine
Dynamic backward learning
Madness factor operator
Multiobjective vehicle routing problem with time windows
Deep reinforcement learning
Evolutionary multi-task optimization
Knowledge transfer
NSGA-II
DSSAT model
Local search
Optimization of irrigation and fertilization
Evolutionary algorithms
Tree genetic programming
Linear genetic programming
Imperative programming
Many-objective optimization
Penalty-based boundary intersection
Comprehensive adaptive penalty scheme
NSGA-III
Metasurface
Polarization conversion
Ultrawideband
Topology optimization
Shape optimization
Genetic algorithm
Artificial intelligence
ANFIS
Brent oil
Metaheuristic optimization
Methodological symmetry
Time-series analysis
Swarm intelligence
Optimization algorithms
Nature-inspired algorithms
Cloud–edge–end collaborative network
Task offloading
Method symmetry
Particle swarm optimization
Metaheuristic algorithm
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Urunga tuihono:ONIX_20260416T142754_9783725858330_33
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Whakarāpopototanga:Computational intelligence is an important branch of artificial intelligence. Nowadays, evolutionary computation as a part of computational intelligence is widely used to solve various numerical problems and real-world engineering problems. Its application and development bring a great contribution to the optimization domain. Thus, it is of great interest to investigate the role and significance of evolutionary computation, metaheuristics, and nature-inspired algorithms in optimizing distinctive problems. This Reprint aims to bring together both experts and newcomers from either academia or industry to discuss new and existing issues concerning evolutionary computation and optimization. The research topics include cloud-edge-end collaborative task offloading, time-series analysis of brent oil price, high-efficiency and ultrawideband polarization conversion metasurface, many-objective optimization, imperative programs, maize water and fertilizer irrigation simulation, multi-objective vehicle routing problems with time windows, and short-term electrical load forecasting. Various optimization algorithms such as particle swarm optimization, genetic programming, and non-dominated sorting genetic algorithm are successfully applied to these topics and show superior performance. These algorithms not only greatly promote the development of evolutionary computation and community, but also effectively address some existing limitation of optimization problems.

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