A multiobjective human evolutionary optimization algorithm for complex engineering problems

Nature·Jan 8

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Researchers are exploring various optimization algorithms to solve complex engineering problems. Several new algorithms have been proposed, including those inspired by natural phenomena such as swarms, particles, and animal behavior. These algorithms aim to improve the efficiency and effectiveness of solving multi-objective engineering design and optimization problems.

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Evolutionary salp swarm algorithm with multi-search strategies and advanced memory mechanism for solving global optimization and complex engineering problems

Nature·Sep 30

Multilevel learning aided coevolutionary particle swarm optimization algorithm for multiobjective fuzzy flexible job shop scheduling problem

Nature·Nov 6

A memorized multi-objective Sinh-Cosh optimizer for solving multi-objective engineering design problems

Nature·Jan 21

Bilevel multiobjective control enhances arterial performance via spatiotemporal optimization of presignalized intersections

Nature·Feb 18

Opposition-based chaotic evolution for optimization

Nature·Jul 2

An efficient multi-objective parrot optimizer for global and engineering optimization problems

Nature·Feb 11

Adaptive dynamic crayfish algorithm with multi-enhanced strategy for global high-dimensional optimization and real-engineering problems

Nature·Mar 27

Multi objective elk herd optimization for efficient structural design

Nature·Apr 6

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