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The major disadvantage of this technique is its very slow convergence: this makes it not suitable for many complex optimization problems.
However, for the basic PSO, the updating strategy is mainly aims to learn the global best, and it often suffers premature convergence as well as performs poorly on many complex optimization problems, especially for multimodal problems.
Swarm intelligence (SI) was very popular and widely used in many complex optimization problems which was collective behavior of social systems such as honey bees (bee algorithm, BA) and birds (particle swarm optimization, PSO).
PSO algorithm has been used in many complex optimization tasks, especially in solving the optimization of continuous space [27, 28].
Finally, although it may be time consuming when the number of optimization parameters increases, the proposed algorithm has been shown to be efficient in many complex optimization problems dealing with local minima issues[50].
GA has been successfully adopted in many complex optimization problems and shows its merits over traditional optimization methods, especially when the system under study has multiple local optimal solutions.
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Multi-objective optimization is a realistic model for many complex engineering optimization problems.
Multi-objective formulations are realistic models for many complex engineering optimization problems.
The main structure of the NSGA-II which has been so far applied to many complex multi-objective optimization problems successfully is presented as follows.
The LinReg estimator is faster to compute than the RLR estimator, because LinReg involves a simple linear regression, while RLR requires a complex
Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function.
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many combinatorial optimization
many efficient optimization
many different optimization
many continuous optimization
many objective optimization
many local optimization
many complex screen
many complex market
many dynamic optimization
many multimodal optimization
many global optimization
many fast optimization
many complex postindependence
many complex brain
many practical optimization
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