Now showing items 1-5 of 5
A general framework of multi-population methods with clustering in undetectable dynamic environments.
To solve dynamic optimization problems, multiple population methods are used to enhance the population diversity for an algorithm with the aim of maintaining multiple populations in different subareas in the fitness ...
Differential evolution with a two-stage optimization mechanism for numerical optimization
(IEEE Press, 2016-07-25)
Differential Evolution (DE) is a popular paradigm of evolutionary algorithms, which has been successfully applied to solve different kinds of optimization problems. To design an effective DE, it is necessary to consider ...
A two-phase differential evolution for uniform designs in constrained experimental domains
(IEEE Press, 2017-02-17)
In many real-world engineering applications, a uniform design needs to be conducted in a constrained experimental domain that includes linear/nonlinear and inequality/equality constraints. In general, these constraints ...
Accelerating differential evolution based on a subset-to-subset survivor selection operator
Differential evolution (DE) is one of the most powerful and effective evolutionary algorithms for solving global optimization problems. However, just like all other metaheuristics, DE also has some drawbacks, such as slow ...
A two-layer optimisation management method for the microgrid with electric vehicles
(IEEE Press, 2019-06)
The energy management of the microgrid (MG) with electric vehicles (EVs) is a large-scale optimization problem where the goal should take into account the performance and economic benefits of the power system while meeting ...