An effective memetic differential evolution algorithm based on chaotic local search
D Jia, G Zheng, MK Khan - Information Sciences, 2011 - Elsevier
This paper proposes an effective memetic differential evolution (DE) algorithm, or DECLS,
that utilizes a chaotic local search (CLS) with a 'shrinking'strategy. The CLS helps to improve …
that utilizes a chaotic local search (CLS) with a 'shrinking'strategy. The CLS helps to improve …
[HTML][HTML] Enhanced opposition-based differential evolution for solving high-dimensional continuous optimization problems
H Wang, Z Wu, S Rahnamayan - Soft Computing, 2011 - Springer
This paper presents a novel algorithm based on generalized opposition-based learning
(GOBL) to improve the performance of differential evolution (DE) to solve high-dimensional …
(GOBL) to improve the performance of differential evolution (DE) to solve high-dimensional …
[HTML][HTML] Self-adaptive differential evolution algorithm using population size reduction and three strategies
Many real-world optimization problems are large-scale in nature. In order to solve these
problems, an optimization algorithm is required that is able to apply a global search …
problems, an optimization algorithm is required that is able to apply a global search …
A comprehensive comparison of large scale global optimizers
Abstract Large Scale Global Optimization is one of the most active research lines in
evolutionary and metaheuristic algorithms. In the last five years, several conference …
evolutionary and metaheuristic algorithms. In the last five years, several conference …
Parallel differential evolution with self-adapting control parameters and generalized opposition-based learning for solving high-dimensional optimization problems
H Wang, S Rahnamayan, Z Wu - Journal of Parallel and Distributed …, 2013 - Elsevier
Solving high-dimensional global optimization problems is a time-consuming task because of
the high complexity of the problems. To reduce the computational time for high-dimensional …
the high complexity of the problems. To reduce the computational time for high-dimensional …
[HTML][HTML] A MOS-based dynamic memetic differential evolution algorithm for continuous optimization: a scalability test
Continuous optimization is one of the areas with more activity in the field of heuristic
optimization. Many algorithms have been proposed and compared on several benchmarks …
optimization. Many algorithms have been proposed and compared on several benchmarks …
An enhanced differential evolution algorithm with a new oppositional-mutual learning strategy
Global optimization has been a hot research topic in various engineering applications,
where differential evolution (DE) is one of the most popular approaches. Actually, it is …
where differential evolution (DE) is one of the most popular approaches. Actually, it is …
Multiple offspring sampling in large scale global optimization
Continuous optimization is one of the most active research lines in evolutionary and
metaheuristic algorithms. Through CEC 2005 to CEC 2011 competitions, many different …
metaheuristic algorithms. Through CEC 2005 to CEC 2011 competitions, many different …
Habcde: a hybrid evolutionary algorithm based on artificial bee colony algorithm and differential evolution
W Xiang, S Ma, M An - Applied Mathematics and Computation, 2014 - Elsevier
Artificial bee colony (ABC) algorithm is one of the most recent swarm intelligence based
algorithms which has been proven to be competitive with other population based algorithms …
algorithms which has been proven to be competitive with other population based algorithms …
Machine learning based multiscale calibration of mesoscopic constitutive models for composite materials: application to brain white matter
A modular pipeline for improving the constitutive modelling of composite materials is
proposed. The method is leveraged here for the development of subject-specific spatially …
proposed. The method is leveraged here for the development of subject-specific spatially …