Now showing items 41-50 of 59
Parallel Memetic Structures
Memetic Computing (MC) structures are algorithms composed of heterogeneous operators (memes) for solving optimization problems. In order to address these problems, this study investigates and proposes a simple yet extremely ...
Simplified and yet Turing universal spiking neural P systems with communication on request
(World Scientific, 2018)
Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural ...
Memetic compact differential evolution for cartesian robot control.
This article deals with optimization problems to be solved in the absence of a full power computer device. The goal is to solve a complex optimization problem by using a control card related to portable devices, e.g. for ...
Compact particle swarm optimization
Shuffle Or Update Parallel Differential Evolution for Large-Scale Optimization
This paper proposes a novel algorithm for large-scale optimization problems. The proposed algorithm, namely shuffle or update parallel differential evolution (SOUPDE) is a structured population algorithm characterized by ...
A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms
(Springer Berlin Heidelberg, 2014-11)
The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the ...
A Fast Hypervolume Driven Selection Mechanism for Many-Objective Optimisation Problems
olutions to real-world problems often require the simultaneous optimisation of multiple conflicting objectives. In the presence of four or more objectives, the problem is referred to as a “many-objective optimisation ...