Now showing items 11-20 of 218
Evolution strategies with q-Gaussian mutation for dynamic optimization problems.
Evolution strategies with q-Gaussian mutation, which allows the self-adaptation of the mutation distribution shape, is proposed for dynamic optimization problems in this paper. In the proposed method, a real parameter q, ...
Environment identification-based memory scheme for estimation of distribution algorithms in dynamic environments.
In estimation of distribution algorithms (EDAs), the joint probability distribution of high-performance solutions is presented by a probability model. This means that the priority search areas of the solution space are ...
A grid-based evolutionary algorithm for many-objective optimization
Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO). Most current EMO algorithms perform well on problems with two or three objectives, but encounter difficulties in their ...
Genetic algorithms with immigrants schemes for dynamic multicast problems in mobile ad hoc networks.
(IFAC, the International Federation of Automatic Control, 2010)
In this paper, the problem of dynamic quality-of-service (QoS) multicast routing in mobile ad hoc networks is investigated. Lots of interesting works have been done on multicast since it is proved to be a NP-hard problem. ...
QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms.
In this paper, two bio-inspired Quality of Service (QoS) multicast algorithms are proposed in IP over dense wavelength division multiplexing (DWDM) optical Internet. Given a QoS multicast request and the delay interval ...
Particle swarm optimization with composite particles in dynamic environments.
In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address ...
A hybrid evolutionary multiobjective optimization strategy for the dynamic power supply problem in magnesia grain manufacturing.
(World Federation on Soft Computing (WFSC), 2012)
A memetic particle swarm optimization algorithm for multimodal optimization problems.
(Elsevier B.V., 2012)
Recently, multimodal optimization problems (MMOPs) have gained a lot of attention from the evolutionary algorithm (EA) community since many real-world applications are MMOPs and may require EAs to present multiple optimal ...
A directed mutation operator for real coded genetic algorithms.
Developing directed mutation methods has been an interesting research topic to improve the performance of genetic algorithms (GAs) for function optimization. This paper introduces a directed mutation (DM) operator for GAs ...