5,989 research outputs found
Genetic algorithms with elitism-based immigrants for dynamic load balanced clustering problem in mobile ad hoc networks
This article is posted here with permission of IEEE - Copyright @ 2011 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1 and Grant EP/E060722/2
A Tight Convex Upper Bound on the Likelihood of a Finite Mixture
The likelihood function of a finite mixture model is a non-convex function
with multiple local maxima and commonly used iterative algorithms such as EM
will converge to different solutions depending on initial conditions. In this
paper we ask: is it possible to assess how far we are from the global maximum
of the likelihood? Since the likelihood of a finite mixture model can grow
unboundedly by centering a Gaussian on a single datapoint and shrinking the
covariance, we constrain the problem by assuming that the parameters of the
individual models are members of a large discrete set (e.g. estimating a
mixture of two Gaussians where the means and variances of both Gaussians are
members of a set of a million possible means and variances). For this setting
we show that a simple upper bound on the likelihood can be computed using
convex optimization and we analyze conditions under which the bound is
guaranteed to be tight. This bound can then be used to assess the quality of
solutions found by EM (where the final result is projected on the discrete set)
or any other mixture estimation algorithm. For any dataset our method allows us
to find a finite mixture model together with a dataset-specific bound on how
far the likelihood of this mixture is from the global optimum of the likelihoodComment: icpr 201
RNAiFold2T: Constraint Programming design of thermo-IRES switches
Motivation: RNA thermometers (RNATs) are cis-regulatory ele- ments that
change secondary structure upon temperature shift. Often involved in the
regulation of heat shock, cold shock and virulence genes, RNATs constitute an
interesting potential resource in synthetic biology, where engineered RNATs
could prove to be useful tools in biosensors and conditional gene regulation.
Results: Solving the 2-temperature inverse folding problem is critical for RNAT
engineering. Here we introduce RNAiFold2T, the first Constraint Programming
(CP) and Large Neighborhood Search (LNS) algorithms to solve this problem.
Benchmarking tests of RNAiFold2T against existent programs (adaptive walk and
genetic algorithm) inverse folding show that our software generates two orders
of magnitude more solutions, thus allow- ing ample exploration of the space of
solutions. Subsequently, solutions can be prioritized by computing various
measures, including probability of target structure in the ensemble, melting
temperature, etc. Using this strategy, we rationally designed two thermosensor
internal ribosome entry site (thermo-IRES) elements, whose normalized
cap-independent transla- tion efficiency is approximately 50% greater at 42?C
than 30?C, when tested in reticulocyte lysates. Translation efficiency is lower
than that of the wild-type IRES element, which on the other hand is fully
resistant to temperature shift-up. This appears to be the first purely
computational design of functional RNA thermoswitches, and certainly the first
purely computational design of functional thermo-IRES elements. Availability:
RNAiFold2T is publicly available as as part of the new re- lease RNAiFold3.0 at
https://github.com/clotelab/RNAiFold and http:
//bioinformatics.bc.edu/clotelab/RNAiFold, which latter has a web server as
well. The software is written in C++ and uses OR-Tools CP search engine.Comment: 24 pages, 5 figures, Intelligent Systems for Molecular Biology (ISMB
2016), to appear in journal Bioinformatics 201
- …