Guest editorial: Memetic computing in the presence of uncertainties

Copyright @ Springer-Verlag 2010.The Guest Editors acknowledge the research support by the Academy of Finland, Akatemiatutkija 130600, Algorithmic Design Issues in Memetic Computing, and by the UK Engineering and Physical Sciences Research Council (EPSRC) Project: Evolutionary Algorithms for Dynamic Optimisation Problems, under Grant EP/E060722/1

Explicit memory schemes for evolutionary algorithms in dynamic environments

Copyright @ 2007 Springer-VerlagProblem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used

Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks

This article is posted here with permission of IEEE - Copyright @ 2010 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 of U.K. underGrant EP/E060722/

Effective range expansion in various scenarios of EFT(\notpi)

Using rigorous solutions, we compare the ERE parameters obtained in three different scenarios of EFT(\notpi) in nonperturbative regime. A scenario with unconventional power counting (like KSW) is shown to be disfavored by the PSA data, while the one with elaborate prescription of renormalization but keeping conventional power counting intact seems more promising.Comment: 6 pages, 3 tables, no figure, revtex4-1, minor revisions, to appear in EP

Genetic algorithms with elitism-based immigrants for changing optimization problems

Copyright @ Springer-Verlag Berlin Heidelberg 2007.Addressing dynamic optimization problems has been a challenging task for the genetic algorithm community. Over the years, several approaches have been developed into genetic algorithms to enhance their performance in dynamic environments. One major approach is to maintain the diversity of the population, e.g., via random immigrants. This paper proposes an elitism-based immigrants scheme for genetic algorithms in dynamic environments. In the scheme, the elite from previous generation is used as the base to create immigrants via mutation to replace the worst individuals in the current population. This way, the introduced immigrants are more adapted to the changing environment. This paper also proposes a hybrid scheme that combines the elitism-based immigrants scheme with traditional random immigrants scheme to deal with significant changes. The experimental results show that the proposed elitism-based and hybrid immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments

The Arches Cluster Mass Function

We have analyzed H and K_s-band images of the Arches cluster obtained using the NIRC2 instrument on Keck with the laser guide star adaptive optics (LGS AO) system. With the help of the LGS AO system, we were able to obtain the deepest ever photometry for this cluster and its neighborhood, and derive the background-subtracted present-day mass function (PDMF) down to 1.3 Msun for the 5 arcsec-9 arcsec annulus of the cluster. We find that the previously reported turnover at 6 Msun is simply due to a local bump in the mass function (MF), and that the MF continues to increase down to our 50 % completeness limit (1.3 Msun) with a power-law exponent of Gamma = -0.91 for the mass range of 1.3 < M/Msun < 50. Our numerical calculations for the evolution of the Arches cluster show that the Gamma values for our annulus increase by 0.1-0.2 during the lifetime of the cluster, and thus suggest that the Arches cluster initially had Gamma of -1.0 ~ -1.1, which is only slightly shallower than the Salpeter value.Comment: Accepted for publication in ApJ

Effect of iron on the microstructure and mechanical property of Al-Mg-Si-Mn and Al-Mg-Si diecast alloys

This article is made available through the Brunel Open Access Publishing Fund. Copyright @ 2012 Elsevier B.V.This article has been made available through the Brunel Open Access Publishing Fund.Al–Mg–Si based alloys can provide super ductility to satisfy the demands of thin wall castings in the application of automotive structure. In this work, the effect of iron on the microstructure and mechanical properties of the Al–Mg–Si diecast alloys with different Mn concentrations is investigated. The CALPHAD (acronym of Calculation of Phase Diagrams) modelling with the thermodynamic properties of the multi-component Al–Mg–Si–Mn–Fe and Al–Mg–Si–Fe systems is carried out to understand the role of alloying on the formation of different primary Fe-rich intermetallic compounds. The results showed that the Fe-rich intermetallic phases precipitate in two solidification stages in the high pressure die casting process: one is in the shot sleeve and the other is in the die cavity, resulting in the different morphologies and sizes. In the Al–Mg–Si–Mn alloys, the Fe-rich intermetallic phase formed in the shot sleeve exhibited coarse compact morphology and those formed in the die cavity were fine compact particles. Although with different morphologies, the compact intermetallics were identified as the same α-AlFeMnSi phase with typical composition of Al24(Fe,Mn)6Si2. With increased Fe content, β-AlFe was found in the microstructure with a long needle-shaped morphology, which was identified as Al13(Fe,Mn)4Si0.25. In the Al–Mg–Si alloy, the identified Fe-rich intermetallics included the compact α-AlFeSi phase with typical composition of Al8Fe2Si and the needle-shaped β-AlFe phase with typical composition of Al13Fe4. Generally, the existence of iron in the alloy slightly increases the yield strength, but significantly reduces the elongation. The ultimate tensile strength maintains at similar levels when Fe contents is less than 0.5 wt%, but decreases significantly with the further increased Fe concentration in the alloys. CALPHAD modelling shows that the addition of Mn enlarges the Fe tolerance for the formation of α-AlFeMnSi intermetallics and suppresses the formation of β-AlFe phase in the Al–Mg–Si alloys, and thus improves their mechanical properties.EPSRC and JL

A Real-Time Remote IDS Testbed for Connected Vehicles

Connected vehicles are becoming commonplace. A constant connection between vehicles and a central server enables new features and services. This added connectivity raises the likelihood of exposure to attackers and risks unauthorized access. A possible countermeasure to this issue are intrusion detection systems (IDS), which aim at detecting these intrusions during or after their occurrence. The problem with IDS is the large variety of possible approaches with no sensible option for comparing them. Our contribution to this problem comprises the conceptualization and implementation of a testbed for an automotive real-world scenario. That amounts to a server-side IDS detecting intrusions into vehicles remotely. To verify the validity of our approach, we evaluate the testbed from multiple perspectives, including its fitness for purpose and the quality of the data it generates. Our evaluation shows that the testbed makes the effective assessment of various IDS possible. It solves multiple problems of existing approaches, including class imbalance. Additionally, it enables reproducibility and generating data of varying detection difficulties. This allows for comprehensive evaluation of real-time, remote IDS.Comment: Peer-reviewed version accepted for publication in the proceedings of the 34th ACM/SIGAPP Symposium On Applied Computing (SAC'19