Multi-population-based differential evolution algorithm for optimization problems

A differential evolution (DE) algorithm is an evolutionary algorithm for optimization problems over a continuous domain. To solve high dimensional global optimization problems, this work investigates the performance of differential evolution algorithms under a multi-population strategy. The original DE algorithm generates an initial set of suitable solutions. The multi-population strategy divides the set into several subsets. These subsets evolve independently and connect with each other according to the DE algorithm. This helps in preserving the diversity of the initial set. Furthermore, a comparison of combination of different mutation techniques on several optimization algorithms is studied to verify their performance. Finally, the computational results on the arbitrarily generated experiments, reveal some interesting relationship between the number of subpopulations and performance of the DE. Centralized charging of electric vehicles (EVs) based on battery swapping is a promising strategy for their large-scale utilization in power systems. In this problem, the above algorithm is designed to minimize total charging cost, as well as to reduce power loss and voltage deviation of power networks. The resulting algorithm and several others are executed on an IEEE 30-bus test system, and the results suggest that the proposed algorithm is one of effective and promising methods for optimal EV centralized charging

Rapid evolution of protein kinase PKR alters sensitivity to viral inhibitors.

Protein kinase PKR (also known as EIF2AK2) is activated during viral infection and phosphorylates the alpha subunit of eukaryotic translation initiation factor 2 (eIF2), leading to inhibition of translation and viral replication. We report fast evolution of the PKR kinase domain in vertebrates, coupled with positive selection of specific sites. Substitution of positively selected residues in human PKR with residues found in related species altered sensitivity to PKR inhibitors from different poxviruses. Species-specific differences in sensitivity to poxviral pseudosubstrate inhibitors were identified between human and mouse PKR, and these differences were traced to positively selected residues near the eIF2alpha binding site. Our findings indicate how an antiviral protein evolved to evade viral inhibition while maintaining its primary function. Moreover, the identified species-specific differences in the susceptibility to viral inhibitors have important implications for studying human infections in nonhuman model systems

A single residue substitution in the receptor-binding domain of H5N1 hemagglutinin is critical for packaging into pseudotyped lentiviral particles

© 2012 Tang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Serological studies for influenza infection and vaccine response often involve microneutralization and hemagglutination inhibition assays to evaluate neutralizing antibodies against human and avian influenza viruses, including H5N1. We have previously characterized lentiviral particles pseudotyped with H5-HA (H5pp) and validated an H5pp-based assay as a safe alternative for high-throughput serological studies in BSL-2 facilities. Here we show that H5-HAs from different clades do not always give rise to efficient production of H5pp and the underlying mechanisms are addressed. Methodology/Findings: We have carried out mutational analysis to delineate the molecular determinants responsible for efficient packaging of HA from A/Cambodia/40808/2005 (H5Cam) and A/Anhui/1/2005 (H5Anh) into H5pp. Our results demonstrate that a single A134V mutation in the 130-loop of the receptor binding domain is sufficient to render H5Anh the ability to generate H5Anh-pp efficiently, whereas the reverse V134A mutation greatly hampers production of H5Cam-pp. Although protein expression in total cell lysates is similar for H5Anh and H5Cam, cell surface expression of H5Cam is detected at a significantly higher level than that of H5Anh. We further demonstrate by several independent lines of evidence that the behaviour of H5Anh can be explained by a stronger binding to sialic acid receptors implicating residue 134. Conclusions: We have identified a single A134V mutation as the molecular determinant in H5-HA for efficient incorporation into H5pp envelope and delineated the underlying mechanism. The reduced binding to sialic acid receptors as a result of the A134V mutation not only exerts a critical influence in pseudotyping efficiency of H5-HA, but has also an impact at the whole virus level. Because A134V substitution has been reported as a naturally occurring mutation in human host, our results may have implications for the understanding of human host adaptation of avian influenza H5N1 virusesThis work was supported by grants from the Research Fund for the Control of Infectious Diseases of Hong Kong (RFCID#08070972), the Area of Excellence Scheme of the University Grants Committee (grant AoE/M-12/-06 of the Hong Kong Special Administrative Region, China), the French Ministry of Health, and the RESPARI project of the Institut Pasteur International Network

Optimal Ship Maintenance Scheduling Under Restricted Conditions and Constrained Resources

The research presented in this dissertation addresses the application of evolution algorithms, i.e. Genetic Algorithm (GA) and Differential Evolution algorithm (DE) to scheduling problems in the presence of restricted conditions and resource limitations. This research is motivated by the scheduling of engineering design tasks in shop scheduling problems and ship maintenance scheduling problems to minimize total completion time. The thesis consists of two major parts; the first corresponds to the first appended paper and deals with the computational complexity of mixed shop scheduling problems. A modified Genetic algorithm is proposed to solve the problem. Computational experiments, conducted to evaluate its performance against known optimal solutions for different sized problems, show its superiority in computation time and the high applicability in practical mixed shop scheduling problems. The second part considers the major theme in the second appended paper and is related to the ship maintenance scheduling problem and the extended research on the multi-mode resource-constrained ship scheduling problem. A heuristic Differential Evolution is developed and applied to solve these problems. A mathematical optimization model is also formulated for the multi-mode resource-constrained ship scheduling problem. Through the computed results, DE proves its effectiveness and efficiency in addressing both single and multi-objective ship maintenance scheduling problem

Conformational adaptation of Asian macaque TRIMCyp directs lineage specific antiviral activity

TRIMCyps are anti-retroviral proteins that have arisen independently in New World and Old World primates. All TRIMCyps comprise a CypA domain fused to the tripartite domains of TRIM5α but they have distinct lentiviral specificities, conferring HIV-1 restriction in New World owl monkeys and HIV-2 restriction in Old World rhesus macaques. Here we provide evidence that Asian macaque TRIMCyps have acquired changes that switch restriction specificity between different lentiviral lineages, resulting in species-specific alleles that target different viruses. Structural, thermodynamic and viral restriction analysis suggests that a single mutation in the Cyp domain, R69H, occurred early in macaque TRIMCyp evolution, expanding restriction specificity to the lentiviral lineages found in African green monkeys, sooty mangabeys and chimpanzees. Subsequent mutations have enhanced restriction to particular viruses but at the cost of broad specificity. We reveal how specificity is altered by a scaffold mutation, E143K, that modifies surface electrostatics and propagates conformational changes into the active site. Our results suggest that lentiviruses may have been important pathogens in Asian macaques despite the fact that there are no reported lentiviral infections in current macaque populations

Multi-Guide Particle Swarm Optimization for Large-Scale Multi-Objective Optimization Problems

Multi-guide particle swarm optimization (MGPSO) is a novel metaheuristic for multi-objective optimization based on particle swarm optimization (PSO). MGPSO has been shown to be competitive when compared with other state-of-the-art multi-objective optimization algorithms for low-dimensional problems. However, to the best of the author’s knowledge, the suitability of MGPSO for high-dimensional multi-objective optimization problems has not been studied. One goal of this thesis is to provide a scalability study of MGPSO in order to evaluate its efficacy for high-dimensional multi-objective optimization problems. It is observed that while MGPSO has comparable performance to state-of-the-art multi-objective optimization algorithms, it experiences a performance drop with the increase in the problem dimensionality. Therefore, a main contribution of this work is a new scalable MGPSO-based algorithm, termed cooperative co-evolutionary multi-guide particle swarm optimization (CCMGPSO), that incorporates ideas from cooperative PSOs. A detailed empirical study on well-known benchmark problems comparing the proposed improved approach with various state-of-the-art multi-objective optimization algorithms is done. Results show that the proposed CCMGPSO is highly competitive for high-dimensional problems