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Memetic algorithms (MAs) are optimization techniques based on the orchestrated interplay between global and local search components and have the exploitation of specific problem knowledge as one of their guiding principles. In its most... more
Memetic algorithms (MAs) are optimization techniques based on the orchestrated interplay between global and local search components and have the exploitation of specific problem knowledge as one of their guiding principles. In its most classical form, a MA is typically composed of an underlying population-based engine onto which a local search component is integrated. These aspects are described in this chapter in some detail, paying particular attention to design and integration issues. After this description of the basic architecture of MAs, we move to different algorithmic extensions that give rise to more sophisticated memetic approaches. After providing a meta-review of the numerous practical applications of MAs, we close this chapter with an overview of current perspectives of memetic algorithms.
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This chapter addresses three main problems of the production planning area: Single Machine Scheduling (SMS), Parallel Machine Scheduling (PMS) and Flowshop Scheduling (FS). Many situations in production environments found in industries... more
This chapter addresses three main problems of the production planning area: Single Machine Scheduling (SMS), Parallel Machine Scheduling (PMS) and Flowshop Scheduling (FS). Many situations in production environments found in industries around the world can be modelled as one or a set of them (Baker 1974). It is easy to find dozens of problem variants in the literature due to different production constraints and objective functions. Due to the overwhelming number of combinations, we focused our discussion on only one of each problem class. They are: SMS with sequence-dependent setup times and with the objective of minimizing of the total tardiness. PMS with sequence-dependent setup times and minimization of the makespan. FS with families of jobs, sequence-dependent setup times and minimization of the makespan.
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Multiple sclerosis (MS) is a chronic relapsing-remitting inflammatory disease of the central nervous system characterized by oligodendrocyte damage, demyelination and neuronal death. Genetic association studies have shown a two-fold or... more
Multiple sclerosis (MS) is a chronic relapsing-remitting inflammatory disease of the central nervous system characterized by oligodendrocyte damage, demyelination and neuronal death. Genetic association studies have shown a two-fold or greater prevalence of the HLA-DRB1*1501 allele in the MS population compared with normal Caucasians. In discovery cohorts of Australasian patients with multiple sclerosis (total 2941 patients, 3008 controls) we examined the associations of twelve functional polymorphisms of P2X7, a microglial/macrophage receptor with proinflammatory effects when activated by extracellular ATP. In discovery cohorts, rs28360457, coding for Arg307Gln was associated with MS and combined analysis showed a two-fold lower minor allele frequency compared with controls (1.11% for MS and 2.15% for controls, p=0.0000071). Replication analysis of four independent European MS case-control cohorts (total 2140 cases and 2634 controls) confirmed this association (OR 0.69, p=0.026). A...
Research Interests: Engineering, Genetics, Biology, Medicine, Biological Sciences, and 15 moreHumans, Human Molecular Genetics, Genetic Association Studies, Australasia, Glutamine, Arginine, European Continental Ancestry Group, Amino Acid Substitution Rates, Case Control Study, Allele, Haplotype, Adenosine Triphosphate, binding sites, Medical and Health Sciences, and Genetic predisposition to disease
Research Interests: Engineering, Genetics, Biology, Dendritic Cells, Biological Sciences, and 15 moreHumans, Autoimmune Disease, Female, Male, Human Molecular Genetics, Gene, Genetic linkage analysis, Aged, Adult, Linkage Disequilibrium, Genetic variation, Allele, Gene Expression Regulation, Medical and Health Sciences, and Genetic predisposition to disease
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We introduce new analytical approximations of the minimum electrostatic energy configuration of n electrons, E(n), when they are constrained to be on the surface of a unit sphere. Using 454 putative optimal configurations we searched for... more
We introduce new analytical approximations of the minimum electrostatic energy configuration of n electrons, E(n), when they are constrained to be on the surface of a unit sphere. Using 454 putative optimal configurations we searched for approximations of the form E(n) = (n2/2) e g(n) where g(n) was obtained via a memetic algorithm that searched for truncated analytic continued fractions finally obtaining one with Mean Squared Error equal to 4.5744×10^(-8). Using the Online Encyclopedia of Integer Sequences, we searched over 350,000 sequences and, for small values of n, we identified a strong correlation of the highest residual of our best approximations with the sequence of integers n defined by the condition that n2 +12 is a prime. We also observed an interesting correlation with the behaviour of the smallest angle α(n), measured in radians, subtended by the vectors associated with the nearest pair of electrons in the optimal configuration. When using both √n and α(n) as variables...
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Complex software intensive systems, especially distributed systems, generate logs for troubleshooting. The logs are text messages recording system events, which can help engineers determine the system's runtime status. This paper... more
Complex software intensive systems, especially distributed systems, generate logs for troubleshooting. The logs are text messages recording system events, which can help engineers determine the system's runtime status. This paper proposes a novel approach named ADR (stands for Anomaly Detection by workflow Relations) that employs matrix nullspace to mine numerical relations from log data. The mined relations can be used for both offline and online anomaly detection and facilitate fault diagnosis. We have evaluated ADR on log data collected from two distributed systems, HDFS (Hadoop Distributed File System) and BGL (IBM Blue Gene/L supercomputers system). ADR successfully mined 87 and 669 numerical relations from the logs and used them to detect anomalies with high precision and recall. For online anomaly detection, ADR employs PSO (Particle Swarm Optimization) to find the optimal sliding windows' size and achieves fast anomaly detection.The experimental results confirm that ...
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ABSTRACT
The Quadratic Assignment Problem (QAP) is a well-studied, NP-Hard combinatorial optimization problem with practical applications in timetabling, scheduling, logistics, circuit design and data visualisation, to name a few. In this paper a... more
The Quadratic Assignment Problem (QAP) is a well-studied, NP-Hard combinatorial optimization problem with practical applications in timetabling, scheduling, logistics, circuit design and data visualisation, to name a few. In this paper a Memetic Algorithm is described, which utilises a ternary tree structure for its population and uses a Tabu Search as its local improvement strategy. The Tabu Search is also run in parallel, significantly reducing the running time of the algorithm. The ternary tree not only stores the individuals within the population, but the inherent structure within this tree also determines parent selection for crossover. A small number of rules, which include fitness and diversity-based rules, govern whether a newly produced solution remains within the population, or whether it is discarded. These key features are tested against a basic Memetic Algorithm using the instances from the QAP library, QAPLIB, and have shown to significantly improve the performance in terms of both time and solution quality. The best version of the Memetic Algorithm is shown to perform competitively with some of the state-of-the-art algorithms for the QAP from the literature, with grid-based and real-life instances shown to be solved very efficiently and effectively by the presented algorithms.
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Research Interests: Multiple sclerosis, Biological Sciences, Humans, Haplotypes, Human Molecular Genetics, and 11 moreAntigen Presentation, T lymphocytes, Genotype, Oxidative phosphorylation, Oxford university, Linkage Disequilibrium, Genetic Association, Gene Expression Regulation, Gene expression profiling, Whole-blood, and Medical and Health Sciences
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... Tell us what you think. Memetic algorithms: a short introduction. Source, Mcgraw-Hill'S Advanced Topics In Computer Science Series archive New ideas in optimization book contents. Pages: 219 - 234. Year of Publication: 1999.... more
... Tell us what you think. Memetic algorithms: a short introduction. Source, Mcgraw-Hill'S Advanced Topics In Computer Science Series archive New ideas in optimization book contents. Pages: 219 - 234. Year of Publication: 1999. ISBN:0-07-709506-5. Author, Pablo Moscato, ...
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We introduce novel Information Theory quantifiers in a computational linguistic study that involves a large corpus of English Renaissance literature. The 185 texts studied (136 plays and 49 poems in total), with first editions that range... more
We introduce novel Information Theory quantifiers in a computational linguistic study that involves a large corpus of English Renaissance literature. The 185 texts studied (136 plays and 49 poems in total), with first editions that range from 1580 to 1640, form a representative set of its period. Our data set includes 30 texts unquestionably attributed to Shakespeare; in addition we also included A Lover's Complaint, a poem which generally appears in Shakespeare collected editions but whose authorship is currently in dispute. Our statistical ...
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Background: Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several... more
Background: Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls. Methodology/Principal Findings: We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expres...
Research Interests: Multiple sclerosis, Biology, Adolescent, Medicine, Multidisciplinary, and 15 moreHumans, Female, Male, Transcription Factor, PLoS one, Primary Progressive Aphasia, Aged, Middle Aged, Adult, Gene Expression Analysis, Expression analysis, Gene expression profiling, Case Control Studies, Cohort Studies, and Differential expression
Abstract. This paper illustrates how the Quadratic Assignment Prob-lem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the relationships between the objects (genes or samples). The... more
Abstract. This paper illustrates how the Quadratic Assignment Prob-lem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the relationships between the objects (genes or samples). The visualization method can also incorpo-rate the result of a clustering algorithm to facilitate the process of data analysis. Specifically, we show the integration with a graph-based clus-tering algorithm that outperforms the results against other benchmarks, namely k−means and self-organizing maps. Even though the application uses gene expression data, the method is general and only requires a sim-ilarity function being defined between pairs of objects. The microarray dataset is based on the budding yeast (S. cerevisiae). It is composed of 79 samples taken from different experiments and 2,467 genes. The pro-posed method delivers an automatically generated visualization of the microarray dataset based on the integration of the relationships coming fro...
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Abstract. This paper introduces an automatic procedure to assist on the interpretation of a large dataset when a similarity metric is available. We propose a visualization approach based on a graph layout method-ology that uses a... more
Abstract. This paper introduces an automatic procedure to assist on the interpretation of a large dataset when a similarity metric is available. We propose a visualization approach based on a graph layout method-ology that uses a Quadratic Assignment Problem (QAP) formulation. The methodology is presented using as testbed a time series dataset of the Standard & Poor’s 100, one the leading stock market indicators in the United States. A weighted graph is created with the stocks repre-sented by the nodes and the edges ’ weights are related to the correlation between the stocks ’ time series. A heuristic for clustering is then pro-posed; it is based on the graph partition into disconnected subgraphs allowing the identification of clusters of highly-correlated stocks. The final layout corresponds well with the perceived market notion of the different industrial sectors. We compare the output of this procedure with a traditional dendogram approach of hierarchical clustering. 1
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Background: Alzheimer’s disease (AD) is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly... more
Background: Alzheimer’s disease (AD) is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer’s is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96 % total accuracy in predicting clinical AD. The signature is composed of the abundances of...
Research Interests: Computer Science, Computational Biology, Medicine, Multidisciplinary, Feature Selection, and 15 moreSoftware, Brain, Humans, Developing Country, Prediction error, Proteins, PLoS one, Epidermal Growth Factor, Reproducibility of Results, Biological markers, Disease Progression, Logistic Model, Alzheimer Disease, Gene Expression Regulation, and Interleukin
A large number of problems in business and consumer analytics have input graphs or networks. These mathematical entities have a long standing tradition in discrete applied mathematics and computer science. In many cases, they are the most... more
A large number of problems in business and consumer analytics have input graphs or networks. These mathematical entities have a long standing tradition in discrete applied mathematics and computer science. In many cases, they are the most natural means to represent some type of relationships in data. Consequently, a large number of solution methods based on heuristics and exact algorithms exist for problems that have graphs and/or networks as part of their input. While the number of possible applications of these techniques is not limited to problems in business and customer analytics, we have chosen to present some of them in a survey that would allow newcomers to the field of data science to create some familiarity with the key questions that motivate the area. We have also provided a survey on recent applications and new algorithmic approaches for data analytics. In addition we discuss issues related to the computational complexity of some problems associated with them. Other chapters of this section complement the discussion in this chapter with specific examples of interest or that could motivate new novel research direction and application.