Double-shock control bump design optimization using hybridized evolutionary algorithms

This study investigates the application of two advanced optimization methods for solving active flow control (AFC) device shape design problem and compares their optimization efficiency in terms of computational cost and design quality. The first optimization method uses hierarchical asynchronous parallel multi-objective evolutionary algorithm and the second uses hybridized evolutionary algorithm with Nash-Game strategies (Hybrid-Game). Both optimization methods are based on a canonical evolution strategy and incorporate the concepts of parallel computing and asynchronous evaluation. One type of AFC device named shock control bump (SCB) is considered and applied to a natural laminar flow (NLF) aerofoil. The concept of SCB is used to decelerate supersonic flow on suction/pressure side of transonic aerofoil that leads to a delay of shock occurrence. Such active flow technique reduces total drag at transonic speeds which is of special interest to commercial aircraft. Numerical results show that the Hybrid-Game helps an EA to accelerate optimization process. From the practical point of view, applying a SCB on the suction and pressure sides significantly reduces transonic total drag and improves lift-to-drag (L/D) value when compared to the baseline design.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

On the computation and interpretation of auto- and cross-trispectra

This paper discusses the principal domains of auto- and cross-trispectra. It is shown that the cumulant and moment based trispectra are identical except on certain planes in trifrequency space. If these planes are avoided, their principal domains can be derived by considering the regions of symmetry of the fourth order spectral moment. The fourth order averaged periodogram will then serve as an estimate for both cumulant and moment trispectra. Statistics of estimates of normalised trispectra or tricoherence are also discussed.

Why evolutionary realism underpins evolutionary economic analysis and theory

This paper offers a reply to Jochen Runde's critical appraisal of the ontological framework underpinning Dopfer and Potts's (2008) General Theory of Economic Evolution. We argue that Runde's comprehensive critique contains several of what we perceive to be misunderstandings in relation to the key concepts of ‘generic’ and ‘meso’ that we seek here to unpack and redress.

An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation

This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.

Robust multidisciplinary UAS design optimisation

There are many applications in aeronautical/aerospace engineering where some values of the design parameters states cannot be provided or determined accurately. These values can be related to the geometry(wingspan, length, angles) and or to operational flight conditions that vary due to the presence of uncertainty parameters (Mach, angle of attack, air density and temperature, etc.). These uncertainty design parameters cannot be ignored in engineering design and must be taken into the optimisation task to produce more realistic and reliable solutions. In this paper, a robust/uncertainty design method with statistical constraints is introduced to produce a set of reliable solutions which have high performance and low sensitivity. Robust design concept coupled with Multi Objective Evolutionary Algorithms (MOEAs) is defined by applying two statistical sampling formulas; mean and variance/standard deviation associated with the optimisation fitness/objective functions. The methodology is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. It is implemented for two practical Unmanned Aerial System (UAS) design problems; the flrst case considers robust multi-objective (single disciplinary: aerodynamics) design optimisation and the second considers a robust multidisciplinary (aero structures) design optimisation. Numerical results show that the solutions obtained by the robust design method with statistical constraints have a more reliable performance and sensitivity in both aerodynamics and structures when compared to the baseline design.

Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion

This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

Evolutionary morphing for music composition

From one view of composition—let us call it the inspired or “Mozartian” view—musical compositions arrive fully formed in the mind of the composer and simply require transcription. In reality, however, it seems that very few people are so inspired, and composition is often more akin to a gradual clarification and refinement of partially formed ideas on the musical landscape. Particular landmarks in the compositional landscape tend to become clear before others, such that the incomplete piece is a patchwork of disconnected musical islands. An interactive evolutionary morphing system may provide some assistance for composers, to help build bridges between musical islands by generating hybrid musical transitions.

A natural model for architecture

In John Frazer's seminal book An Evolutionary Architecture (1995), from which this essay is extracted, a fundamental approach is established for have natural systems can unfold mechanisms for negotiating the complex design space inherent in architectural systems. In this essay, which forms a critical part of the book, Frazer draws both correlations and distinctions from natural processes as emulated in design processes and form as active manifestations within natural systems. Form is seen as an evolving agent generated via the rules of descriptive genetic coding, functioning as a part of a metabolic environment. Frazer's process-model establishes the realm in which computation must manoeuvre to produce a valid solution space, including the operations of self-organisation, complexity and emergent behaviour. Addressing design as an authored practice, he extends the transference of 'creativity' from the explicit impression into form, to the investment of though, organisation and strategy in the computational processes which produce form. Frazer's text concentrates astutely on the practising of the evolutionary paradigm, the output of which postulates an architecture born of the relationships to dynamic environmental and socio-economic contexts, and realised through morphogenetic materialisation.

Towards an evolutionary perspective for human information behavior: An exploratory study

Purpose - Since the beginning of human existence, humankind has sought, organized and used information as it evolved patterns and practices of human information behaviors. However, the field of human information behavior (HIB) has not heretofore pursued an evolutionary understanding of information behavior. The goal of this exploratory study is to provide insight about the information behavior of various individuals from the past to begin the development of an evolutionary perspective for our understanding of HIB. Design/methodology/approach - This paper presents findings from a qualitative analysis of the autobiographies and personal writings of several historical figures, including Napoleon Bonaparte, Charles Darwin, Giacomo Casanova and others. Findings - Analysis of their writings shows that these persons of the past articulated aspects of their HIB's, including information seeking, information organization and information use, providing tangible insights into their information-related thoughts and actions. Practical implications - This paper has implications for expanding the nature of our evolutionary understanding of information behavior and provides a broader context for the HIB research field. Originality/value - This the first paper in the information science field of HIB to study the information behavior of historical figures and begin to develop an evolutionary framework for HIB research. © Emerald Group Publishing Limited.

Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens

In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.

Evolutionary biology : mass survivals

The conclusion that the primary divergences of the modern groups of mammals occurred in the mid-Cretaceous requires fresh thinking about this facet of evolutionary history — especially in ecological terms.

Review ["Telling the Evolutionary Time : Molecular Clocks and the Fossil Record" edited by Philip C. J. Donoghue and M. Paul Smith]

Determining the temporal scale of biological evolution has traditionally been the preserve of paleontology, with the timing of species originations and major diversifications all being read from the fossil record. However, the ages of the earliest (correctly identified) records will underestimate actual origins due to the incomplete nature of the fossil record and the necessity for lineages to have evolved sufficiently divergent morphologies in order to be distinguished. The possibility of inferring divergence times more accurately has been promoted by the idea that the accumulation of genetic change between modern lineages can be used as a molecular clock (Zuckerkandl and Pauling, 1965). In practice, though, molecular dates have often been so old as to be incongruent even with liberal readings of the fossil record. Prominent examples include inferred diversifications of metazoan phyla hundreds of millions of years before their Cambrian fossil record appearances (e.g., Nei et al., 2001) and a basal split between modern birds (Neoaves) that is almost double the age of their earliest recognizable fossils (e.g., Cooper and Penny, 1997).