FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

A novel approach to dynamic modelling of polymer extrusion for improved process control

Polymer extrusion is a complex process and the availability of good dynamic models is key for improved system operation. Previous modelling attempts have failed adequately to capture the non-linearities of the process or prove too complex for control applications. This work presents a novel approach to the problem by the modelling of extrusion viscosity and pressure, adopting a grey box modelling technique that combines mechanistic knowledge with empirical data using a genetic algorithm approach. The models are shown to outperform those of a much higher order generated by a conventional black box technique while providing insight into the underlying processes at work within the extruder.

The VLT-FLAMES survey of massive stars: mass loss and rotation of early-type stars in the SMC

We have studied the optical spectra of a sample of 31 O- and early B-type stars in the Small Magellanic Cloud, 21 of which are associated with the young massive cluster NGC 346. Stellar parameters are determined using an automated fitting method (Mokiem et al. 2005, A&A, 441, 711), which combines the stellar atmosphere code FASTWIND (Puls et al. 2005, A&A, 435, 669) with the genetic algorithm based optimisation routine PIKAIA (Charbonneau 1995, ApJS, 101, 309). Comparison with predictions of stellar evolution that account for stellar rotation does not result in a unique age, though most stars are best represented by an age of 1-3 Myr. The automated method allows for a detailed determination of the projected rotational velocities. The present day v(r) sin i distribution of the 21 dwarf stars in our sample is consistent with an underlying rotational velocity (v(r)) distribution that can be characterised by a mean velocity of about 160-190 km s(-1) and an effective half width of 100-150 km s(-1). The vr distribution must include a small percentage of slowly rotating stars. If predictions of the time evolution of the equatorial velocity for massive stars within the environment of the SMC are correct (Maeder & Meynet 2001, A&A, 373, 555), the young age of the cluster implies that this underlying distribution is representative for the initial rotational velocity distribution. The location in the Hertzsprung-Russell diagram of the stars showing helium enrichment is in qualitative agreement with evolutionary tracks accounting for rotation, but not for those ignoring vr. The mass loss rates of the SMC objects having luminosities of log L-star/L-circle dot greater than or similar to 5.4 are in excellent agreement with predictions by Vink et al. (2001, A&A, 369, 574). However, for lower luminosity stars the winds are too weak to determine. M accurately from the optical spectrum. Three targets were classified as Vz stars, two of which are located close to the theoretical zero-age main sequence. Three lower luminosity targets that were not classified as Vz stars are also found to lie near the ZAMS. We argue that this is related to a temperature effect inhibiting cooler from displaying the spectral features required for the Vz luminosity class.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

A Hybrid Evolutionary Approach to the Nurse Rostering Problem

Nurse rostering is a difficult search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle these constraints within genetic algorithm frameworks. In this paper, we investigate an extension of a previously proposed stochastic ranking method, which has demonstrated superior performance to other constraint handling techniques when tested against a set of constrained optimisation benchmark problems. An initial experiment on nurse rostering problems demonstrates that the stochastic ranking method is better in finding feasible solutions but fails to obtain good results with regard to the objective function. To improve the performance of the algorithm, we hybridise it with a recently proposed simulated annealing hyper-heuristic within a local search and genetic algorithm framework. The hybrid algorithm shows significant improvement over both the genetic algorithm with stochastic ranking and the simulated annealing hyper-heuristic alone. The hybrid algorithm also considerably outperforms the methods in the literature which have the previously best known results.

The VLT-FLAMES survey of massive stars: wind properties and evolution of hot massive stars in the Large Magellanic Cloud

We have studied the optical spectra of a sample of 28 O- and early B-type stars in the Large Magellanic Cloud, 22 of which are associated with the young star forming region N11. Our observations sample the central associations of LH9 and LH10, and the surrounding regions. Stellar parameters are determined using an automated fitting method ( Mokiem et al. 2005), which combines the stellar atmosphere code fastwind ( Puls et al. 2005) with the genetic algorithm based optimisation routine PIKAIA ( Charbonneau 1995). We derive an age of 7.0 +/- 1.0 and 3.0 +/- 1.0 Myr for LH9 and LH10, respectively. The age difference and relative distance of the associations are consistent with a sequential star formation scenario in which stellar activity in LH9 triggered the formation of LH10. Our sample contains four stars of spectral type O2. From helium and hydrogen line fitting we find the hottest three of these stars to be similar to 49- 54 kK ( compared to similar to 45- 46 kK for O3 stars). Detailed determination of the helium mass fraction reveals that the masses of helium enriched dwarfs and giants derived in our spectroscopic analysis are systematically lower than those implied by non-rotating evolutionary tracks. We interpret this as evidence for efficient rotationally enhanced mixing leading to the surfacing of primary helium and to an increase of the stellar luminosity. This result is consistent with findings for SMC stars by Mokiem et al. ( 2006). For bright giants and supergiants no such mass discrepancy is found; these stars therefore appear to follow tracks of modestly or non-rotating objects. The set of programme stars was sufficiently large to establish the mass loss rates of OB stars in this Z similar to 1/2 Z(circle dot) environment sufficiently accurate to allow for a quantitative comparison with similar objects in the Galaxy and the SMC. The mass loss properties are found to be intermediate to massive stars in the Galaxy and SMC. Comparing the derived modified wind momenta D-mom as a function of luminosity with predictions for LMC metallicities by Vink et al. ( 2001) yields good agreement in the entire luminosity range that was investigated, i.e. 5.0

A computational intelligent approach to multi-factor analysis of violent crime information systems

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Optimal design of long-span steel portal frames using fabricated beams

This paper considers the optimal design of fabricated steel beams for long-span portal frames. The design optimisation takes into account ultimate as well as serviceability limit states, adopting deflection limits recommended by the Steel Construction Institute (SCI). Results for three benchmark frames demonstrate the efficiency of the optimisation methodology. A genetic algorithm (GA) was used to optimise the dimensions of the plates used for the columns, rafters and haunches. Discrete decision variables were adopted for the thickness of the steel plates and continuous variables for the breadth and depth of the plates. Strategies were developed to enhance the performance of the GA including solution space reduction and a hybrid initial population half of which is derived using Latin hypercube sampling. The results show that the proposed GA-based optimisation model generates optimal and near-optimal solutions consistently. A parametric study is then conducted on frames of different spans. A significant variation in weight between fabricated and conventional hot-rolled steel portal frames is shown; for a 50 m span frame, a 14–19% saving in weight was achieved. Furthermore, since Universal Beam sections in the UK come from a discrete section library, the results could also provide overall dimensions of other beams that could be more efficient for portal frames. Eurocode 3 was used for illustrative purposes; any alternative code of practice may be used.

Dimensioning of multilayer optical networks

Este trabalho apresenta um estudo sobre o dimensionamento de redes ópticas, com vistas a obter um modelo de dimensionamento para redes de transporte sobreviventes. No estudo utilizou-se uma abordagem estatística em detrimento à determinística. Inicialmente, apresentam-se as principais tecnologias e diferentes arquitecturas utilizadas nas redes ópticas de transporte. Bem como os principais esquemas de sobrevivência e modos de transporte. São identificadas variáveis necessárias e apresenta-se um modelo dimensionamento para redes de transporte, tendo-se dado ênfase às redes com topologia em malha e considerando os modos de transporte opaco, transparente e translúcido. É feita uma análise rigorosa das características das topologias de redes de transporte reais, e desenvolve-se um gerador de topologias de redes de transporte, para testar a validade dos modelos desenvolvidos. Também é implementado um algoritmo genético para a obtenção de uma topologia optimizada para um dado tráfego. São propostas expressões para o cálculo de variáveis não determinísticas, nomeadamente, para o número médio de saltos de um pedido, coeficiente de protecção e coeficiente de restauro. Para as duas últimas, também é analisado o impacto do modelo de tráfego. Verifica-se que os resultados obtidos pelas expressões propostas são similares às obtidas por cálculo numérico, e que o modelo de tráfego não influencia significativamente os valores obtidos para os coeficientes. Finalmente, é demonstrado que o modelo proposto é útil para o dimensionamento e cálculo dos custos de capital de redes com informação incompleta.

Alternative techniques for Raman amplification in telecommunications

O presente trabalho centra-se no estudo dos amplificadores de Raman em fibra ótica e suas aplicações em sistemas modernos de comunicações óticas. Abordaram-se tópicos específicos como a simulação espacial do amplificador de Raman, a equalização e alargamento do ganho, o uso de abordagens híbridas de amplificação através da associação de amplificadores de Raman em fibra ótica com amplificadores de fibra dopada com Érbio (EDFA) e os efeitos transitórios no ganho dos amplificadores. As actividades realizadas basearam-se em modelos teóricos, sendo os resultados validados experimentalmente. De entre as contribuições mais importantes desta tese, destaca-se (i) o desenvolvimento de um simulador eficiente para amplificadores de Raman que suporta arquitecturas de bombeamento contraprogantes e bidirecionais num contexto com multiplexagem no comprimento de onda (WDM); (ii) a implementação de um algoritmo de alocação de sinais de bombeamento usando a combinação do algoritmo genético com o método de Nelder- Mead; (iii) a apreciação de soluções de amplificação híbridas por associação dos amplificadores de Raman com EDFA em cenários de redes óticas passivas, nomeadamente WDM/TDM-PON com extensão a região espectral C+L; e (iv) a avaliação e caracterização de fenómenos transitórios em amplificadores para tráfego em rajadas/pacotes óticos e consequente desenvolvimento de soluções de mitigação baseadas em técnicas de clamping ótico.

Advanced optical modulation and format conversion

Over the years, the increased search and exchange of information lead to an increase of traffic intensity in todays optical communication networks. Coherent communications, using the amplitude and phase of the signal, reappears as one of the transmission techniques to increase the spectral efficiency and throughput of optical channels. In this context, this work present a study on format conversion of modulated signals using MZI-SOAs, based exclusively on all- optical techniques through wavelength conversion. This approach, when applied in interconnection nodes between optical networks with different bit rates and modulation formats, allow a better efficiency and scalability of the network. We start with an experimental characterization of the static and dynamic properties of the MZI-SOA. Then, we propose a semi-analytical model to describe the evolution of phase and amplitude at the output of the MZI-SOA. The model’s coefficients are obtained using a multi-objective genetic algorithm. We validate the model experimentally, by exploring the dependency of the optical signal with the operational parameters of the MZI-SOA. We also propose an all-optical technique for the conversion of amplitude modulation signals to a continuous phase modulation format. Finally, we study the potential of MZI-SOAs for the conversion of amplitude signals to QPSK and QAM signals. We show the dependency of the conversion process with the operational parameters deviation from the optimal values. The technique is experimentally validated for QPSK modulation.

Intelligent predictive control for thermal comfort and energy savings in public buildings

This talk addresses the problem of controlling a heating ventilating and air conditioning system with the purpose of achieving a desired thermal comfort level and energy savings. The formulation uses the thermal comfort, assessed using the predicted mean vote (PMV) index, as a restriction and minimises the energy spent to comply with it. This results in the maintenance of thermal comfort and on the minimisation of energy, which in most operating conditions are conflicting goals requiring some sort of optimisation method to find appropriate solutions over time. In this work a discrete model based predictive control methodology is applied to the problem. It consists of three major components: the predictive models, implemented by radial basis function neural networks identifed by means of a multi-objective genetic algorithm [1]; the cost function that will be optimised to minimise energy consumption and provide adequate thermal comfort; and finally the optimisation method, in this case a discrete branch and bound approach. Each component will be described, with a special emphasis on a fast and accurate computation of the PMV indices [2]. Experimental results obtained within different rooms in a building of the University of Algarve will be presented, both in summer [3] and winter [4] conditions, demonstrating the feasibility and performance of the approach. Energy savings resulting from the application of the method are estimated to be greater than 50%.

Model comparison for temperature estimation inside buildings

This paper presents a comparison between a physical model and an artificial neural network model (NN) for temperature estimation inside a building room. Despite the obvious advantages of the physical model for structure optimisation purposes, this paper will test the performance of neural models for inside temperature estimation. The great advantage of the NN model is a big reduction of human effort time, because it is not needed to develop the structural geometry and structural thermal capacities and to simulate, which consumes a great human effort and great computation time. The NN model deals with this problem as a “black box” problem. We describe the use of the Radial Basis Function (RBF), the training method and a multi-objective genetic algorithm for optimisation/selection of the RBF neural network inputs and number of neurons.

Learning control systems

Novel method of controller (PID) autotuning, involving neural networks and genetic algorithms: to employ neural networks to map the identification measures and controller parameters to objective functions, adapt these models on-line; to employ the genetic algorithm to perform on-line minimization.