Hybrid genetic algorithm–tabu search approach for optimising multilayer optical coatings

Constructing multilayer optical coatings (MOCs) is a difficult large-scale optimisation problem due to the enormous size of the search space. In the present paper, a new approach for designing MOCs is presented using genetic algorithms (GAs) and tabu search (TS). In this approach, it is not necessary to specify how many layers will be present in a design, only a maximum needs to be defined. As it is generally recognised that the existence of specific repeating blocks is beneficial for a design, a specific GA representation of a design is used which promotes the occurrence of repeating blocks. Solutions found by GAs are improved by a new refinement method, based on TS, a global optimisation method which is loosely based on artificial intelligence. The improvements are demonstrated by creating a visible transmitting/infrared reflecting filter with a wide variety of materials.     

Protein fold recognition

Summary An important, yet seemingly unattainable, goal in structural molecular biology is to be able to predict the native three-dimensional structure of a protein entirely from its amino acid sequence. Prediction methods based on rigorous energy calculations have not yet been successful, and best results have been obtained from homology modelling and statistical secondary structure prediction. Homology modelling is limited to cases where significant sequence similarity is shared between a protein of known structure and the unknown. Secondary structure prediction methods are not only unreliable, but also do not offer any obvious route to the full tertiary structure. Recently, methods have been developed whereby entire protein folds are recognized from sequence, even where little or no sequence similarity is shared between the proteins under consideration. In this paper we review the current methods, including our own, and in particular offer a historical background to their development. In addition, we also discuss the future of these methods and outline the developments under investigation in our laboratory.     

Drying and pyrolysis of wood particles: experiments and simulation

The objective of this study is to develop a flexible and stable numerical method to predict the thermal decomposition of large wood particles due to drying and pyrolysis. At a later stage, this model is applied to each particle of a packed bed and thus, forms the entire packed bed process as a sum of individual particle processes. Therefore, this approach can deal with particles of different sizes, shapes and properties. A general formulation of the conservation equations allows the geometry of a fuel particle to be treated as a plate, cylinder or sphere. The various processes such as heat-up, drying and pyrolysis are described by a set of one-dimensional and transient conservation equations for mass and energy. This allows for simultaneous processes e.g. reactions in time and covers the entire range between transport-limited (shrinking core) and kinetically limited (reacting core) reaction regimes. The particles interact with a gas phase by heat and mass transfer taking into account the Stefan correction due to the gas outflow during conversion. Experiments carried out span a temperature range between T=300 and 900 °C for particle sizes varying between 8 and 17 mm. A comparison between measurements and predictions of drying models yielded satisfactory agreement only for the constant evaporation temperature model and thus, indicating, that the drying process is transport limited by heat transfer for large wood particles. Likewise, predicted results of pyrolysis for the above-mentioned range of temperatures and sizes agreed satisfactorily with measurements.     

Numerical analysis of the behavior of hydrogen added into a free-burning arc

The objective of the present work is to investigate the behavior of hydrogen in an atmospheric-pressure free-burning argon are when a small amount of hydrogen is added into the arc. A two-dimensional model calculation is carried out under the assumption that the ionization reaction of argon is in equilibrium and the reactions among hydrogen molecules, atoms, ions, and electrons are not necessarily in equilibrium. This calculation gives the following conclusion. The hydrogen mass fraction of 0.001 is too small to affect the flow and temperature fields markedly, and the concentration ratios among the hydrogen species are in equilibrium in the greater part of the arc region except for same parts with a steep temperature gradient. The hydrogen mass Junction, however, is not uniform in the me and, especially in the high-temperature region near the cathodes, over three dynes mass fraction of the hydrogen accumulates and flows downstream to cause a high flux of hydrogen atom toward the anode. This phenomena can be explained by the large difference between the diffusivity of hydrogen atom and that of hydrogen ion in argon ion.     

Reduction of Chemical Reactions in Nitrogen and Nitrogen–Hydrogen Plasma Jets Flowing into Atmospheric Air

The large number of possible chemical reactions represents a severe burdenfor modeling of even relatively simple plasma systems. Reduced sets ofchemical reactions have been obtained for numerical simulations of nitrogenand nitrogen-hydrogen plasma jets flowing into an atmospheric airenvironment. The important or active reactions are determined based on asimplified reduction method. A reaction is considered active if it leadsto higher sensitivities than a specified cutoff sensitivity of 1%. Theactive reactions exert a significant influence on main plasma parameters,such as velocity, temperature, and species concentrations. The sensitivityanalysis for the specified systems shows that two NO reactions, known asZel'dovich reactions (N₂+ONO+N andNO+OO₂+N),⁽¹⁾ are both active in a nitrogenplasma jet. On the other hand, the latter is not active and may be omittedin a nitrogen–hydrogen plasma jet. A nitrogen–hydrogen plasmajet requires contribution of two active charge exchange reactions:N₂+N⁺N⁺ ₂+N andN+H+N+ +H, while only the former is needed in a nitrogen plasmajet. The dissociation reactions are all active in both plasma jets, exceptthe dissociation of OH.     

Study of the Optimal Integrated Control of a Dengue Transmission Model北大核心CSCD

建立了一个登革热在蚊子和人之间传播的模型,引入了Wolbachia、自我保护和杀虫剂三种控制措施,分别从常数控制和时变控制两个方面进行探讨。首先,分析了常数控制对模型基本再生数的影响,研究发现:Wolbachia有助于减小基本再生数,且基本再生数与自我保护和杀虫剂呈负相关。其次,以使得感染数最少且实施成本最低为目标,使用Pontryagin极值原理讨论最优控制。最后,通过数值模拟展示了最优控制的效果。     

GO-MOCE: Greedy Order Method of Conditional Expectations for Max Sat

In this paper we present and study a new algorithm for the Maximum Satisfiability (Max Sat) problem. The algorithm is based on the Method of Conditional Expectations (MOCE, also known as Johnson’s Algorithm) and applies a greedy variable ordering to MOCE. Thus, we name it Greedy Order MOCE (GO-MOCE). We also suggest a combination of GO-MOCE with CCLS, a state-of-the-art solver. We refer to this combined solver as GO-MOCE-CCLS.We conduct a comprehensive comparative evaluation of GO-MOCE versus MOCE on random instances and on public competition benchmark instances. We show that GO-MOCE reduces the number of unsatisfied clauses by tens of percents, while keeping the runtime almost the same. The worst case time complexity of GO-MOCE is linear. We also show that GO-MOCE-CCLS improves on CCLS consistently by up to about 80%.We study the asymptotic performance of GO-MOCE. To this end, we introduce three measures for evaluating the asymptotic performance of algorithms for Max Sat. We point out to further possible improvements of GO-MOCE, based on an empirical study of the main quantities managed by GO-MOCE during its execution.     

Efficient simulation of general stochastic hybrid systems

General Stochastic Hybrid System (SHS) are characterised by Stochastic Differential Equations (SDEs) with discontinuities and Poisson jump processes. SHS are useful in model based design of Cyber-Physical System (CPS) controllers under uncertainty. Industry standard model based design tools such as Simulink/Stateflow® are inefficient when simulating, testing, and validating SHS, because of dependence on fixed-step Euler–Maruyama (EM) integration and discontinuity detection. We present a novel efficient adaptive step-size simulation/integration technique for general SHSs modelled as a network of Stochastic Hybrid Automatons (SHAs). We propose a simulation algorithm where each SHA in the network executes synchronously with the other, at an integration step-size computed using adaptive step-size integration. Ito’ multi-dimensional lemma and the inverse sampling theorem are leveraged to compute the integration step-size by making the SDEs and Poisson jump rate integration dependent upon discontinuities. Existence and convergence analysis along with experimental results show that the proposed technique is substantially faster than Simulink/Stateflow®when simulating general SHSs.     

An exact algorithm for the capacitated shortest spanning arborescence

We are given a complete and loop-free digraphG=(V, A), whereV={1,...,n} is the vertex set,A={(i, j) :i, j V} the arc set, andr V is a distinguishedroot vertex. For each arc (i, j) A, letc _ij be the associatedcost, and for each vertexi, letq _i 0 be the associateddemand (withq _r =0). Moreover, a nonnegativebranch capacity, Q, is defined.A Capacitated Shortest Spanning Arborescence rooted at r (CSSA _r ) is a minimum cost partial digraph such that: (i) each vertexj r has exactly one entering arc; (ii) for each vertexj r, a path fromr toj exists; (iii) for each branch leaving vertexr, the total demand of the vertices does not exceed the branch capacity,Q. A variant of theCSSA _r problem (calledD-CSSA _r ) arises when the out-degree of the root vertex is constrained to be equal to a given valueD. These problems are strongly NP-hard, and find practical applications in routing and network design. We describe a new Lagrangian lower bound forCSSA _r andD-CSSA _r problems, strengthened in a cutting plane fashion by iteratively adding violated constraints to the Lagrangian problem. We also present a new lower bound based on projection leading to the solution of min-cost flow problems. The two lower bounds are then combined so as to obtain an overall additive lower bounding procedure. The additive procedure is then imbedded in a branch-and-bound algorithm whose performance is enhanced by means of reduction procedures, dominance criteria, feasibility checks and upper bounding. Computational tests on asymmetric and symmetric instances from the literature, involving up to 200 vertices, are given, showing the effectiveness of the proposed approach.     

Stochastic on-line knapsack problems

Different classes of on-line algorithms are developed and analyzed for the solution of {0, 1} and relaxed stochastic knapsack problems, in which both profit and size coefficients are random variables. In particular, a linear time on-line algorithm is proposed for which the expected difference between the optimum and the approximate solution value isO(log^3/2 n). An(1) lower bound on the expected difference between the optimum and the solution found by any on-line algorithm is also shown to hold.Corresponding author.Partially supported by the Basic Research Action of the European Communities under Contract 3075 (Alcom).Partially supported by research project Models and Algorithms for Optimization of the Italian Ministry of University and Scientific and Technological Research (MURST 40%).