Hybrid-Game Strategies for multi-objective design optimization in engineering

A number of Game Strategies (GS) have been developed in past decades. They have been used in the fields of economics, engineering, computer science and biology due to their efficiency in solving design optimization problems. In addition, research in multi-objective (MO) and multidisciplinary design optimization (MDO) has focused on developing robust and efficient optimization methods to produce a set of high quality solutions with low computational cost. In this paper, two optimization techniques are considered; the first optimization method uses multi-fidelity hierarchical Pareto optimality. The second optimization method uses the combination of two Game Strategies; Nash-equilibrium and Pareto optimality. The paper shows how Game Strategies can be hybridised and coupled to Multi-Objective Evolutionary Algorithms (MOEA) to accelerate convergence speed and to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid-Game Strategies are clearly demonstrated

Relative entropy rate based design for linear hybrid system models

Hybrid system representations have been applied to many challenging modeling situations. In these hybrid system representations, a mixture of continuous and discrete states is used to capture the dominating behavioural features of a nonlinear, possible uncertain, model under approximation. Unfortunately, the problem of how to best design a suitable hybrid system model has not yet been fully addressed. This paper proposes a new joint state measurement relative entropy rate based approach for this design purpose. Design examples and simulation studies are presented which highlight the benefits of our proposed design approaches.

ZnO nanostructures grown on epitaxial GaN

Presented is the growth of zinc oxide nanorod/nanowire arrays on gallium nitride epitaxial layers. A hierarchical zinc oxide morphology comprising of different scale zinc oxide nanostructures was observed. The first tier of the surface comprised of typical zinc oxide nanorods, with most bridging to adjacent nanorods. While the second tier comprised of smaller zinc oxide nanowires approximately 30 nm in width often growing atop the aforementioned bridges. Samples were analysed via scanning electron microscopy, as well as, cross-sectional and high resolution transmission electron microscopy to elucidate the detailed growth and structural elements of the heterostructure. © 2009 Elsevier B.V. All rights reserved.

Hybrid light-emitting diodes based on flexible sheets of mass-produced ZnO nanowires

We report the production of free-standing thin sheets made up of mass-produced ZnO nanowires and the application of these nanowire sheets for the fabrication of ZnO/organic hybrid light-emitting diodes in the manner of assembly. Different p-type organic semiconductors are used to form heterojunctions with the ZnO nanowire film. Electroluminescence measurements of the devices show UV and visible emissions. Identical strong red emission is observed independent of the organic semiconductor materials used in this work. The visible emissions corresponding to the electron transition between defect levels within the energy bandgap of ZnO are discussed.

Coupling hybrid-game strategies with particle swarm optimisation for multi-objective high lift systems design optimisation

This paper investigates the High Lift System (HLS) application of complex aerodynamic design problem using Particle Swarm Optimisation (PSO) coupled to Game strategies. Two types of optimization methods are used; the first method is a standard PSO based on Pareto dominance and the second method hybridises PSO with a well-known Nash Game strategies named Hybrid-PSO. These optimization techniques are coupled to a pre/post processor GiD providing unstructured meshes during the optimisation procedure and a transonic analysis software PUMI. The computational efficiency and quality design obtained by PSO and Hybrid-PSO are compared. The numerical results for the multi-objective HLS design optimisation clearly shows the benefits of hybridising a PSO with the Nash game and makes promising the above methodology for solving other more complex multi-physics optimisation problems in Aeronautics.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Towards a controlled growth of self-assembled nanostructures: shaping, ordering and localization in Ge/Si heteroepitaxy.

The strain-induced self-assembly of suitable semiconductor pairs is an attractive natural route to nanofabrication. To bring to fruition their full potential for actual applications, individual nanostructures need to be combined into ordered patterns in which the location of each single unit is coupled with others and the surrounding environment. Within the Ge/Si model system, we analyze a number of examples of bottom-up strategies in which the shape, positioning, and actual growth mode of epitaxial nanostructures are tailored by manipulating the intrinsic physical processes of heteroepitaxy. The possibility of controlling elastic interactions and, hence, the configuration of self-assembled quantum dots by modulating surface orientation with the miscut angle is discussed. We focus on the use of atomic steps and step bunching as natural templates for nanodot clustering. Then, we consider several different patterning techniques which allow one to harness the natural self-organization dynamics of the system, such as: scanning tunneling nanolithography, focused ion beam and nanoindentation patterning. By analyzing the evolution of the dot assembly by scanning probe microscopy, we follow the pathway which leads to lateral ordering, discussing the thermodynamic and kinetic effects involved in selective nucleation on patterned substrates.

Effective hybrid recommendation combining users-searches correlations using tensors

Most recommendation methods employ item-item similarity measures or use ratings data to generate recommendations. These methods use traditional two dimensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective inter group recommendations. Web log data is multi-dimensional data. Unlike vector based methods, tensors have the ability to highly correlate and find latent relationships between such similar instances, consisting of users and searches. Non redundant rules from such associations of user-searches are then used for making recommendations to the users.

Polymer self assembly on carbon nanotubes

This chapter analyses the poly(3-hexylthiophene) self-assembly on carbon nanotubes and the interaction between the two materials forming a new hybrid nanostructure. The chapter starts with a review of the several studies investigating polymers and biomolecules self-assembled on nanotubes. Then conducting polymers and polythiophenes are briefly introduced. Accordingly, carbon nanotube structure and properties are reported in Sect. 3. The experimental section starts with the bulk characterisation of polymer thin films with the inclusion of uniformly distributed carbon nanotubes. By using volume film analysis techniques (AFM, TEM, UV–Vis and Raman), we show how the polymer’s higher degree of order is a direct consequence of interaction with carbon nanotubes. Nevertheless, it is through the use of nanoscale analysis and molecular dynamic simulations that the self-assembly of the polymer on the nanotube surface can be clearly evidenced and characterised. In Sect. 6, the effect of the carbon templating structure on the P3HT organisation on the surface is investigated, showing the chirality-driven polymer assembly on the carbon nanotube surface. The interaction between P3HT and CNTs brings also to charge transfer, with the modification of physical properties for both species. In particular, the alteration of the polymer electronic properties and the modification of the nanotube mechanical structure are a direct consequence of the P3HT p-p stacking on the nanotube surface. Finally, some considerations based on molecular dynamics studies are reported in order to confirm and support the experimental results discussed.

Personalised search – a hybrid approach for web information retrieval and its evaluation

Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

Nanostructures for sensors, electronics, energy and environment

Nanoscale science is growing evermore important on a global scale and is widely seen as playing an integral part in the growth of future world economies. The daunting energy crisis we are facing could be solved not only by new and improved ways of getting energy directly from the sun, but also by saving power thanks to advancements in electronics and sensors. New, cheap dye-sensitized and polymer solar cells hold the promise of environmentally friendly and simple production methods, along with mechanical flexibility and low weight, matching the conditions for a widespread deployment of this technology. Cheap sensors based on nanomaterials can make a fundamental contribution to the reduction of greenhouse gas emissions, allowing the creation of large sensor networks to monitor countries and cities, improving our quality of life. Nanowires and nano-platelets of metal oxides are at the forefront of the research to improve sensitivity and reduce the power consumption in gas sensors. Nanoelectronics is the next step in the electronic roadmap, with many devices currently in production already containing components smaller than 100 nm. Molecules and conducting polymers are at the forefront of this research with the goal of reducing component size through the use of cheap and environmentally friendly production methods. This, and the coming steps that will eventually bring the individual circuit element close to the ultimate limit of the atomic level, are expected to deliver better devices with reduced power consumption.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

Driving Ge island ordering on nanostructured Si surfaces

Semiconductor epitaxial nanostructures have been recently proposed as the key building blocks of many innovative applications in materials science and technology. To bring their tremendous potential to fruition, a fine control of nanostructure size and placement is necessary. We present a detailed investigation of the self-ordering process in the prototype case of Ge/Si heteroepitaxy. Starting from a bottom-up strategy (step-bunching instabilities), our analysis moves to lithographic techniques (scanning tunneling lithography, nanomechanical stamping, focused ion beam patterning) with the aim of developing a hybrid approach in which the exogenous intervention is specifically designed to suit and harness the natural self-organization dynamics of the system.