1,905,994 research outputs found
Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation
No full textPortfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation methods such as mean-variance optimisation are not appropriate for such problems and global search optimisation algorithms could serve better to address such problems. Also, in implementing such an approach the goal is to incorporate information as to the future expected outcomes to determine the optimised portfolio rather than optimise a portfolio on historic performance. In this paper, we consider the suitability of global search optimisation algorithms applied to FoHF portfolios, and using one of these algorithms to construct an optimal portfolio of investable hedge fund indices given forecast views of the future and our confidence in such views.portfolio optimisation; optimization; fund of hedge funds; global search optimisation; direct search; pgsl; hedge fund portfolio
Business process improvement using multi-objective optimisation
No full textBusiness process redesign and improvement has become an increasingly attractive subject in the wider area of business process intelligence. Although there have been many attempts to establish a business process redesign framework, there is little work on the actual optimisation of business processes with given objectives. Furthermore, most of the attempts to optimise a business process are manual and do not involve a formal automated methodology. This paper proposes a process improvement approach for automated multi-objective optimisation of business processes. The proposed framework uses a generic business process model that is formally defined. The formal definition of business processes is necessary to ensure that the optimisation will take place in a clearly defined, repeatable and verifiable way. Multi-objectivity is expressed in terms of process cost and duration as two key objectives for any business process. The business process model is programmed and incorporated into a software optimisation platform where a selection of multi-objective optimisation algorithms can be applied to a business process design. This paper outlines a case study of business process design that is optimised by the state-of-the-art multi-objective optimisation algorithm NSGA2. The results indicate that, although business process optimisation is a highly constrained problem with fragmented search space, a number of alternative optimised business processes that meet the optimisation criteria can be produced. The paper also provides directions for future research in this area
Algorithms Applied to Global Optimisation – Visual Evaluation
No full textEvaluation and assessment of various search and optimisation algorithms is subject of large research efforts. Particular interest of this study is global optimisation and presented approach is based on observation and visual evaluation of Real-Coded Genetic Algorithm, Particle Swarm Optimisation, Differential Evolution and Free Search, which are briefly described and used for experiments. 3D graphical views, generated by visualisation tool VOTASA, illustrate essential aspects of global search process such as divergence, convergence, dependence on initialisation and utilisation of accidental events. Discussion on potential benefits of visual analysis, supported with numerical results, which could be used for comparative assessment of other methods and directions for further research conclude presented study
Optimisation-based clearance
No full textThe basic feature of the optimisation-based clearance approach is to reformulate the clearance problems as equivalent minimum distance problems for which ”anti”-optimisation is performed to determine the worst-case parameter combination/ flight condition leading to worst performance. The basic requirements for the applicability of the optimisation-based approach are the availability of suitable parametric models describing the overall nonlinear dynamics of the augmented aircraft and of accompanying effcient and reliable trimming, linearisation and optimisation software tools. The optimisation-based approach has no limitations with respect to clearance criteria, being able to address all kind of clearance requirements which are expressible as mathematical criteria
Multi-objective optimisation of web business processes
No full textThis paper proposes an approach for the optimisation of web business processes
using multi-objective evolutionary computing. Business process optimisation is
considered as the problem of constructing feasible business process designs with
optimum attribute values such as duration and cost. This optimisation framework
involves the application of a series of Evolutionary Multi-objective
Optimisation Algorithms (EMOAs) in an attempt to generate a series of diverse
optimised business process designs for given requirements. The optimisation
framework is tested to validate the framework's capability in capturing,
composing and optimising business process designs constituted of web services.
The results from the web business process optimisation scenario, featured in
this paper, demonstrate that the framework can identify business process designs
with optimised attribute values
Simulation-Based Fitness Landscape Analysis and Optimisation of Complex Problems
No full textWidespread hard optimisation problems in economics and logistics are characterised by large dimensions, uncertainty and nonlinearity and require more powerful methods of stochastic optimisation that traditional ones. Simulation optimisation is a powerful tool for solving these problems. Moreover, fitness landscape analysis techniques provide an efficient approach to better selection of a suitable optimisation algorithm. The concept and techniques of fitness landscape analysis are described. A formalised scheme for simulation optimisation enhanced with fitness landscape analysis is given. Benchmark fitness landscape analysis is performed to find relations between efficiency of an optimisation algorithm and structural features of a fitness landscape. Case study in simulation optimisation of vehicle routing and scheduling is described. Various optimisation scenarios with application of the fitness landscape analysis are discussed and investigated
Smooth boundary topology optimisation applied to an electrostatic actuator
No full textSmooth boundary topology optimisation in conjunction with the continuum design sensitivity analysis avoids many of the problems encountered by conventional cell-based systems coupled with material homogenisation or the density method. Shape optimisation becomes part of topology optimisation. The effectiveness of the proposed method is demonstrated through the design of an electrostatic MEMS actuator to generate maximum torque for a predefined maximum size (area)
Optimisation of Combustor Wall Heat Transfer and Pollutant Emissions for Preliminary Design Using Evolutionary Techniques
No full textThis paper presents the concept and application of a design optimisation toolbox, based
upon evolutionary techniques, for the preliminary design of a gas turbine combustor.
The toolbox has been designed to interface with existing analysis packages and to
perform optimisation in parallel over a heterogeneous network of workstations. The
optimisation capabilities of the toolbox are demonstrated for gas turbine combustor
design by automatically attaining twenty-two performance targets in a combustor design
whilst performing minimisation of wall cooling flow and NOx emissions
Handling integrated quantitative and qualitative search space in engineering design optimisation problems
No full textSince information in engineering design problems can be both quantitative (QT)
and qualitative (QL) in nature, combining both types of information can result
in more realistic solutions for real world optimisation problems. However, most
of the approaches reported in the literature are incapable of conducting
optimisation searches in such a mixed environment. Therefore this report
proposes a mathematically proven methodology for handling integrated QT and QL
search space in real world optimisation problems. The report begins by
presenting the definition of these optimisation problems, an analysis of the
challenges that they pose for existing optimisation strategies and related
research. The report then presents the proposed solution strategy and the
mathematical proof. Furthermore, a case study on a rod rolling problem is
presented to validate the effectiveness of the proposed methodology. The report
concludes with a brief outline of limitations and future research activities
Work roll system optimisation using thermal analysis and genetic algroithm
No full textIn today‟s highly competitive business environment it is vital to have smart and robust decision making framework for companies to be competitive or even to stay in the business. Profit margin increases is no longer a result of producing and bring more products to the market. Instead it is also a result of reducing cost, in particular tooling cost. In order to succeed with this, industry need to look in to innovative intelligent systems to enhance their process development so that maximum utilisation of tools can be achieved. Tooling is part of a process hence having an optimal process design is one ideal strategy for best utilising of tools. In design optimisation however presence of uncertainty in design variables and in the mathematical model (used for representing the real life process) is inevitable. For reliable design solution to be found this process complexity need to be addressed. The aim of this research is to understand work roll system optimisation and thermal issues within rolling system design, understand uncertainties and sources of uncertainties and develop Genetic Algorithm (GA) based solution frameworks so that a conscious decision, that prolong tool life can be made.
The thesis has proposed a framework for generating approximate models from numeric finite element (FE) data. Using the proposed framework a number of quantitative work roll system thermal analysis and optimisation models were generated and used in subsequent optimisation process. In the absence of a suitable multi-pass model that exhibits the features of a multi-stage process; confident decision making will not be possible. Hence the research has developed a quantitative multi-pass model to simulate the work roll system thermal analysis and optimisation problem that represents the relationships as well as inherited features between passes.
The research has developed a Genetic Algorithm based optimisation framework that deals with the constraint quantitative problem as well as the uncertainty, in the design space and fitness function. The research also proposed a post GA result analysis methodology for identifying the final best optimal design solution for the research many objective high dimensional work roll system problems in presence of uncertainty
The performance of the proposed frameworks was studied and analysed through case studies. The research also identifies future research directions in the subject area
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