A pre-processing optimisation is proposed that can be applied to the integer and mixed integer linear programming models that are used to solve the cell suppression problem in statistical disclosure control. In this paper we report our initial findings and acknowledge that there is much more work to be done. Early indications are that the preprocessing optimisation will considerably reduce the ...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...

This thesis develops a registration algorithm specifically for diffusion-tensor (DT) im­ ages. The proposed approach matches the tensor orientations to find the registration transformation. Early results show that local optimisation does not find the global minimum in registration of DT-MR brain images. Therefore, a global optimisation re­ gistration technique is also implemented. This thesis p...

Evolutionary algorithms are a commonly applied optimisation approach in water distribution systems. However, the algorithms are time consuming when applied to large optimisation problems. The aim of this paper is to evaluate the application of a penalty-free multi-objective evolutionary optimisation algorithm to solve a real-world network design problem. The optimization model uses pressure-dep...

The choice of an adequate representation is an important part of every evolutionary design optimisation. A exible representation which allows a huge number of design variation while getting along with a few parameters is preferable. In the past the Free-From Deformation method was successfully applied for design optimisation. In this diploma thesis an adaptive Free-Form Deformation is combined ...

In this paper, we model the optimisation of the resource allocation in cloud computing as a constraint satisfaction problem considering three types of resources (CPU, RAM and bandwidth) and design a Choco-Based algorithm (CB) for VM resource allocation in virtualised cloud data centres. We also propose an Improved First-Fit Decreasing Algorithm (IFFD) and an Improved Best-Fit Decreasing Algorit...

The problem of service composition is of key importance in the Internet of Things paradigm. A composite Web Service can clearly determine how real life objects described as Web Services could interact with each other. This article proposes a non-functional parameters aggregation algorithm, used in composite service plan optimisation stage, taking into account the uncertainty of the non-function...

−We investigate the performance of a classical constrained optimisation (CCO) algorithm and a constrained optimisation Genetic Algorithm (GA) for solving the Bandwidth Allocation for Virtual Paths (BAVP) problem. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCOBAVP are ...

The current state of traditional software development is surveyed and essential problems are investigated on the basis of empirical data and theoretical considerations. The concept of optimisation cycle is proposed as a solution. The relation of several different kinds of local optimisation cycles to the specifications, the communications, and the optimisation problem is integrated into a conce...