All Outputs (24)

Special issue on explainable AI in evolutionary computation. (2024)
Journal Article
BACARDIT, J., BROWNLEE, A., CAGNONI, S., IACCA, G., MCCALL, J. and WALKER, D. (eds.) 2024. Special issue on explainable AI in evolutionary computation. ACM transactions on evolutionary learning and optimization [online], 4(1). Available from: https://dl.acm.org/toc/telo/2024/4/1

Explainable Artificial Intelligence (XAI) has recently emerged as one of the most active areas of research in AI. While Evolutionary Computation (EC) is also a very active research area, the intersection between XAI and EC is still rather unexplored.... Read More about Special issue on explainable AI in evolutionary computation..

Bi-level optimisation and machine learning in the management of large service-oriented field workforces. (2022)
Thesis
AINSLIE, R.T. 2022. Bi-level optimisation and machine learning in the management of large service-oriented field workforces. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1880200

The tactical planning problem for members of the service industry with large multi-skilled workforces is an important process that is often underlooked. It sits between the operational plan - which involves the actual allocation of members of the wor... Read More about Bi-level optimisation and machine learning in the management of large service-oriented field workforces..

Holistic, data-driven, service and supply chain optimisation: linked optimisation. (2022)
Thesis
OGUNSEMI, A. 2022. Holistic, data-driven, service and supply chain optimisation: linked optimisation. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1987884

The intensity of competition and technological advancements in the business environment has made companies collaborate and cooperate together as a means of survival. This creates a chain of companies and business components with unified business obje... Read More about Holistic, data-driven, service and supply chain optimisation: linked optimisation..

Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. (2019)
Thesis
ANKRAH, R.B. 2019. Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The location-allocation (LA) problem concerns the location of facilities and the allocation of demand, to minimise or maximise a particular function such as cost, profit or a measure of distance. Many formulations of LA problems have been presented i... Read More about Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry..

Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. (2018)
Thesis
AYODELE, M. 2018. Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. Robert Gordon University, PhD thesis.

Estimation of Distribution Algorithm (EDA) is a branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables which may give useful, human-un... Read More about Effective and efficient estimation of distribution algorithms for permutation and scheduling problems..

Simulation and optimisation of the separation process in offshore oil and gas platforms. (2017)
Thesis
VELESHKI, S. 2017. Simulation and optimisation of the separation process in offshore oil and gas platforms. Robert Gordon University, MRes thesis.

Hydrocarbon separation in offshore oil and gas platforms is the process that transforms extracted crude oil into transportable oil and gas. Temperatures and pressures of the separation system can be adjusted to modify the separation of the hydrocarbo... Read More about Simulation and optimisation of the separation process in offshore oil and gas platforms..

The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance. (2016)
Thesis
CHRISTIE, L.A. 2016. The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance. Robert Gordon University, PhD thesis.

Optimisation heuristics rely on implicit or explicit assumptions about the structure of the black-box fitness function they optimise. A review of the literature shows that understanding of structure and linkage is helpful to the design and analysis o... Read More about The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance..

Generating easy and hard problems using the proximate optimality principle. [Dataset] (2015)
Data
MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2015. Generating easy and hard problems using the proximate optimality principle. [Dataset]

These data were gathered to investigate the hypothesis that coherent functions will be easy and anti-coherent functions will be hard for a hillclimber. We generated 10 coherent functions for each length on bit-strings of length 6-100 and the same num... Read More about Generating easy and hard problems using the proximate optimality principle. [Dataset].

Autonomic behavioural framework for structural parallelism over heterogeneous multi-core systems. (2015)
Thesis
GOLI, M. 2015. Autonomic behavioural framework for structural parallelism over heterogeneous multi-core systems. Robert Gordon University, PhD thesis.

With the continuous advancement in hardware technologies, significant research has been devoted to design and develop high-level parallel programming models that allow programmers to exploit the latest developments in heterogeneous multi-core/many-co... Read More about Autonomic behavioural framework for structural parallelism over heterogeneous multi-core systems..

Adaptive heterogeneous parallelism for semi-empirical lattice dynamics in computational materials science. (2015)
Thesis
GARBA, M. 2015. Adaptive heterogeneous parallelism for semi-empirical lattice dynamics in computational materials science. Robert Gordon University, PhD thesis.

With the variability in performance of the multitude of parallel environments available today, the conceptual overhead created by the need to anticipate runtime information to make design-time decisions has become overwhelming. Performance-critical a... Read More about Adaptive heterogeneous parallelism for semi-empirical lattice dynamics in computational materials science..

Computational aspects of cellular intelligence and their role in artificial intelligence. (2014)
Thesis
GERRARD, C.E. 2014. Computational aspects of cellular intelligence and their role in artificial intelligence. Robert Gordon University, PhD thesis.

The work presented in this thesis is concerned with an exploration of the computational aspects of the primitive intelligence associated with single-celled organisms. The main aim is to explore this Cellular Intelligence and its role within Artificia... Read More about Computational aspects of cellular intelligence and their role in artificial intelligence..

Multi-objective particle swarm optimisation: methods and applications. (2014)
Thesis
AL MOUBAYED, N. 2014. Multi-objective particle swarm optimisation: methods and applications. Robert Gordon University, PhD thesis.

Solving real life optimisation problems is a challenging engineering venture. Since the early days of research on optimisation it was realised that many problems do not simply have one optimisation objective. This led to the development of multi-obje... Read More about Multi-objective particle swarm optimisation: methods and applications..

The asset replacement problem state of the art. (2013)
Book Chapter
ANSARIPOOR, A.H., OLIVEIRA, F.S. and LIRET, A. 2013. The asset replacement problem state of the art. In Owusu, G., O'Brien, P., McCall, J. and Doherty, N.F. (eds.) Transforming field and service operations: methodologies for successful technology-driven business transformation. Berlin: Springer [online], chapter 14, pages 213-233. Available from: https://doi.org/10.1007/978-3-642-44970-3_14

This book chapter outlines the different modelling approaches for realising sustainable operations of asset replacement and studying the impact of the economic life, the repair-cost limit and comprehensive cost minimisation models. In particular it a... Read More about The asset replacement problem state of the art..

Experimental user interface design toolkit for interaction research (IDTR). (2013)
Thesis
GOLOVINE, J.C.R.R. 2013. Experimental user interface design toolkit for interaction research (IDTR). Robert Gordon University, PhD thesis.

The research reported and discussed in this thesis represents a novel approach to User Interface evaluation and optimisation through cognitive modelling. This is achieved through the development and testing of a toolkit or platform titled Toolkit for... Read More about Experimental user interface design toolkit for interaction research (IDTR)..

Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment. (2013)
Thesis
REGNIER-COUDERT, O. 2013. Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment. Robert Gordon University, PhD thesis.

Over the last decades, Bayesian Networks (BNs) have become an increasingly popular technique to model data under presence of uncertainty. BNs are probabilistic models that represent relationships between variables by means of a node structure and a s... Read More about Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment..

Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence. (2013)
Thesis
FOURNIER, F.A. 2013. Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

This work investigates the use of evolved Bayesian networks learning algorithms based on computational intelligence meta-heuristic algorithms. These algorithms are applied to a new domain provided by the exclusive data, available to this project from... Read More about Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence..

Approximating true relevance model in relevance feedback. (2013)
Thesis
ZHANG, P. 2013. Approximating true relevance model in relevance feedback. Robert Gordon University, PhD thesis.

Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundamental IR task. It involves not only document relevance estimation, but also estimation of user's information need. Relevance-based language model aims... Read More about Approximating true relevance model in relevance feedback..

Problem dependent metaheuristic performance in Bayesian network structure learning. (2012)
Thesis
WU, Y. 2012. Problem dependent metaheuristic performance in Bayesian network structure learning. Robert Gordon University, PhD thesis.

Bayesian network (BN) structure learning from data has been an active research area in the machine learning field in recent decades. Much of the research has considered BN structure learning as an optimization problem. However, the finding of optimal... Read More about Problem dependent metaheuristic performance in Bayesian network structure learning..

A sequence-length sensitive approach to learning biological grammars using inductive logic programming. (2011)
Thesis
MAMER, T. 2011. A sequence-length sensitive approach to learning biological grammars using inductive logic programming. Robert Gordon University, PhD thesis.

This thesis aims to investigate if the ideas behind compression principles, such as the Minimum Description Length, can help us to improve the process of learning biological grammars from protein sequences using Inductive Logic Programming (ILP). Con... Read More about A sequence-length sensitive approach to learning biological grammars using inductive logic programming..

Multivariate Markov networks for fitness modelling in an estimation of distribution algorithm. (2009)
Thesis
BROWNLEE, A.E.I. 2009. Multivariate Markov networks for fitness modelling in an estimation of distribution algorithm. Robert Gordon University, PhD thesis.

A well-known paradigm for optimisation is the evolutionary algorithm (EA). An EA maintains a population of possible solutions to a problem which converges on a global optimum using biologically-inspired selection and reproduction operators. These alg... Read More about Multivariate Markov networks for fitness modelling in an estimation of distribution algorithm..