All Outputs (26)

Acoustic topology optimisation using CMA-ES (2020)
Conference Proceeding

Structural topology optimisation techniques are increasingly being applied to acoustic materials. Most acoustic topology optimisation applications use the solid-isotropic-material-with-penalization (SIMP) approach [1]–[4] which is a derivative-based... Read More about Acoustic topology optimisation using CMA-ES.

Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem (2020)
Conference Proceeding

This study presents an offline learning Simulated Annealing approach to generate a constructive hyper-heuristic evaluated through training and testing on a set of instances for solving the Job-Shop Scheduling problem. The generated hyperheuristic use... Read More about Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem.

Metaheuristic optimisation of sound absorption performance of multilayered porous materials (2019)
Conference Proceeding

The optimization of multilayered-sound-packaging is a challenging task which involves searching the best/op-timal settings for a number of acoustic parameters. The search space size becomes too large to handle by brute force, as the number of those p... Read More about Metaheuristic optimisation of sound absorption performance of multilayered porous materials.

Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures (2019)
Conference Proceeding

In order to fully exploit the benefits provided by using composite materials in large scale aerospace structures, more efficient detailed design optimisation techniques need to be developed. In the present work, the optimisation procedure is split up... Read More about Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures.

Fuzzy Hot Spot Identification for Big Data: An Initial Approach (2019)
Conference Proceeding

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of iden... Read More about Fuzzy Hot Spot Identification for Big Data: An Initial Approach.

A study on the interpretability of a fuzzy system to control an inverted pendulum (2019)
Conference Proceeding

Fuzzy systems mimic human reasoning and provide solutions to problems under uncertainty via 'computing with words'. This particular strength of fuzzy systems is often discarded in some real world applications where the fuzzy sets are designed for con... Read More about A study on the interpretability of a fuzzy system to control an inverted pendulum.

Proposal of a design pattern for embedding the concept of social forces in human centric simulation models (2018)
Conference Proceeding

There exist many papers that explain the social force model and its application for modelling pedestrian dynamics. None of these papers, however, explains how to implement the social force model in order to use it for systems simulation studies. In t... Read More about Proposal of a design pattern for embedding the concept of social forces in human centric simulation models.

Learning heuristic selection using a time delay neural network for open vehicle routing (2017)
Conference Proceeding

A selection hyper-heuristic is a search method that controls a prefixed set of low-level heuristics for solving a given computationally difficult problem. This study investigates a learning-via demonstrations approach generating a selection hyper-heu... Read More about Learning heuristic selection using a time delay neural network for open vehicle routing.

An investigation of tuning a memetic algorithm for cross-domain search (2016)
Conference Proceeding

Memetic algorithms, which hybridise evolutionary algorithms with local search, are well-known metaheuristics for solving combinatorial optimisation problems. A common issue with the application of a memetic algorithm is determining the best initial s... Read More about An investigation of tuning a memetic algorithm for cross-domain search.

Performance of selection hyper-heuristics on the extended HyFlex domains (2016)
Conference Proceeding

Selection hyper-heuristics perform search over the space of heuristics by mixing and controlling a predefined set of low level heuristics for solving computationally hard combinatorial optimisation problems. Being reusable methods, they are expected... Read More about Performance of selection hyper-heuristics on the extended HyFlex domains.

An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget (2016)
Conference Proceeding

Determining the best initial parameter values for an algorithm, called parameter tuning, is crucial to obtaining better algorithm performance; however, it is often a time-consuming task and needs to be performed under a restricted computational budge... Read More about An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget.

Ensemble move acceptance in selection hyper-heuristics (2016)
Conference Proceeding

Selection hyper-heuristics are high level search methodologies which control a set of low level heuristics while solving a given problem. Move acceptance is a crucial component of selection hyper-heuristics, deciding whether to accept or reject a new... Read More about Ensemble move acceptance in selection hyper-heuristics.

A comparative study of fuzzy parameter control in a general purpose local search metaheuristic (2016)
Conference Proceeding

There is a growing number of studies on general purpose metaheuristics that are directly applicable to multiple domains. Parameter setting is a particular issue considering that many of such search methods come with a set of... Read More about A comparative study of fuzzy parameter control in a general purpose local search metaheuristic.

Automatically designing more general mutation operators of Evolutionary Programming for groups of function classes using a hyper-heuristic (2016)
Conference Proceeding

In this study we use Genetic Programming (GP) as an offline hyper-heuristic to evolve a mutation operator for Evolutionary Programming. This is done using the Gaussian and uniform distributions as the terminal set, and arithmetic operators as the fun... Read More about Automatically designing more general mutation operators of Evolutionary Programming for groups of function classes using a hyper-heuristic.

Improving performance of a hyper-heuristic using a multilayer perceptron for vehicle routing (2015)
Conference Proceeding

A hyper-heuristic is a heuristic optimisation method which generates or selects heuristics (move operators) based on a set of components while solving a computationally difficult problem. Apprenticeship learning arises while observing the behavior of... Read More about Improving performance of a hyper-heuristic using a multilayer perceptron for vehicle routing.

Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks (2015)
Conference Proceeding

In many cases, the efficient operation of Additive Manufacturing (AM) technology relies on build volumes being packed effectively. Packing algorithms have been developed in response to this requirement. The configuration of AM build volumes is partic... Read More about Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks.

A tensor analysis improved genetic algorithm for online bin packing (2015)
Conference Proceeding

Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe... Read More about A tensor analysis improved genetic algorithm for online bin packing.

A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex (2015)
Conference Proceeding

Hyper-heuristics are search methodologies which operate at a higher level of abstraction than traditional search and optimisation techniques. Rather than operating on a search space of solutions directly, a hyper-heuristic searches a space of low-lev... Read More about A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex.

A modified choice function hyper-heuristic controlling unary and binary operators (2015)
Conference Proceeding

Hyper-heuristics are a class of high-level search methodologies which operate on a search space of low-level heuristics or components, rather than on solutions directly. Traditional iterative selection hyper-heuristics rely on two key components, a h... Read More about A modified choice function hyper-heuristic controlling unary and binary operators.

A simulated annealing approach to supplier selection aware inventory planning (2015)
Conference Proceeding

Selection of an appropriate supplier is a crucial and challenging task in the effective management of a supply chain. Also, appropriate inventory management is critical to the success of a supply chain operation. In recent years, there has been a gro... Read More about A simulated annealing approach to supplier selection aware inventory planning.