Darren M. Chitty

Orcid: 0000-0003-2566-1182

According to our database1, Darren M. Chitty authored at least 38 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Greedy Strategies to Improve Phased Genetic Programming When Applied Directly to the Traveling Salesman Problem.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Applying a Quantum Annealer to the Traffic Assignment Problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Improving the Efficiency Of Genetic Programming for Classification Tasks Using a Phased Approach.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023
Strategies to Apply Genetic Programming Directly to the Traveling Salesman Problem.
Proceedings of the Advances in Computational Intelligence Systems, 2023

Using a Parallel Ensemble of Sequence-Based Selection Hyper-Heuristics for Electric Bus Scheduling.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

An Adaptive Sequence-Based Selection Hyper-Heuristic for Application to Electric Bus Scheduling.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Phased Genetic Programming for Application to the Traveling Salesman Problem.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022
Using Evolutionary Routing Optimisation to Transition to Electric Vehicle Fleets.
Proceedings of the Advances in Computational Intelligence Systems, 2022

Combining Edge Recombination Crossover with Ant Colony Optimisation for Improved Routing.
Proceedings of the Intelligent Systems and Applications, 2022

An edge quality aware crossover operator for application to the capacitated vehicle routing problem.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Accelerating genetic algorithm evolution via ant-based mutation and crossover for application to large-scale TSPs.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study.
Proceedings of the Artificial Evolution, 2022

2021
ACO Inspired GA Mutation Applied to the TSP.
Proceedings of the Advances in Computational Intelligence Systems, 2021

A Greedy Approach to Ant Colony Optimisation Inspired Mutation for Permutation Type Problems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

A partially asynchronous global parallel genetic algorithm.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Partial-ACO as a GA mutation operator applied to TSP instances.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

An Ant Colony Optimisation Inspired Crossover Operator for Permutation Type Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
Scalable Partial-ACO Applied to Fleet Optimisation: Sampling and Multi-Colony Approaches.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Partial-ACO Mutation Strategies to Scale-Up Fleet Optimisation and Improve Air Quality (Best Application Paper).
Proceedings of the Artificial Intelligence XXXVII, 2020

2019
Applying Partial-ACO to Large-scale Vehicle Fleet Optimisation.
CoRR, 2019

Can Bio-Inspired Swarm Algorithms Scale to Modern Societal Problems?
Proceedings of the 2019 Conference on Artificial Life, 2019

Improving Urban Air Quality Through Long-Term Optimisation of Vehicle Fleets.
Proceedings of the Intelligent Systems and Applications, 2019

Scaling ACO to large-scale vehicle fleet optimisation via partial-ACO.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

2018
Exploiting Tournament Selection for Efficient Parallel Genetic Programming.
Proceedings of the Advances in Computational Intelligence Systems, 2018

2017
Faster GPU-based genetic programming using a two-dimensional stack.
Soft Comput., 2017

Applying ACO to Large Scale TSP Instances.
Proceedings of the Advances in Computational Intelligence Systems, 2017

Considering flexibility in the evolutionary dynamic optimisation of airport security lane schedules.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Robustness and Evolutionary Dynamic Optimisation of Airport Security Schedules.
Proceedings of the Recent Advances in Soft Computing, 2017

2016
Improving the performance of GPU-based genetic programming through exploitation of on-chip memory.
Soft Comput., 2016

Evolutionary dynamic optimisation of airport security lane schedules.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Experiments with High Performance Genetic Programming for Classification Problems.
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016

2015
Improving the computational speed of genetic programming.
PhD thesis, 2015

2013
Multi-objective evolutionary auto-tuning for optimising algorithm speed and cache memory usage.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

2012
Fast parallel genetic programming: multi-core CPU versus many-core GPU.
Soft Comput., 2012

2007
A data parallel approach to genetic programming using programmable graphics hardware.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2005
Using evolutionary algorithms and dynamic programming to solve uncertain multi-criteria optimization problems with application to lifetime management for military platforms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004
A Hybrid Ant Colony Optimisation Technique for Dynamic Vehicle Routing.
Proceedings of the Genetic and Evolutionary Computation, 2004

An Evolved Autonomous Controller for Satellite Task Scheduling.
Proceedings of the Genetic and Evolutionary Computation, 2004


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