A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics
Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021)
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1007/978-3-030-72069-8_6
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the doma...
On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018)
On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part Ihttps://doi.org/10.1007/978-3-319-99253-2_14
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains,...
Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm
Conference Proceeding
Hart, E., Steyven, A. S. W., & Paechter, B. (2018)
Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. In GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference, (101-108). https://doi.org/10.1145/3205455.3205481
The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad...
Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2017)
Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation, 578-593
In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heurist...
An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2017)
An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. , (155-162). https://doi.org/10.1145/3071178.3071232
A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. How...
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016)
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016 (296-305). https://doi.org/10.1007/978-3-319-50349-3_25
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic whic...
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems
Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016)
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC)https://doi.org/10.1109/CEC.2016.7743969
In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control sche...
Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2016)
Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In Parallel Problem Solving from Nature – PPSN XIV; Lecture Notes in Computer Science. , (921-931). https://doi.org/10.1007/978-3-319-45823-6_86
It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear e...
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016)
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV. , (134-144). https://doi.org/10.1007/978-3-319-45823-6_13
We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds...
Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication.
Conference Proceeding
Hart, E., Steyven, A., & Paechter, B. (2015)
Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15, (169-176). https://doi.org/10.1145/2739480.2754688
Ensuring the integrity of a robot swarm in terms of maintaining
a stable population of functioning robots over long
periods of time is a mandatory prerequisite for building mo...