Research explorer tool

16 results

Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids

Conference Proceeding
Powers, S. T., Meanwell, O., & Cai, Z. (2019)
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids. In PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 269-272. https://doi.org/10.1007/978-3-030-24209-1_28
Reducing peak electricity consumption is important to maximise use of renewable energy sources, and reduce the total amount of capacity required on a grid. Most approaches use...

A Cooperative Learning Approach for the Quadratic Knapsack Problem

Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018)
A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12), (31-35). https://doi.org/10.1007/978-3-030-05348-2_3
The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has sever...

For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems

Conference Proceeding
Pitt, J., & Hart, E. (2017)
For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W),. https://doi.org/10.1109/fas-w.2017.119
This position paper is concerned with the challenge of engineering multi-scale and long-lasting systems, whose operation is regulated by sets of mutually-agreed, conventional ...

Impact of selection methods on the diversity of many-objective Pareto set approximations

Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017)
Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science, 112, (844-853). ISSN 1877-0509
Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultane...

The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles

Conference Proceeding
Segura, C., Segredo, E., & Miranda, G. (2017)
The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles. In 2017 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2017.7969565
In recent years, several memetic algorithms with explicit mechanisms to delay convergence have shown great promise when solving 9x9 Sudoku puzzles. This paper analyzes and ext...

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector

Conference Proceeding
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017)
A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference, (1121-1128). https://doi.org/10.1145/3071178.3071217
Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing r...

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, (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...

Artificial Immunology for Collective Adaptive Systems Design and Implementation

Journal Article
Capodieci, N., Hart, E., & Cabri, G. (2016)
Artificial Immunology for Collective Adaptive Systems Design and Implementation. ACM transactions on autonomous and adaptive systems, 11(2), 1-25. https://doi.org/10.1145/2897372
Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms to deal wi...

A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules

Conference Proceeding
Sim, K., & Hart, E. (2015)
A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules. In GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, (1485-1486). https://doi.org/10.1145/2739482.2764697
A previously described hyper-heuristic framework named NELLI is adapted for the classic Job Shop Scheduling Problem (JSSP) and used to find ensembles of reusable heuristics th...

Heaven and Hell: visions for pervasive adaptation

Journal Article
Paechter, B., Pitt, J., Serbedzija, N., Michael, K., Willies, J., & Helgason, I. (2011)
Heaven and Hell: visions for pervasive adaptation. Procedia computer science, 7, 81-82. https://doi.org/10.1016/j.procs.2011.12.025
With everyday objects becoming increasingly smart and the “info-sphere” being enriched with nano-sensors and networked to computationally-enabled devices and services, the way...