Research explorer tool

37 results

Incorporating emissions models within a multi-objective vehicle routing problem.

Conference Proceeding
Urquhart, N. B., Scott, C., & Hart, E. (2013)
Incorporating emissions models within a multi-objective vehicle routing problem. In C. Blum (Ed.), GECCO'13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation, (193-194). https://doi.org/10.1145/2464576.2464663
The vehicle routing problem with time windows (VRPTW) has previously been investigated as a multi-objective problem. In this paper estimated carbon emissions is added as an ob...

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...

On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system.

Conference Proceeding
Hart, E., & Sim, K. (2014)
On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system. In Proceedings of PPSN, 13th International Conference on Parallel problem Solving from Nature, (282-291). https://doi.org/10.1007/978-3-319-10762-2_28
Real-world applications of optimisation techniques place more importance on finding approaches that result in acceptable quality solutions in a short time-frame and can provid...

A comparison of dominance mechanisms and simple mutation on non-stationary problems.

Conference Proceeding
Lewis, J., Hart, E., & Ritchie, G. (1998)
A comparison of dominance mechanisms and simple mutation on non-stationary problems. In Parallel Problem Solving from Nature-PPSN V. , (139-148). https://doi.org/10.1007/BFb0056857
It is sometimes claimed that genetic algorithms using diploid representations will be more suitable for problems in which the environment changes from time to time, as the add...

Algorithm selection using deep learning without feature extraction

Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...

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...

A novel similarity-based mutant vector generation strategy for differential evolution

Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018)
A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018https://doi.org/10.1145/3205455.3205628
The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the...

An improved immune inspired hyper-heuristic for combinatorial optimisation problems.

Conference Proceeding
Sim, K., & Hart, E. (2014)
An improved immune inspired hyper-heuristic for combinatorial optimisation problems. In C. Igel (Ed.), Proceedings of GECCO 2014 (Genetic and Evolutionary Computation Conference) (121-128). https://doi.org/10.1145/2576768.2598241
The meta-dynamics of an immune-inspired optimisation sys- tem NELLI are considered. NELLI has previously shown to exhibit good performance when applied to a large set of optim...

Using graphical information systems to improve vehicle routing problem instances.

Conference Proceeding
Urquhart, N. B., Scott, C., & Hart, E. (2013)
Using graphical information systems to improve vehicle routing problem instances. In C. Blum (Ed.), GECCO'13 Companion, (1097-1102). https://doi.org/10.1145/2464576.2466802
This paper makes the assertion that vehicle routing rearch has produced increasingly more powerful problem solvers, but has not increased the realism or compexity of typical p...

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...