Research explorer tool

4 results

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 new rich vehicle routing problem model and benchmark resource

Conference Proceeding
Sim, K., Hart, E., Urquhart, N. B., & Pigden, T. (2018)
A new rich vehicle routing problem model and benchmark resource. In Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Scienceshttps://doi.org/10.1007/978-3-319-89988-6_30
We describe a new rich VRP model that captures many real-world constraints, following a recently proposed taxonomy that addresses both scenario and problem physical characteri...

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 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...