|Appears in Collections:||Computing Science and Mathematics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||A methodology for determining an effective subset of heuristics in selection hyper-heuristics|
|Authors:||Soria-Alcaraz, Jorge A|
Burke, Edmund K
Iterated Local Search
|Citation:||Soria-Alcaraz JA, Ochoa G, Sotelo-Figeroa M & Burke EK (2017) A methodology for determining an effective subset of heuristics in selection hyper-heuristics, European Journal of Operational Research, 260 (3), pp. 972-983.|
|Abstract:||We address the important step of determining an effective subset of heuristics in selection hyper-heuristics. Little attention has been devoted to this in the literature, and the decision is left at the discretion of the investigator. The performance of a hyper-heuristic depends on the quality and size of the heuristic pool. Using more than one heuristic is generally advantageous, however, an unnecessary large pool can decrease the performance of adaptive approaches. Our goal is to bring methodological rigour to this step. The proposed methodology uses non-parametric statistics and fitness landscape measurements from an available set of heuristics and benchmark instances, in order to produce a compact subset of effective heuristics for the underlying problem. We also propose a new iterated local search hyper-heuristic usingmulti-armed banditscoupled with a change detection mechanism. The methodology is tested on two real-world optimisation problems: course timetabling and vehicle routing. The proposed hyper-heuristic with a compact heuristic pool, outperforms state-of-the-art hyper-heuristics and competes with problem-specific methods in course timetabling, even producing new best-known solutions in 5 out of the 24 studied instances.|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Soria-Alcaraz JA, Ochoa G, Sotelo-Figeroa M & Burke EK (2017) A methodology for determining an effective subset of heuristics in selection hyper-heuristics, European Journal of Operational Research, 260 (3), pp. 972-983. DOI: 10.1016/j.ejor.2017.01.042 © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
|EJORMethodologySelHH2017 (1).pdf||329.52 kB||Adobe PDF||Under Embargo until 30/1/2019 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.