Iterated local search using an add and delete hyper- heuristic for university course timetabling

Soria-Alcaraz, Jorge A., Özcan, Ender, Swan, Jerry, Kendall, Graham and Carpio, Martin (2016) Iterated local search using an add and delete hyper- heuristic for university course timetabling. Applied Soft Computing, 40 . pp. 581-593. ISSN 1872-9681

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Hyper-heuristics are (meta-)heuristics that operate at a higher level to choose or generate a set of low-level (meta-)heuristics in an attempt of solve difficult optimization problems. Iterated local search (ILS) is a well-known approach for discrete optimization, combining perturbation and hill-climbing within an iterative framework. In this study, we introduce an ILS approach, strengthened by a hyper-heuristic which generates heuristics based on a fixed number of add and delete operations. The performance of the proposed hyper-heuristic is tested across two different problem domains using real world benchmark of course timetabling instances from the second International Timetabling Competition Tracks 2 and 3. The results show that mixing add and delete operations within an ILS framework yields an effective hyper-heuristic approach.

Item Type: Article
Keywords: Benchmarking; Heuristic methods; Iterative methods; Local search (optimization); Scheduling, Add-delete list; Discrete optimization; Hyperheuristic; Iterated local search; Iterative framework; Optimization problems; Timetabling; University Course Timetabling, Optimization
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number:
Depositing User: Ozcan, Dr Ender
Date Deposited: 10 Mar 2016 12:00
Last Modified: 04 May 2020 20:03

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