An iterated multi-stage selection hyper-heuristic

Kheiri, Ahmed and Özcan, Ender (2016) An iterated multi-stage selection hyper-heuristic. European Journal of Operational Research, 250 (1). pp. 77-90. ISSN 0377-2217

PDF (EJOR2016)
EJOR2016.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (542kB)


There is a growing interest towards the design of reusable general purpose search methods that are applicable to different problems instead of tailored solutions to a single particular problem. Hyper-heuristics have emerged as such high level methods that explore the space formed by a set of heuristics (move operators) or heuristic components for solving computationally hard problems. A selection hyper-heuristic mixes and controls a predefined set of low level heuristics with the goal of improving an initially generated solution by choosing and applying an appropriate heuristic to a solution in hand and deciding whether to accept or reject the new solution at each step under an iterative framework. Designing an adaptive control mechanism for the heuristic selection and combining it with a suitable acceptance method is a major challenge, because both components can influence the overall performance of a selection hyper-heuristic. In this study, we describe a novel iterated multi-stage hyper-heuristic approach which cycles through two interacting hyper-heuristics and operates based on the principle that not all low level heuristics for a problem domain would be useful at any point of the search process. The empirical results on a hyper-heuristic benchmark indicate the success of the proposed selection hyper-heuristic across six problem domains beating the state-of-the-art approach.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
18 Nov 2017 13:48
Last Modified:
18 Sep 2023 01:17