Automatically improving the anytime behaviour of optimisation algorithms

•A method to automatically improve the anytime behaviour of optimisation algorithms.•Anytime behaviour is evaluated by the hypervolume measure.•Decision-maker’s preferences may be incorporated into the automatic tuning procedure.•Case-studies include configuring a heuristic algorithm and an MIP solv...

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Bibliographic Details
Published in:	European journal of operational research Vol. 235; no. 3; pp. 569 - 582
Main Authors:	López-Ibáñez, Manuel, Stützle, Thomas
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 16.06.2014 Elsevier Sequoia S.A
Subjects:	Algorithms Anytime algorithms Automatic configuration Automation Computation Integer programming Mathematical models Metaheuristics Offline tuning Optimization Optimization algorithms Source code Studies Tradeoff analysis Tradeoffs Tuning Anytime algorithms Metaheuristics Automatic configuration Offline tuning
ISSN:	0377-2217, 1872-6860
Online Access:	Get full text
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