Article (Scientific journals)
Tackling Large-Scale and Combinatorial Bi-level Problems with a Genetic Programming Hyper-heuristic
Kieffer, Emmanuel; Danoy, Grégoire; Bouvry, Pascal et al.
2019In IEEE Transactions on Evolutionary Computation
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Keywords :
Bi-level optimization; Genetic programming; Hyper-heuristics
Abstract :
[en] Combinatorial bi-level optimization remains a challenging topic, especially when the lower-level is a NP-hard problem. In this work, we tackle large-scale and combinatorial bi-level problems using GP Hyper-heuristics, i.e., an approach that permits to train heuristics like a machine learning model. Our contribution aims at targeting the intensive and complex lower-level optimizations that occur when solving a large-scale and combinatorial bi-level problem. For this purpose, we consider hyper-heuristics through heuristic generation. Using a GP hyper-heuristic approach, we train greedy heuristics in order to make them more reliable when encountering unseen lower-level instances that could be generated during bi-level optimization. To validate our approach referred to as GA+AGH, we tackle instances from the Bi-level Cloud Pricing Optimization Problem (BCPOP) that model the trading interactions between a cloud service provider and cloud service customers. Numerical results demonstrate the abilities of the trained heuristics to cope with the inherent nested structure that makes bi-level optimization problems so hard. Furthermore, it has been shown that training heuristics for lower-level optimization permits to outperform human-based heuristics and metaheuristics which constitute an excellent outcome for bi-level optimization.
Disciplines :
Computer science
Author, co-author :
Kieffer, Emmanuel ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Danoy, Grégoire  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Bouvry, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Nagih, Anass
External co-authors :
yes
Language :
English
Title :
Tackling Large-Scale and Combinatorial Bi-level Problems with a Genetic Programming Hyper-heuristic
Publication date :
20 March 2019
Journal title :
IEEE Transactions on Evolutionary Computation
ISSN :
1941-0026
Publisher :
Institute of Electrical and Electronics Engineers, New-York, United States - New York
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Name of the research project :
CoevolutionAry HybRid Bi-level OptimizatioN (CARBON)
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
since 25 June 2019

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