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Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Author(s): Wu, Xiuli
Consoli, Pietro
Minku, Leandro
Ochoa, Gabriela
Yao, Xin
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Title: An Evolutionary Hyper-heuristic for the Software Project Scheduling Problem
Editor(s): Handl, J
Hart, E
Lewis, PR
Lopez-Ibanez, M
Ochoa, G
Paechter, B
Citation: Wu X, Consoli P, Minku L, Ochoa G & Yao X (2016) An Evolutionary Hyper-heuristic for the Software Project Scheduling Problem. In: Handl J, Hart E, Lewis P, Lopez-Ibanez M, Ochoa G & Paechter B (eds.) Parallel Problem Solving from Nature - PPSN XIV. Lecture Notes in Computer Science, 9921. International Conference on Parallel Problem Solving from Nature 2016: PPSN XIV, Edinburgh, 17.09.2016-21.09.2017. Cham, Switzerland: Springer Verlag, pp. 37-47.
Issue Date: 2016
Series/Report no.: Lecture Notes in Computer Science, 9921
Conference Name: International Conference on Parallel Problem Solving from Nature 2016: PPSN XIV
Conference Dates: 2016-09-17 - 2017-09-21
Conference Location: Edinburgh
Abstract: Software project scheduling plays an important role in reducing the cost and duration of software projects. It is an NP-hard combinatorial optimization problem that has been addressed based on single and multi-objective algorithms. However, such algorithms have always used fixed genetic operators, and it is unclear which operators would be more appropriate across the search process. In this paper, we propose an evolutionary hyper-heuristic to solve the software project scheduling problem. Our novelties include the following: (1) this is the first work to adopt an evolutionary hyper-heuristic for the software project scheduling problem; (2) this is the first work for adaptive selection of both crossover and mutation operators; (3) we design different credit assignment methods for mutation and crossover; and (4) we use a sliding multi-armed bandit strategy to adaptively choose both crossover and mutation operators. The experimental results show that the proposed algorithm can solve the software project scheduling problem effectively.
Status: VoR - Version of Record
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