Abstract
The Quadratic Multiple Knapsack Problem (QMKP) is a variant of the well-known NP-hard knapsack problem that assign profits not only to individual items but also to pairs of items. QMKP aims to maximize a quadratic objective function subject to a linear capacity constraint. In this paper, we focus on proposing a hyper-heuristic approach based in the iterated variable neighborhood descent algorithm for solving the QMKP. Numerical investigations based on well-known benchmark instances are conducted. The results clearly demonstrate the good performance of the proposed algorithm in solving the QMKP.
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Tlili, T., Yahyaoui, H., Krichen, S. (2016). An Iterated Variable Neighborhood Descent Hyperheuristic for the Quadratic Multiple Knapsack Problem. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2015. Studies in Computational Intelligence, vol 612. Springer, Cham. https://doi.org/10.1007/978-3-319-23509-7_17
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DOI: https://doi.org/10.1007/978-3-319-23509-7_17
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