Abstract
In this paper, we consider the binary quadratic programming problems (\(BQP\)). The unconstrained \(BQP\) is known to be NP-hard and has many practical applications like signal processing, economy, management and engineering. Due to this reason, many algorithms have been proposed to improve its effectiveness and efficiency. In this paper, we propose a novel algorithm based on the basic algorithm proposed in [1], [2, 3] to solve problem \(BQP\) with \(Q\) being a seven-diagonal matrix. It is shown that the proposed algorithm has good performance and high efficiency. To further improve its efficiency, the neural network implementation is realized.
This work was supported by the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) under Grant 20113108120010.
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Gu, S., Peng, J., Cui, R. (2014). A Polynomial Time Solvable Algorithm to Binary Quadratic Programming Problems with Q Being a Seven-Diagonal Matrix and Its Neural Network Implementation. In: Zeng, Z., Li, Y., King, I. (eds) Advances in Neural Networks – ISNN 2014. ISNN 2014. Lecture Notes in Computer Science(), vol 8866. Springer, Cham. https://doi.org/10.1007/978-3-319-12436-0_38
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DOI: https://doi.org/10.1007/978-3-319-12436-0_38
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