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A first augmented Lagrangian method for binary QCQP problems based on a class of continuous functions

Nirakar Sahoo & Rupaj Kumar Nayak

International Journal of Operational Research2026https://doi.org/10.1504/ijor.2026.151741article
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What the paper says

This paper addresses the solution of a non-convex 0-1 QCQP using two faster convergent augmented Lagrangian methods (ALM) based on a class of continuous functions and a parameter free convexification method. The binary constraints are converted into a class of continuous functions and the non-convex constraints are convexified by a parameter free method. The proposed algorithm is then tested on a set of QCQP problems available in the research of Zheng and co-workers. We also present the comparison results among relaxed versions of SDPs and some state-of-the-art ALMs and obtained an advantage over their counterparts.

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https://doi.org/https://doi.org/10.1504/ijor.2026.151741

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@article{nirakar2026,
  title        = {{A first augmented Lagrangian method for binary QCQP problems based on a class of continuous functions}},
  author       = {Nirakar Sahoo & Rupaj Kumar Nayak},
  journal      = {International Journal of Operational Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijor.2026.151741},
}

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A first augmented Lagrangian method for binary QCQP problems based on a class of continuous functions

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F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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R · text relevance †0.50 × 0.4 = 0.20

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