The SHOT solver is best described in the following paper:

Lundell, A., Kronqvist, J. and Westerlund T. The Supporting Hyperplane Optimization Toolkit for Convex MINLP. Optimization Online (2020).

The nonconvex features are described in:

Lundell, A. and Kronqvist, J., Polyhedral approximation strategies for nonconvex mixed-integer nonlinear programming in SHOT. Journal of Global Optimization (2021).
Please cite these papers if you use SHOT for research purposes.

Additional relevant publications include:

    Kronqvist, J., Lundell, A. and Westerlund, T. The extended supporting hyperplane algorithm for convex mixed-integer nonlinear programming. Journal of Global Optimization (2016) 64: 249.
    Lundell, A., Kronqvist, J. and Westerlund, T. Improvements to the Supporting Hyperplane Optimization Toolkit Solver for Convex MINLP, Proceedings of the XIII Global Optimization Workshop GOW’16 (2016).
    Kronqvist, J., Bernal, D.E, Lundell, A. and Grossmann, I.E. A review and comparison of solvers for convex MINLP. Optimization and Engineering 20(2), pp. 397-455 (2018).
    Lundell, A. and Kronqvist, J. On Solving Nonconvex MINLP Problems with SHOT (2019). In: Le Thi H., Le H., Pham Dinh T. (editors) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham.
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