# News ## Paper about SHOT published in Journal of Global Optimization **Date: February 10, 2022** The final version of the SHOT paper has been made available online. It is available as open access. Lundell, A., Kronqvist, J. and Westerlund T. *The Supporting Hyperplane Optimization Toolkit for Convex MINLP.* Journal of Global Optimization (2022). ## SHOT 1.1 released SHOT 1.1 is now available at [Github](https://github.com/coin-or/SHOT/releases/tag/releases%2F1.1.0). ### Major new features * SHOT no longer needs an external NLP solver in its primal strategy since SHOT can now call itself for solving fixed NLP problems. Activated with `Primal.FixedInteger.Solver=2`. For nonconvex problems it is still recommended to use an external NLP solver. * Partition convex nonseparable quadratic functions as separate constraints using an eigenvalue decomposition-based reformulation. Activated with `Model.Reformulation.Quadratics.UseEigenValueDecomposition=true.` * Support for performing an initial polyhedral approximation of the nonlinear feasible set before feasibility-based bound tightening. Activated with `Model.BoundTightening.InitialPOA.Use=true`. * Support for problems containing semi-continuous and semi-integer variables. * Support for problems containing special ordered sets. ### Minor improvements and bug fixes * Improved support for generating supporting hyperplanes for the entire nonlinear feasible set instead of the feasible sets for the individual constraint functions. Activated with Dual.ESH.Rootsearch.UseMaxFunction=true. * Improved support for passing nonconvex quadratic functions directly to the MIP solver (if supported). * Bug fixes for the AMPL interface. ## Open access paper about nonconvex features in SHOT **Date: March 20, 2021** The full paper about the nonconvex features in SHOT is now available online in the Journal of Global Optimization. The paper also includes some benchmarks on nonconvex MINLP and MIQCQP problems. Lundell, A. and Kronqvist, J., *Polyhedral approximation strategies for nonconvex mixed-integer nonlinear programming in SHOT.* Journal of Global Optimization (2021). ## SHOT available on the NEOS Server **Date: August 25, 2020** SHOT is now available as a solver on the NEOS Solver. You can submit jobs in GAMS format [here](https://neos-server.org/neos/solvers/minco:SHOT/GAMS.html). The NEOS (Network-Enabled Optimization System) Server is a free internet-based service for solving numerical optimization problems. Visit the [NEOS Server](https://neos-server.org/neos/) web site to access 60 state-of-the-art solvers in more than a dozen categories. ## Call SHOT through GAMS' Pyomo and JuMP interfaces **Date: July 1, 2020** If you have a licensed version of GAMS (you can also request a [free community license](https://www.gams.com/latest/docs/UG_License.html)) it is also possible to call SHOT through GAMS' Pyomo and JuMP interfaces. Read more about it [in this blog post](https://www.gams.com/blog/2020/06/new-and-improved-gams-links-for-pyomo-and-jump/) or check out the Github repositories for [GAMS.jl](https://github.com/GAMS-dev/gams.jl) or the documentation page for the [Pyomo interface](https://pyomo.readthedocs.io/en/stable/library_reference/solvers/gams.html). ## Updated version of the SHOT paper **Date: June 10, 2020** An updated preprint of the SHOT paper: Lundell, A., Kronqvist, J. and Westerlund T. *The Supporting Hyperplane Optimization Toolkit for Convex MINLP.* Optimization Online (2020). is now available. ## SHOT 1.0 released **Date: May 28, 2020** SHOT 1.0 is now available at [Github](https://github.com/coin-or/SHOT/releases/tag/releases%2F1.0.1). Binaries are available for Windows, and Linux and MacOS users can easily compile SHOT themselves using the instructions on the page [Compiling](/shot/about-shot/compiling.md). SHOT is also available in GAMS 31.1. A trial version can be [downloaded ](https://www.gams.com/download/)from GAMS. ## Preprint available about the nonconvex features in SHOT **Date: March 22, 2020** There is now a new preprint available that describes the nonconvex features in SHOT. The paper also includes some benchmarks on nonconvex MINLP and MIQCQP problems. It can be downloaded from Optimization Online: Lundell, A. and Kronqvist, J., *Polyhedral Approximation Strategies in Nonconvex Mixed-Integer Nonlinear Programming.* Optimization Online (2020). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://www.shotsolver.dev/shot/news.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.