what methods can be used to solve a TP-BVP with variable control?

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  • torchquad

    Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX

    • What about combining a fast numerical integrator like https://github.com/esa/torchquad or https://github.com/AnyarInc/Ascent with a fast parallel CMA-ES implementation like https://github.com/dietmarwo/fast-cma-es/blob/master/fcmaes/cmaescpp.py ? A numerical integrator allows you to implement variable control and a fast non-derivative optimizer can solve any related optimization problem.

  • Ascent

    A fast and flexible C++ simulation engine and differential equation solver. (by AnyarInc)

    • What about combining a fast numerical integrator like https://github.com/esa/torchquad or https://github.com/AnyarInc/Ascent with a fast parallel CMA-ES implementation like https://github.com/dietmarwo/fast-cma-es/blob/master/fcmaes/cmaescpp.py ? A numerical integrator allows you to implement variable control and a fast non-derivative optimizer can solve any related optimization problem.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • fast-cma-es

    A Python 3 gradient-free optimization library

    • What about combining a fast numerical integrator like https://github.com/esa/torchquad or https://github.com/AnyarInc/Ascent with a fast parallel CMA-ES implementation like https://github.com/dietmarwo/fast-cma-es/blob/master/fcmaes/cmaescpp.py ? A numerical integrator allows you to implement variable control and a fast non-derivative optimizer can solve any related optimization problem.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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