BocopHJB 1.0.1

BocopHJB 1.0.1 is out!

The BocopHJB package implements a global optimization method. Similarly to the Dynamic Programming approach, the optimal control problem is solved in two steps. First we solve the Hamilton-Jacobi-Bellman equation satisfied by the value function of the problem. Then we simulate the optimal trajectory from any chosen initial condition.

Key features:

  • Global optimization for both deterministic and stochastic optimal control problems.
  • Handles switching between discrete modes of the system.
  • Stopping time problems can be solved using switching.
  • Built-in simulation module to recompute optimal strategies.
  • Support advanced rules to define the discrete control set.
  • Parallel execution with OpenMP.
  • Matlab/Python scripts to read the value function and simulated trajectories.

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