An implementation of the Simulated Annealing stochastic nonlinear optimization method.
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#include <frc/optimization/SimulatedAnnealing.h>
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| constexpr | SimulatedAnnealing (double initialTemperature, std::function< State(const State &)> neighbor, std::function< double(const State &)> cost) |
| | Constructor for Simulated Annealing that can be used for the same functions but with different initial states. More...
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| State | Solve (const State &initialGuess, int iterations) |
| | Runs the Simulated Annealing algorithm. More...
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template<typename State>
class frc::SimulatedAnnealing< State >
An implementation of the Simulated Annealing stochastic nonlinear optimization method.
- See also
- https://en.wikipedia.org/wiki/Simulated_annealing
- Template Parameters
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| State | The type of the state to optimize. |
◆ SimulatedAnnealing()
template<typename State >
| constexpr frc::SimulatedAnnealing< State >::SimulatedAnnealing |
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double |
initialTemperature, |
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std::function< State(const State &)> |
neighbor, |
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std::function< double(const State &)> |
cost |
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inlineconstexpr |
Constructor for Simulated Annealing that can be used for the same functions but with different initial states.
- Parameters
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| initialTemperature | The initial temperature. Higher temperatures make it more likely a worse state will be accepted during iteration, helping to avoid local minima. The temperature is decreased over time. |
| neighbor | Function that generates a random neighbor of the current state. |
| cost | Function that returns the scalar cost of a state. |
◆ Solve()
template<typename State >
Runs the Simulated Annealing algorithm.
- Parameters
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| initialGuess | The initial state. |
| iterations | Number of iterations to run the solver. |
- Returns
- The optimized state.
The documentation for this class was generated from the following file:
1.9.4