Struct soco::problem::Online

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pub struct Online<P> {
    pub p: P,
    pub w: i32,
}

Expand description

Online instance of a problem.

Fields

p: P

Problem.

w: i32

Finite, non-negative prediction window.

This prediction window is included in the time bound of the problem instance, i.e. at time $t$ $t_end$ should be set to $t + w$.

Implementations

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impl<'a, P> Online where
P: DiscretizableProblem,

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pub fn into_i(self) -> Online<P::Output>

Discretize online problem.

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impl<'a, P> Online where
P: RelaxableProblem,

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pub fn into_f(self) -> Online<P::Output>

Relax online problem.

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pub fn into_ssco(
self
) -> Online<SimplifiedSmoothedConvexOptimization<'a, T, DataCenterModelOutputSuccess, DataCenterModelOutputFailure>>

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impl<'a, T, C, D> Online<SimplifiedSmoothedConvexOptimization<'a, T, C, D>> where
 T: Value<'a>,
 C: ModelOutputSuccess + 'a,
 D: ModelOutputFailure + 'a,

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pub fn into_sco(self) -> Online<SmoothedConvexOptimization<'a, T, C, D>>

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impl<'a, P> Online

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pub fn stream<T, M, O, C, D>(
 &mut self,
 alg: &impl OnlineAlgorithm<'a, T, P, M, O, C, D>,
 update: impl Fn(&mut Online, &Schedule<T>) -> bool,
 options: O
) -> Result<(Schedule<T>, Option<M>)> where
 T: Value<'a>,
 P: Problem<T, C, D> + 'a,
 M: Memory<'a, T, P, C, D>,
 O: Options<T, P, C, D>,
 C: ModelOutputSuccess,
 D: ModelOutputFailure,

Utility to stream an online algorithm from $T = 1$.

Returns resulting schedule, final memory of the algorithm.

alg - Online algorithm to stream.
update - Callback that in each iteration updates the problem instance. Return true to continue stream, false to end stream.
options - Algorithm options.

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pub fn stream_from<T, M, O, C, D>(
 &mut self,
 alg: &impl OnlineAlgorithm<'a, T, P, M, O, C, D>,
 update: impl Fn(&mut Online, &Schedule<T>) -> bool,
 options: O,
 xs: &mut Schedule<T>,
 prev_m: Option<M>
) -> Result<Option<M>> where
 T: Value<'a>,
 P: Problem<T, C, D> + 'a,
 M: Memory<'a, T, P, C, D>,
 O: Options<T, P, C, D>,
 C: ModelOutputSuccess,
 D: ModelOutputFailure,

Stream an online algorithm from an arbitrary initial time, given the previous schedule and memory.

Returns final memory of the algorithm.

alg - Online algorithm to stream.
update - Callback that in each iteration updates the problem instance. Return true to continue stream, false to end stream.
options - Algorithm options.
xs - Schedule.
prev_m - Memory of last iteration.

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pub fn next<T, M, O, C, D>(
 &self,
 alg: &impl OnlineAlgorithm<'a, T, P, M, O, C, D>,
 options: O,
 xs: &mut Schedule<T>,
 prev_m: Option<M>
) -> Result<(Config<T>, Option<M>)> where
 T: Value<'a>,
 P: Problem<T, C, D> + 'a,
 M: Memory<'a, T, P, C, D>,
 O: Options<T, P, C, D>,
 C: ModelOutputSuccess,
 D: ModelOutputFailure,

Executes one step of an online algorithm.

alg - Online algorithm to stream.
options - Algorithm options.
xs - Schedule.
prev_m - Memory of last iteration.

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pub fn offline_stream<T, M, O, C, D>(
 &mut self,
 alg: &impl OnlineAlgorithm<'a, T, P, M, O, C, D>,
 t_end: i32,
 options: O
) -> Result<(Schedule<T>, Option<M>)> where
 T: Value<'a>,
 P: Problem<T, C, D> + 'a,
 M: Memory<'a, T, P, C, D>,
 O: Options<T, P, C, D>,
 C: ModelOutputSuccess,
 D: ModelOutputFailure,

Utility to stream an online algorithm with a constant cost function from $T = 1$.

Returns resulting schedule, final memory of the algorithm.

alg - Online algorithm to stream.
t_end - Finite time horizon. $t_end \geq 1$.

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pub fn offline_stream_from<T, M, O, C, D>(
 &'a mut self,
 alg: &impl OnlineAlgorithm<'a, T, P, M, O, C, D>,
 t_end: i32,
 options: O,
 xs: &mut Schedule<T>,
 prev_m: Option<M>
) -> Result<Option<M>> where
 T: Value<'a>,
 P: Problem<T, C, D>,
 M: Memory<'a, T, P, C, D>,
 O: Options<T, P, C, D>,
 C: ModelOutputSuccess,
 D: ModelOutputFailure,

Utility to stream an online algorithm with a constant cost function from an arbitrary initial time, given the previous schedule and memory.

Returns final memory of the algorithm.

alg - Online algorithm to stream.
t_end - Finite time horizon. Must be greater or equals to the current time slot.
xs - Schedule.
prev_m - Memory of last iteration.

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