Struct Online

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

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

impl<'a, P> Online<P>

where P: DiscretizableProblem,

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

Discretize online problem.

impl<'a, P> Online<P>

where P: RelaxableProblem,

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

Relax online problem.

impl<'a, T> Online<SmoothedLoadOptimization<T>>

where T: Value<'a>,

pub fn into_sblo(self) -> Online<SmoothedBalancedLoadOptimization<'a, T>>

impl<'a, T> Online<SmoothedBalancedLoadOptimization<'a, T>>

where T: Value<'a>,

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

impl<'a, T, C, D> Online<SimplifiedSmoothedConvexOptimization<'a, T, C, D>>

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

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

impl<'a, P> Online<P>

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<P>, &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.

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<P>, &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.

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.

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. $t_end \geq 1$.

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.

impl<'a, P> Online<P>

where P: VerifiableProblem,

pub fn verify(&self) -> Result<()>

Trait Implementations

impl<P: Clone> Clone for Online<P>

fn clone(&self) -> Online<P>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<P: Debug> Debug for Online<P>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.