Optimal scheduling of deferrable demands with colocated stochastic supply and piecewise-linear pricing reduces to a finite set of three procrastination thresholds per demand class; a reinforcement learning algorithm learns these thresholds when distributions are unknown.
By the first order condition, and assumption A3 −π+ + q′(yT − v) > 0, which implies v∗ T = min{yT , ¯v}
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Joint Scheduling of Deferrable and Nondeferrable Demand with Colocated Stochastic Supply
Optimal scheduling of deferrable demands with colocated stochastic supply and piecewise-linear pricing reduces to a finite set of three procrastination thresholds per demand class; a reinforcement learning algorithm learns these thresholds when distributions are unknown.