A key component of the smart grid is the ability to enable dynamic residential pricing to incentivize the customer and the overall community to utilize energy more uniformly. However, the complications involved require that automated strategies be provided to the customer to achieve this goal. This paper presents a solution to the problem of optimally scheduling a set of residential appliances under day-ahead variable peak pricing in order to minimize the customer's energy bill (and also, simultaneously spread out energy usage). We map the problem to a well known problem in computer science - the multiple knapsack problem - which enables cheap and efficient solutions to the scheduling problem. Results show that this method is effective in meeting its goals.