this paper proposes an optimal power flow (opf) algorithm by direct load control (dlc) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. the cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with dlc programs. the load curtailment cost is based ...

We propose a prooling tool for experimental evaluation of garbage collection algorithms. Behaviour of the prooler is determined by some probability distributions on object size and life time etc. that are derived from the properties of certain languages or applications. A standard memory management interface allows precise, objective evaluation of several garbage collection algorithms under lab...

Cost-optimal planning is a very well-studied topic within planning, and it has proven to be computationally hard both in theory practice. Since cost-optimal an optimisation problem, natural analyse through the lens of approximation. An important reason for studying heuristic search; functions that guide search can often viewed as algorithms solving or approximating certain problems. Many (such ...

This paper is a survey about recent results on sparse representations and optimal models in different settings. Given a set of functions, we show that there exists an optimal collection of subspaces minimizing the sum of the square of the distances between each function and its closest subspace in the collection. Further, this collection of subspaces gives the best sparse representation for the...

In transportation planning there can be long lead times to adapt capacity. This paper addresses two questions. First, in a one mode world (say rail or road), what is the optimal capacity choice when faced with uncertain demand, long lead times and congestion. Using a simple analytical model it is shown that when demand is inelastic, it is socially optimal to invest more than if only the expecte...