Sentence examples for optimization policies from inspiring English sources

We also did a comparison of the penalties between the local optimization policies and MILP.

Among the existing approaches, the artificial intelligence-based approaches that accumulate the operational and optimization experience and form optimization policies based on these experiences are the most promising.

From the simulation results, we conclude that our approach is able to acquire robust optimization policies for different complex scenarios and maintains a significantly better performance in terms of coverage and capacity with low energy consumption.

To prevent potential drastic changes in the network performance, the artificial intelligence approach, which can accumulate the operational and optimization experience and form optimization policies based on the experience, has significant potential [14 17].

Hoque and Goyal (2000) have studied on specifying optimization policies for the integrated system of production and inventory, which comprised a single buyer and single vendor, and have considered the following assumptions in developing this model: First, the demand rate is definite and fixed.

After evaluating a set of candidate optimization policies, inclusive of (eventual) subscription tuning, each SelfLet can pass its choices to the Actuator and inform its neighbors, following a greedy strategy, or a non-greedy one, depending on the state of surrounding SelfLets.

The optimal optimization policy can be obtained from value iteration algorithms in this formulation.

In this case, base station knows the CSI and the power constraint for each CR user and acts as a single controller to design the optimization policy for the whole network.

The authors claimed that if the energy optimization policy could be guided by power consumption prediction models, then about 20%% energy consumption could be saved for typical single site private cloud data-centers.

In Section 3, we obtain the optimal policies of our optimization problem with two cases ((hat{y}>1) or (hat{y}<1)).

All CR users can calculate the optimal policy by solving the same optimization problem (15).