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In this paper, we present a fast and easy-to-use optimization model to find cost-optimal ways to manage the energy system with large-scale VRE.
Regression models were fitted to refrigeration and electrical powers and optimal variable settings were identified using an easy-to-use optimization criterion.
First, very efficient and fast algorithms for solving convex problems have been developed and implemented, which makes convex optimization easy to use in practical wireless communication systems.
For first optimization attempts, the easy to use Tribes algorithm is a good choice.
These methods are essentially all local optimization techniques, familiar and easy to use.
The combination of visualization, user interaction, and stochastic optimization results in a robust and easy to use tool for heat integrated process design.
The program is easy to use for engineers who may not be familiar with either FEA or structure optimization.
The algorithm is simple, easy to use and has shown better global convergence and robustness than most other genetic algorithms, suitable for various optimization problems [2].
First, the model is easy to use, even for programmers without experience with distributed systems, since it hides the details of parallelization, fault-tolerance, locality optimization and load balancing.
Very easy to use.
It's easy to use.
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