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In the past decade, evolutionary methods have been used by various researchers to tackle optimal design problems for water supply systems (WSS).
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In this paper we tackle the optimal Discharge Scheduling of Energy Storage systems Problem (DSESP) in MicroGrids, considering renewable generation, and applying hyper-heuristic (HH) algorithms.
In this paper the model predictive control (MPC) technology is used for tackling the optimal drug administration problem.
The described throughput maximization problem is difficult to tackle and the optimal solution is unknown in the literature.
Controlling variability and process optimization are major issues of manufacturing processes which should be tackled together since optimal processes must be robust.
In this work, a novel surface registration framework is proposed to tackle this problem using optimal mass transport mapping (OMT-Map) and Teichmüller mapping (T-Map).
We tackle the problem using optimal control principles, aiming to minimize the perceived physical exertion while guaranteeing a predetermined electric range.
In this paper we tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions, using a novel meta-heuristic algorithm.
This paper attempts to tackle some aspects of optimal design of a 6DOF cable robot by addressing the variations of the workspace volume and the accuracy of the robot using different geometric configurations, different sizes and orientations of the moving platform.
Evolution of pressure drop, collection efficiency of particles and quality factors are the aspects, which should be tackled, to design an optimal filter structure.
In this context, optimal control tackles the question of bringing a dynamical system from one state to another with minimum expenditure of time and resources [50].
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