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This paper presents a multi-objective optimization model that is capable of optimizing housing design and construction decisions in order to generate optimal/near-optimal tradeoffs among the three sustainability objectives of maximizing the operational environmental performance of housing units, maximizing the social quality of life for their residents, and minimizing their life cycle cost.
The proposed optimization approach to the computation of the absorbing boundary conditions is capable of optimizing the accuracy (the absorbing quality of the boundary condition) while guaranteeing stability of the discretized partial differential equations with the absorbing boundary conditions in place.
On top of these descriptors, an adaptive framework, capable of optimizing the utility has been designed.
A simple algorithm capable of optimizing the charting parameters is also proposed.
Numerical experiments indicate that this approach is capable of optimizing the problem in acceptable computation time.
An algorithm-based system was designed which was capable of optimizing intelligent well control to sustain decision-making on whether or not to utilize intelligent well technology.
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This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically.
Due to this property these types of algorithms are potentially capable of globally optimizing any class of objective functions [2].
The proposed approach is capable of simultaneously optimizing many performance parameters viz.
Traditional tools for flexure system and compliant mechanism synthesis are not capable of simultaneously optimizing the mechanical and sensing subsystems.
As the only technology in the world capable of independently optimizing and robustly manufacturing GMP compliant precision particles of virtually any size, shape, and composition, the PRINT technology has the capability to engineer the future of healthcare.
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