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Optimizing Dynamic Resource Allocation
Author(s) -
Lucas W. Krakow,
Louis Rabiet,
Yun Zou,
Guillaume Iooss,
Edwin K. P. Chong,
Sanjay Rajopadhye
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.05.115
Subject(s) - computer science , resource allocation , constant (computer programming) , acceleration , control (management) , resource (disambiguation) , distributed computing , mathematical optimization , artificial intelligence , programming language , computer network , physics , mathematics , classical mechanics
We present a formulation, solution method, and program acceleration techniques for two dynamic control scenarios, both with the common goal of optimizing resource allocations. These approaches allocate resources in a non-myopic way, accounting for long-term impacts of current control decisions via nominal belief-state optimization (NBO). In both scenarios, the solution techniques are parallelized for reduced execution time. A novel aspect is included in the second scenario: dynamically allocating the computational resources in an online fashion which is made possible through constant aspect ratio tiling (CART)

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