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An iterative RA algorithm is proposed to optimize mode selection (decision whether the relay should help or not), subcarrier assignment (MSSA) and power allocation (PA) alternatively.
An iterative semi-distributed resource allocation (RA) algorithm is first proposed to optimize mode selection (decision whether relaying should be used or not and which relay), subcarrier assignment (MSSA), and power allocation (PA), alternatively.
To solve this problem, an iterative RA algorithm is proposed to optimize mode selection (decision whether the relay should help or not), subcarrier assignment and pairing (MSSAP) and power allocation (PA) in an alternate way.
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The IES is responsible for generating mode choice decision.
These decisions include transportation mode selection, inventory policies, production decisions, supplier selection and so on.
Additionally just three of them integrate the transportation mode selection issues as tactical decisions with strategic network design decisions.
According to the presented literature and Table 1 some drawbacks are found in closed loop supply chain network design area, such as ambiguous of decision variables, considering of more echelons, making tactical decisions, regarding transportation mode selection and so on.
To mitigate the effect of overestimation, the encoder first applies a band-level mode decision process, referred to as skip mode selection.
Under the partially observable Markov decision process framework, we propose an optimal mode selection policy for the distributed secondary users.
Furthermore, and given the extra time that you obtain when combining different approaches for reducing the amount of computational time needed for the ME and compensated process (fast inter mode selection, MV refinement techniques, etc)., it is possible to let the decision tree be more flexible in the MB coding mode selection.
By an adaptive DCT mode selection scheme, several highly discriminative DCT modes are selected.
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