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This problem can be stated mathematically as (39).
This problem can be stated as a constrained optimisation problem using Integer Linear Programming (ILP).
This problem can be stated mathematically as the following quadratic constrained optimization problem: (36).
We show how this problem can be stated as a fuzzy dynamic layout problem with growing uncertainty over time.
Formally, this problem can be stated as follows: Consider a set Γ={τ1,...τ..τ n } of N independent periodic communicating tasks.
This problem can be stated as follows.
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Very briefly, the problem can be stated as follows: it seems that in order to deny the existence of a given individual one must assume the existence of that very individual.
Therefore, the problem can be stated as a Pareto front comparison between two (or more) design concepts that only differ in their relative complexity, implementation issues, or the theory applied to solve the problem at hand.
Formally, the problem can be stated as follows: consider a video multicasting network having a scalable video stream V consisting of m video layers L = {l1, l2,..., l m } and adaptive MCS consisting of n MCSs {M1, M2,..., M n }.
But given that the problem can be stated so graphically, think what could be done by a charismatic man or woman calling the area to community action over healthy living as he or she poses under an umbrella emblazoned with the Tyneside Metro map, under the slogan: "Let's get moving", or some such.
Thus, the problem can be stated as follows: "Which are the optimal adaptation measures' combinations for achieving the maximum reductions (cost savings) of anticipated future losses on transport networks (and consequently to society) due to climate change?" This seemingly simple question conceals a large degree of complexity, because of its multidimensional character.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com