To address this issue, a number of computational tools and experimental approaches have been developed to help expedite the design process to create new cellular factories.
Such methods are gaining popularity because they simplify a number of computational issues.
A numerical example is given to verify the validity of the presented formulae, and the issue of computational efficiency is addressed.
In this paper we address the key issue of computational overhead by designing new routing technique without using pre-selected list of potential forwarders.
The current paper examines the issue of computational efficiency versus degree of suboptimality for systems without uncertainty and develops an extension of this algorithm to reduce the degree of suboptimality for a small increase in the computational burden.
Given the current focus on teaching computational concepts to all from an early age, combined with the growing trend to empower end users to become producers of technology rather than mere consumers, we consider the issue of "computational notation".
Two optimization methods are proposed to tackle the issue of computational complexity.
We have introduced the issue of computational (or algorithmic) irreducibility when we explained the philosophical consequence of a universality proof for an automaton, namely that, although a system follows definite underlying laws, "its overall behavior can still have aspects that fundamentally cannot be described by reasonable laws" (Wolfram 2002, p. 750).
While it is recognized that issues of computational resources are overcome with time as computers and software become more efficient, limitations are likely to remain as the size of databases and complexity of time-dependent analyses will also increase.
We describe typical examples of our retrieval sequencing, notably the basic retrieval scheme, sources of error propagation, cases where a joint retrieval is advantageous — in particular, a combination of temperature retrieval with trace gas determination, issues of computational efficiency and memory requirements during joint retrievals, as well as the impact of microwindows.
Specifically, our work employs an Approximate Dynamic Programming approach that is well suited to address issues of computational tractability of the resulting dynamic planning optimization problem.
