We give a polynomial time algorithm for solving such problems, and prove that the class of problems generated by any larger set of constraints is NP-complete.
Our algorithms can construct n DNA words of shorter length (e.g., 2.1logn+6.28k) and can satisfy the same sets of constraints as the words constructed by the algorithms of Kao et al.. Furthermore, we extend these new algorithms to construct words that satisfy a larger set of constraints for which the algorithms of Kao et al.
The main reactor operation process control objective is the maximization of the molecular weight distribution (MWD) under a desired batch time, subject to a large set of operational constraints, while simultaneously avoiding the formation of polymer network (gel molecule).
Information from a sufficiently large set of noncavity constraints and parameters is integrated to update the cavity parameters.
Complex microprocessor systems consist of a large number of components and a large set of functional specification constraints, the diagnosis of which becomes a burden.
The economic dispatch often solves a short-term unit commitment problem together with the optimal scheduling with a fixed time resolution, i.e. usually on an hourly time resolution, under a large set of unit and system constraints.
There is a large set of analytical methods available for constraint-based modeling including metabolic flux analysis (MFA) [ 20, 21], flux balance analysis (FBA) [ 22- 24] and metabolic pathway analysis (e.g. based on elementary modes [ 25]).
In this paper we consider a problem motivated by a real-world environment: scheduling the charging periods for a large set of electric vehicles, subject to a set of hard constraints, with the objective of minimizing the total tardiness.
Thus, NAPSS often identifies a large set of possible structures that satisfy all of the stacking constraints.
The same is true for dynamic content layout: We achieve far better results by fitting content to a large set of designer-created layouts rather than approximating layouts with a more pure algorithmic approach such as linear constraints.
