Sentence examples for minimal constrained from inspiring English sources

In general, hard instances H of the enumeration problem have to violate the condition of well-separation for same choice of R f ⊂ H, in order that the corresponding minimal constrained hyperpath problem becomes hard.

Given the hypergraph described above (whose size is linear in the size of the underlying 3-SAT problem) consider the minimal constrained hyperpath problem where all the hyperarcs ε i are mandatory, and the target is T. A solution of this problem gives in linear time a solution for the underlying SAT problem, which makes the problem of minimal constrained hyperpath an NP-complete problem.

However, in many practical instances (for instance when hyperarcs only have one head node), the algorithm Minimize returns a minimal constrained hyperpath.

A related problem to Minimize is the minimal constrained hyperpath problem: the problem of finding if a minimal hyperpath from a given source to a given target, containing the hyperarcs in R f exists.

In this section we give a characterization of the hypergraphs where the algorithm Minimize solves the minimal constrained hyperpath problem, characterizing these instances helps to individuate which hypergraphs are expected to give an output only containing minimal hyperpaths.

If the well-separation condition holds for a hypergraph H with constrained reactions R f, the algorithm Minimize returns a minimal hyperpath solving the minimal constrained hyperpath problem if a solution exists.

If π k j is the probability of the region of the support in which the kth factor is the constraining factor on utility, we can write Σ x π x j min ( f 1 x j, f 2 x j,.. f Kx j ) = Σ κ π κ j Σ k ε κ π k | κ f k j where π k|κ is the probability of particular values of the kth factor given that this factor is the minimal constraining one.

We develop a new class of gain-constrained and power-constrained algorithms termed constrained minimal disturbance (CMD).

The multiperiod degree constrained minimal spanning tree (MDCMST) problem consists of scheduling the installation of links in a network so as to connect a set of terminal nodes to a central node with minimal present value of expenditures.

A rigorous formulation – constrained minimal cut sets (cMCS) – for generating NMF has recently been put forward [ 16].

Recently, constrained minimal cut sets (cMCS) have been introduced to derive optimal design strategies for strain improvement by using the full potential of EM analysis.