NP-complete

Computing the crossing number of a given graph is NP-complete the crossing number of only a few families of graphs are known.

As an NP complete problem, grid workflow scheduling is usually solved by means of heuristics.

Some bin packing problems are NP-complete but are amenable to dynamic programming solutions or to approximately optimal heuristic solutions.

In the half a century since the problem was recognized, no one has found an efficient algorithm for an NP-complete problem.

It is proved that this problem belongs to NP complete problem, and it needs to be solved by random method.

They have discovered that the task falls into a notorious category of problems called NP-complete.

The results indicate that the proposed algorithm can quickly obtain the satisfactory solutions of this type of NP-complete problems.

But despite a widespread misconception to the contrary, the factoring problem is neither known nor believed to be NP-complete.

To the best of our current knowledge, there are no exact solutions to problems that are NP Complete.

It have been proved that RWA (routing and wavelength assignment) algorithm in arbitrary mesh optical networks is a NP-complete problem.

In this paper, we prove this problem to be a difficult problem that is NP complete through a polynomial reduction.

In this paper, hairpin structure and molecular beacons are applied in solving a few NP complete problems.

Production scheduling problem has been shown to be a NP complete problem.

Subgraph isomorphism is NP-Complete problem. So must avoiding subgraph isomorphism by canonical code and efficient algorithm.

The question thus remains unanswered: Is there an efficient quantum algorithm to solve NP-complete problems?

First the problem was modeled as an instance of vertex cover problem which was an NP -Complete problem.

The candidate key of minimum cardinality problem was pointed out to be NP-complete in literature [1], [2], and [3].

Aiming at the critical areas coverage NP-complete problem, a heuristic critical areas coverage optimization algorithm(CACOA) is proposed.

Weapon-target assignment(WTA) problems are NP-complete, classical methods for them result in exponential computational complexities.

There exists a huge number of graph problem which is NP-complete, many seemed simple question is intact NP- complete.

Packing problem is NP complete, this paper uses an immune genetic algorithm to solve it.

Because the Time-Constrained Execution Path Selecting Problem is NP-complete, a heuristic algorithm is presented in this thesis.

Maximal profit item selection problem is a NP hard problem, it can be solved by a known quadratic programming which is NP complete.

We present the Maximum Disjoint Sets for Maintaining Coverage and Connectivity (MDS-MCC) problem, and we prove it is NP-complete.

Minimum path set and flow allocation problem(MPSFAP) were NP complete problems.

This paper formulates the satellite imaging scheduling problem as a 0-1 integer programming model, which is NP complete.

Graph vertex coloring problem (GVCP) is a NP-complete problem having good application such as scheduling and timetabling.

and they are known to be NP-complete for general graphs.

Facility layout of job shop problem is non-linear and NP-complete characteristic, and can not he solved well by conventional methods.

This is analogous to the NP Complete problem.

Because graph coloring problem belongs to NP complete problems, it can not get the optimal solution in polynomial time.

Classes of Simplified NP-complete Instances

approximate method for NP complete problem