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This list may not reflect recent changes. NP-completeness * Karp's 21 NP-complete problems; List of NP-complete problems; 0–9. 1-planar graph; 3-dimensional matching;
Each cash inflow/outflow is discounted back to its present value (PV). Then all are summed such that NPV is the sum of all terms: = (+) where: t is the time of the cash flow; i is the discount rate, i.e. the return that could be earned per unit of time on an investment with similar risk
This is a list of some of the more commonly known problems that are NP-complete when expressed as decision problems. As there are thousands of such problems known, this list is in no way comprehensive. Many problems of this type can be found in Garey & Johnson (1979).
The present value formula is the core formula for the time value of money; each of the other formulas is derived from this formula. For example, the annuity formula is the sum of a series of present value calculations. The present value (PV) formula has four variables, each of which can be solved for by numerical methods:
"NP-complete problems are the most difficult known problems." Since NP-complete problems are in NP, their running time is at most exponential. However, some problems have been proven to require more time, for example Presburger arithmetic. Of some problems, it has even been proven that they can never be solved at all, for example the halting ...
Hilbert matrix — example of a matrix which is extremely ill-conditioned (and thus difficult to handle) Wilkinson matrix — example of a symmetric tridiagonal matrix with pairs of nearly, but not exactly, equal eigenvalues; Convergent matrix — square matrix whose successive powers approach the zero matrix; Algorithms for matrix multiplication:
The first Project Euler problem is Multiples of 3 and 5. If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23. Find the sum of all the multiples of 3 or 5 below 1000. It is a 5% rated problem, indicating it is one of the easiest on the site.
In computational complexity, problems that are in the complexity class NP but are neither in the class P nor NP-complete are called NP-intermediate, and the class of such problems is called NPI. Ladner's theorem , shown in 1975 by Richard E. Ladner , [ 1 ] is a result asserting that, if P ≠ NP , then NPI is not empty; that is, NP contains ...