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The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric. [3]: ND22, ND23
Many students work in groups to solve them and help get a better understanding of the material, [6] [7] but most professors require each student to hand in their own individual problem set. Some professors explicitly encourage collaboration, [ 5 ] [ 6 ] some allow it, and some explicitly disallow it [ 3 ] or consider it cheating.
Problem solving in psychology refers to the process of finding solutions to problems encountered in life. [5] Solutions to these problems are usually situation- or context-specific. The process starts with problem finding and problem shaping, in which the problem is discovered and simplified. The next step is to generate possible solutions and ...
(The latter case can be alternatively considered as a changing of the problem rather than of the solution strategy: instead of "What chemical will work well as an antibiotic?" the problem in the sophisticated approach is "Which, if any, of the chemicals in this narrow range will work well as an antibiotic?")
One important drawback for applications of the solution of the classical secretary problem is that the number of applicants must be known in advance, which is rarely the case. One way to overcome this problem is to suppose that the number of applicants is a random variable N {\displaystyle N} with a known distribution of P ( N = k ) k = 1 , 2 ...
The question is whether or not, for all problems for which an algorithm can verify a given solution quickly (that is, in polynomial time), an algorithm can also find that solution quickly. Since the former describes the class of problems termed NP, while the latter describes P, the question is equivalent to asking whether all problems in NP are ...
A workaround is a bypass [1] of a recognized problem or limitation in a system or policy. [2] A workaround is typically a temporary fix [3] [4] that implies that a genuine solution to the problem is needed. But workarounds are frequently as creative as true solutions, involving outside the box thinking [5] [6] in their creation.
Clearly, a #P problem must be at least as hard as the corresponding NP problem, since a count of solutions immediately tells if at least one solution exists, if the count is greater than zero. Surprisingly, some #P problems that are believed to be difficult correspond to easy (for example linear-time) P problems. [ 18 ]