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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
The problem to determine all positive integers such that the concatenation of and in base uses at most distinct characters for and fixed [citation needed] and many other problems in the coding theory are also the unsolved problems in mathematics.
The main purpose of a problem statement is to identify and explain the problem. [3] [4] Another function of the problem statement is as a communication device. [3] Before the project begins, stakeholders verify the problem and goals are accurately described in the problem statement. Once approved, the project reviews it.
A 2013 study has found that 75% of users only ask one question, 65% only answer one question, and only 8% of users answer more than 5 questions. [34] To empower a wider group of users to ask questions and then answer, Stack Overflow created a mentorship program resulting in users having a 50% increase in score on average. [ 35 ]
For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v , an optimization problem might be "find a path from u to v that uses the fewest edges".
Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.
Solution of a travelling salesman problem: the black line shows the shortest possible loop that connects every red dot. In the theory of computational complexity, the travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the ...
Determining the optimal solution to VRP is NP-hard, [2] so the size of problems that can be optimally solved using mathematical programming or combinatorial optimization can be limited. Therefore, commercial solvers tend to use heuristics due to the size and frequency of real world VRPs they need to solve.