The phrase "a known solution" is correct and usable in written English.
It can be used when referring to a solution that is recognized or established within a particular context or field.
Example: "In mathematics, we often rely on a known solution to simplify complex problems."
Alternatives: "an established solution" or "a recognized solution".
First, for a known problem with a known solution — such as customer segmentation and propensity modeling for targeted marketing campaigns — the company could take a hypothesis-based approach by starting with the outcome (e.g. cross-sell/up-sell to existing customers), pilot and test the solution with a control group and then scale broadly across the customer base.
A known solution consists in exciting specifically the microarray surface with evanescent fields.
We should be doing it the other way round: finding the problem to which a known solution is an ideal answer.
This approach reveals the behavior of each criterion as it would be in a design situation and avoids the possibility of calibration toward a known solution.
At that abstract level, either the solution is found through the tools of graph theory, such as the graph duality principle, or the problem is transformed further to another engineering domain, where the problem is associated with a known solution.
We extend a known solution of ordering the signals in a bus bundle to minimize the impact of the first order wire-to-wire parasitic capacitance occurring between adjacent wires into a model accounting for also secondary components of wire-to-wire parasitic capacitances.
So a known problem, known solution, but one still has to solve it by working together.
Some articles merely state that a problem has no known solution -- but that information alone can save you from wild goose chases.
We can conclude that the analysis method fails the 'positive control test', namely the application to a related problem with known solution.
However, when our implementation of GD is started from a point near the known solution and allowed to change the parameters in all, rather than only in the perturbed dimension, it rapidly finds a nearby region of very low gradient, but not the known solution.
Most instances are found difficult to solve optimally while our metaheuristic can find the best known or close to the best known solution in a short time.
