en.wikipedia.org/wiki/Algorithm

The statement is chronologically impossible as written.

• The telephone itself was patented in 1876, so telephone-switching networks could not have been invented in 1835. Britannica dates Alexander Graham Bell’s telephone patent to March 7, 1876.
• Britannica’s history of telephone switching says “the idea of automatic switching appeared as early as 1879” and that “the first fully automatic switch to achieve commercial success was invented in 1889 by Almon B. Strowger.”

So 1835 fits the era of early relay/electromagnet work, not the invention of telephone-switching networks of electromechanical relays. The article appears to have conflated the history of relays with the later history of telephone switching.

The phrase “graphs without negative cycles” is the wrong condition for minimum spanning trees.

A minimum spanning tree (MST) is defined for a connected, undirected weighted graph. Standard algorithm notes define the problem on graphs whose edge weights are any real numbers, and some explicitly note that edge weights may be zero or negative. Because a tree is acyclic by definition, the notion of a negative cycle is relevant to shortest-path problems, not to MSTs.

So the article is mixing up two different graph-algorithm topics:

• Shortest paths: negative cycles matter a lot.
• Minimum spanning trees: negative cycles are not the defining restriction; MST algorithms work on connected undirected weighted graphs, including graphs with negative-weight edges.

That makes the statement inaccurate as written.

This sentence misdefines heuristics.

A heuristic is not limited to problems that lack well-defined correct or optimal results. In computer science and optimization, heuristics are often used precisely for problems that do have a clearly defined optimal solution, but where finding that optimum exactly is too expensive in practice.

For example:

• NIST’s Dictionary of Algorithms and Data Structures defines a heuristic as “an algorithm that usually, but not always, works or that gives nearly the right answer.” That definition does not depend on the problem lacking a correct or optimal answer.
• MIT’s Optimization Methods lecture on heuristic methods discusses heuristics for problems such as the Traveling Salesman Problem and the Knapsack Problem, both of which have well-defined optimal solutions.

So the article’s sentence is misleading because it frames heuristics as applying only when there is no well-defined correct or optimal result, which is false in standard computer-science usage.