One of the reasons the logit model was formulated was that the probit model was computationally difficult due to the requirement of numerically calculating integrals.

Multiple sequence alignments are computationally difficult to produce and most formulations of the problem lead to NP-complete combinatorial optimization problems.

The detailed analysis of CMBR data to produce maps, an angular power spectrum, and ultimately cosmological parameters is a complicated, computationally difficult problem.

The problem of computing n-th residue classes is believed to be computationally difficult.

The number of nontrivial knots of a given crossing number increases rapidly, making tabulation computationally difficult .

The problem is computationally difficult and there are competing mathematical methods of solving the problem.

However, sampling-based methods can be very useful in addressing a variety of problems which are computationally difficult to solve analytically or even to rigorously bound.

Karp introduced the now standard methodology for proving problems to be NP-complete which has led to the identification of many theoretical and practical problems as being computationally difficult.

Factorization is thought to be a computationally difficult problem, whereas primality testing is comparatively easy (its running time is polynomial in the size of the input).

The problem is computationally difficult (NP-hard); however, there are efficient heuristic algorithms that are commonly employed and converge quickly to a local optimum.