The phrase "a stopping problem" is correct and usable in written English.
It can be used in contexts related to decision-making, algorithms, or computational theory, often referring to a situation where one must determine when to stop a process or action.
Example: "In computer science, a stopping problem can arise when designing algorithms that need to decide when to halt execution."
Alternatives: "termination issue" or "halting problem".
We illustrate the proposed approach with an application to an optimal stopping problem in a clinical trial.
Choi et al. (2004) study an investor's decision to switch from active portfolio management to passive management and modelled it to a mixture of a consumption-portfolio selection problem and an optimal stopping problem.
We formulate the online relay selection problem as an optimal stopping problem and design an optimal stopping policy, which can guarantee the success of relay selection in a given time while control the cost of PU for utilizing cooperative communication.
We present an explicit solution to an optimal stopping problem of the stochastic Gilpin-Ayala population model by applying the smooth pasting technique (Dixit in The Art of Smooth Pasting, 1993 and Dixit and Pindyck in Investment under Uncertainty, 1994).
At the other extreme of consumer behavior, the dynamic approach leads to an optimal stopping problem akin to pricing an American put option, albeit complicated by the non-traditional payment structure.
Given an expiration time T and a project value based on one or more nonstationary stochastic processes, the problem of deciding the optimal time to exercise an option can be interpreted as an optimal stopping problem, according to Dixit and Pindyck (1994).
To overcome the limitations of sensing and transmission constraints, an optimal stopping problem was formulated in Su and Zhang (2008a), where a potential CR sender can achieve its optimal expected throughput with the help of derived sensing time.
The other is to apply the method to an American put option with uncertainty formulated as an optimal stopping problem for fuzzy random variables, and the randomness and fuzziness are estimated by the probabilistic expectation and the mean values.
Equation (15) implies that Eq. (9) is equivalent to a standard optimal stopping problem with a terminal payoff G and an underlying (adapted) state process begin{array}{l} Y t)=ln left(frac{M t)}{x t)}right), quad Y 0)=0.
The model of pricing the bond without call is an optimal stopping problem (2.14).
