The paper delves into the analysis of optimization problems that involve changing problem constraints over time and proposes a method to adapt metaheuristic algorithms for real-time applications. The dynamic map labeling problem serves as a case study. In the static version of the problem, the goal is to position labels without overlap for maximum readability. However, in dynamic scenarios where the map view changes, the task becomes more challenging, requiring labels to be adjusted in real-time. To address this challenge, a Tabu Search algorithm is adapted to function in a dynamic environment where user interactions can alter the map view, changing the solution space of possible label placements on the current map view.