Optimization in real time

A search algorithm called real-time search (RTS) for solving combinatorial optimization problems under real-time constraints is presented. The algorithm aims at finding the best possible solution within a given deadline. Since this objective is generally not achievable without first solving the problem, the authors use an alternative heuristic objective that looks for the solution with the best ascertained approximation degree. The algorithm schedules a sequence of guided depth-first searches, each searching for a more accurate solution (based on the approximation degree set), or solutions deeper in the search tree (based on the threshold set), or a combination of both. Five versions of the RTS algorithm for setting approximation degrees and/or thresholds are formulated, evaluated, and analyzed. The authors describe the experimental results obtained for the five versions of RTS