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The frequent actuation of discrete control devices dcds, e.g., on-load tap changers, drastically reduces their lifetime. This, in turn, imposes a huge replacement cost. Simultaneous scheduling of these \textsc{dcd}s and continuous control devices, e.g., distributed energy resources, is imperative for reducing the operating cost. This also increases the lifetime of \textsc{dcd}s and helps to avoid the sub-optimal/infeasible solutions. Considering the high cost of discrete control actions (dcas), they may never be justified against the other options in a short scheduling horizon (sh). With a longer sh, their benefits over a long period justify dcas. However, a shorter \textsc{sh} helps to hedge against the risk impelled by uncertainties. Here, the system's future is modeled as a set of multi-period scenarios. The operator exploits a long sh, but solely applies the decisions made for the first period and waits for updated data to make the next decisions. This enables cost reduction by strategically applying dcas prior to the time that they are inevitable while avoiding them when unneeded. The proposed branch-and-cut-based solution methodology accurately deals with dcas while applying some expediting heuristics. During the branching process, a globally convergent trust-region algorithm solves the integer relaxed problems.