A novel solution approach is developed for the scheduling of chemotherapy sessions at cancer treatment centers. The problem is divided into two subproblems determining the day (interday scheduling) and the time slots (intraday scheduling), respectively. The interday subproblem is solved by a model that allows for effective treatment center capacity choices while the intraday subproblem is addressed using two optimization models. New patient arrivals and treatment protocols specifying the latest starting date and session spacing are sources of uncertainty. Unlike other existing approaches, the proposed method incorporates the concept of effective treatment capacity which facilitates the interaction between the interday and intraday subproblems allowing them to be solved sequentially and iteratively to thus achieve much more resource-efficient solutions. A case study using real data from a Chilean cancer center to conduct comparative simulations of its manual scheduling methods and the proposed methodology found that the latter almost always performed better, often significantly so, on makespan, resource utilization, overtime, and patient diversion metrics.