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Self-adaptive systems typically operate in heterogeneous environments and need to optimize their behavior based on a variety of quality attributes to meet stakeholders’ needs. During adaptation planning, these quality attributes are considered in the form of constraints, describing hard requirements that have to be fulfilled, and utility functions, which are used to select an optimal plan among several alternatives. Up until now, most automated planning approaches are not designed to adapt quality attributes, their priorities, and their trade-offs at run time. Instead, both utility functions and constraints are defined a priori, and cannot be easily adapted in response to changes in the environment or in stakeholders’ preferences. In this paper, we present initial work that combines automated planning and adaptation of quality attributes to address this gap. The approach helps to semi-automatically adjust utility functions and constraints based on changes at run time. We present a preliminary experimental evaluation which indicates that our approach can provide plans with higher utility values while fulfilling changed or added constraints. We conclude this short paper with our envisioned research outlook and plans for future empirical studies.