  We introduce a natural but seemingly yet unstudied generalization of the
problem of scheduling jobs on a single machine so as to minimize the number of
tardy jobs. Our generalization lies in simultaneously considering several
instances of the problem at once. In particular, we have $n$ clients over a
period of $m$ days, where each client has a single job with its own processing
time and deadline per day. Our goal is to provide a schedule for each of the
$m$ days, so that each client is guaranteed to have their job meet its deadline
in at least $k \le m$ days. This corresponds to an equitable schedule where
each client is guaranteed a minimal level of service throughout the period of
$m$ days. We provide a thorough analysis of the computational complexity of
three main variants of this problem, identifying both efficient algorithms and
worst-case intractability results.
