We study the problems of scheduling jobs, with different release dates and
equal processing times, on two types of batching machines. All jobs of the
same batch start and are completed simultaneously. On a serial batching mac
hine, the length of a batch equals the sum of the processing times of its j
obs and, when a new batch starts, a constant setup time s occurs. On a para
llel batching machine, there are at most b jobs per batch and the length of
a batch is the largest processing time of its jobs. We show that in both e
nvironments, for a large class of so called "ordered" objective functions,
the problems are polynomially solvable by dynamic programming. This allows
us to derive that the problems where the objective is to minimize the weigh
ted number of late jobs, or the weighted flow time, or the total tardiness,
or the maximal tardiness are polynomial. In other words, we show that 1 \p
-batch,b < n, r(i), p(i) = p \F and 1 \s-batch, ri, p(i) = p \F, an polynom
ial for F is an element of {Sigma w(i)U(i), Sigmaw(i)C(i), SigmaT(i), T-max
}. The complexity status of these problems was unknown before.