Abstract
We study a natural variant of scheduling that we call partial scheduling: in this variant an instance of a scheduling problem along with an integer k is given and one seeks an optimal schedule where not all, but only k jobs, have to be processed. Specifically, we aim to determine the fine-grained parameterized complexity of partial scheduling problems parameterized by k for all variants of scheduling problems that minimize the makespan and involve unit/arbitrary processing times, identical/unrelated parallel machines, release/due dates, and precedence constraints. That is, we investigate whether algorithms with runtimes of the type f(k)nO(1)
or nO(f(k))
exist for a function f that is as small as possible. Our contribution is two-fold: First, we categorize each variant to be either in P
, NP
-complete and fixed-parameter tractable by k, or W[1]
-hard parameterized by k. Second, for many interesting cases we further investigate the runtime on a finer scale and obtain run times that are (almost) optimal assuming the Exponential Time Hypothesis. As one of our main technical contributions, we give an O(8kk(|V|+|E|))
time algorithm to solve instances of partial scheduling problems minimizing the makespan with unit length jobs, precedence constraints and release dates, where G=(V,E)
is the graph with precedence constraints.
or nO(f(k))
exist for a function f that is as small as possible. Our contribution is two-fold: First, we categorize each variant to be either in P
, NP
-complete and fixed-parameter tractable by k, or W[1]
-hard parameterized by k. Second, for many interesting cases we further investigate the runtime on a finer scale and obtain run times that are (almost) optimal assuming the Exponential Time Hypothesis. As one of our main technical contributions, we give an O(8kk(|V|+|E|))
time algorithm to solve instances of partial scheduling problems minimizing the makespan with unit length jobs, precedence constraints and release dates, where G=(V,E)
is the graph with precedence constraints.
Original language | English |
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Pages (from-to) | 2309-2334 |
Number of pages | 26 |
Journal | Algorithmica |
Volume | 84 |
Issue number | 8 |
DOIs | |
Publication status | Published - May 2022 |