Plan Reordering and Parallel Execution - A Parameterized Complexity View

Abstract

Bäckström has previously studied a number of optimization problems for partial-order plans, like finding a minimum deordering (MCD) or reordering (MCR), and finding the minimum parallel execution length (PPL), which are all NP-complete. We revisit these problems, but applying parameterized complexity analysis rather than standard complexity analysis. We consider various parameters, including both the original and desired size of the plan order, as well as its width and height. Our findings include that MCD and MCR are W[2]-hard and in W[P] when parameterized with the desired order size, and MCD is fixed-parameter tractable (fpt) when parameterized with the original order size. Problem PPL is fpt if parameterized with the size of the non-concurrency relation, but para-NP-hard in most other cases. We also consider this problem when the number (k) of agents, or processors, is restricted, finding that this number is a crucial parameter; this problem is fixed-parameter tractable with the order size, the parallel execution length and k as parameter, but para-NP-hard without k as parameter.

Cite

Text

Aghighi and Bäckström. "Plan Reordering and Parallel Execution - A Parameterized Complexity View." AAAI Conference on Artificial Intelligence, 2017. doi:10.1609/AAAI.V31I1.11025

Markdown

[Aghighi and Bäckström. "Plan Reordering and Parallel Execution - A Parameterized Complexity View." AAAI Conference on Artificial Intelligence, 2017.](https://mlanthology.org/aaai/2017/aghighi2017aaai-plan/) doi:10.1609/AAAI.V31I1.11025

BibTeX

@inproceedings{aghighi2017aaai-plan,
  title     = {{Plan Reordering and Parallel Execution - A Parameterized Complexity View}},
  author    = {Aghighi, Meysam and Bäckström, Christer},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {3540-3546},
  doi       = {10.1609/AAAI.V31I1.11025},
  url       = {https://mlanthology.org/aaai/2017/aghighi2017aaai-plan/}
}