English

Climbing depth-bounded adjacent discrepancy search for solving hybrid flow shop scheduling problems with multiprocessor tasks

Robotics 2011-03-09 v1 Artificial Intelligence

Abstract

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The problem even in its simplest form is NP-hard in the strong sense. The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems. We propose a new approach based on limited discrepancy search to solve the problem. Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature. Computational results show that the developed approach is efficient in particular for large-size problems.

Keywords

Cite

@article{arxiv.1103.1516,
  title  = {Climbing depth-bounded adjacent discrepancy search for solving hybrid flow shop scheduling problems with multiprocessor tasks},
  author = {Asma Lahimer and Pierre Lopez and Mohamed Haouari},
  journal= {arXiv preprint arXiv:1103.1516},
  year   = {2011}
}
R2 v1 2026-06-21T17:36:35.736Z