On the exact solution of a large class of parallel machine scheduling problems

Teobaldo Bulhões (), Ruslan Sadykov (), Anand Subramanian () and Eduardo Uchoa ()
Additional contact information
Teobaldo Bulhões: Universidade Federal da Paraíba
Ruslan Sadykov: Inria Bordeaux Sud-Ouest
Anand Subramanian: Universidade Federal da Paraíba
Eduardo Uchoa: Universidade Federal Fluminense

Journal of Scheduling, 2020, vol. 23, issue 4, No 1, 429 pages

Abstract: Abstract This work deals with a very generic class of scheduling problems with identical/uniform/unrelated parallel machine environment. It considers well-known attributes such as release dates, deadlines, or sequence-dependent setup times and accepts any objective function defined over job completion times. Non-regular objectives are also supported. We introduce a branch-cut-and-price algorithm for such problems that makes use of non-robust cuts, i.e., cuts which change the structure of the pricing problem. This is the first time that such cuts are employed for machine scheduling problems. The algorithm also embeds other important techniques such as strong branching, reduced cost fixing and dual stabilization. Computational experiments over literature benchmarks showed that the proposed algorithm is indeed effective and could solve many instances to optimality for the first time.

Keywords: Parallel machines; Unified algorithm; Branch-cut-and-price (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10951-020-00640-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jsched:v:23:y:2020:i:4:d:10.1007_s10951-020-00640-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10951

DOI: 10.1007/s10951-020-00640-z

Access Statistics for this article

Journal of Scheduling is currently edited by Edmund Burke and Michael Pinedo

More articles in Journal of Scheduling from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().