LP-based working subsets for personnel scheduling: evaluation and augmentation

Michael J. Brusco, Tony R. Johns and Ray R. Venkataraman

European Journal of Industrial Engineering, 2018, vol. 12, issue 2, 175-198

Abstract: This paper evaluates the efficacy of LP-based working subsets for generalised set-covering formulations of personnel scheduling problems and presents a nearest-neighbour augmentation procedure for improving performance. Three experimental studies were completed in the evaluation process. In the first study, the LP-based working subset was sufficient to yield an optimal shift scheduling solution for 85% of the 24,300 test problems and the nearest-neighbour augmentation improved the percentage of optimal solutions to over 98%. The second study focused on more complex cyclic shift scheduling environments that permitted shift length, meal break and relief break flexibility. The adequacy of LP-based working subsets was supported by the provision of optimal shift scheduling solutions for 185 of 189 (98%) of the test problems. The third study examined a challenging tour scheduling environment for which globally-optimal benchmarks are not available. The superiority of the augmented LP-based working subset procedure was nevertheless evident, as it yielded better results than the (non-augmented) LP-based working subset for 92% of the test problems despite being constrained to only 40% of the allowed computation time for the non-augmented subsets. [Received 24 April 2017; Revised 25 August 2017; Revised 17 September 2017; Accepted 6 December 2017]

Keywords: personnel scheduling; integer programming; linear programming. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=90614 (text/html)
Access to full text is restricted to subscribers.

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:ids:eujine:v:12:y:2018:i:2:p:175-198

Access Statistics for this article

More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().