Minimising total earliness and tardiness with periodically supplied non-renewable resource profiles

Mohammad Namakshenas, Aleida Braaksma and Mohammad Mahdavi Mazdeh

International Journal of Production Research, 2022, vol. 60, issue 10, 3170-3181

Abstract: We consider a special class of resource-constrained single machine scheduling problems. In the classical scheduling context, resource types are classified into renewable and non-renewable; however, a large variety of real-world problems may not fit into one of these classes, e.g. labour regulations in project scheduling, budget allocation to different phases of a construction project, and dose management in a medical imaging centre. In this study, we address a class of non-renewable resources supplied, not necessarily immediately, in different periods of the planning horizon. The objective is to assign the jobs to the supply periods and schedule them such that the sum of total tardiness and total earliness is minimised. Several properties and complexity results of the optimal schedules are discussed, then they are used to develop a tractable algorithm. First, we decompose the problem into several single supply problems and then decide the optimal schedule through a polynomial-time optimal algorithm for each single supply problem. The scalability tests indicate the promising performance guarantee of the algorithm compared to provably optimal schedules in the integrated framework.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2021.1912430 (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:taf:tprsxx:v:60:y:2022:i:10:p:3170-3181

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2021.1912430

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().