Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources

Jun-Ho Lee and Hoon Jang
Additional contact information
Jun-Ho Lee: School of Business, Konkuk University, Seoul 05029, Korea
Hoon Jang: College of Global Business, Korea University, Sejong 30019, Korea

Sustainability, 2019, vol. 11, issue 24, 1-23

Abstract: We examine a uniform parallel machine scheduling problem with dedicated machines, job splitting, and limited setup resources for makespan minimization. In this problem, machines have different processing speeds, and each job can only be processed at several designated machines. A job can be split into multiple sections and those sections can be processed on multiple machines simultaneously. Sequence-independent setup times are assumed, and setup operations between jobs require setup operators that are limited. For the problem, we first develop a mathematical optimization model and for large-sized problems a constructive heuristic algorithm is proposed. Finally, we show that the algorithm developed is efficient and provides good solutions by experiments with various scenarios.

Keywords: uniform parallel machine; scheduling; dedicated machines; job splitting; setup resource; heuristic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/24/7137/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/24/7137/ (text/html)

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:gam:jsusta:v:11:y:2019:i:24:p:7137-:d:297455

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().