Production setup-sequencing and lot-sizing at an animal nutrition plant through ATSP subtour elimination and patching

Toso, Eli A.V.; Clark, Alistair; Morabito, Reinaldo

Abstract

This paper considers the usefulness of a production lot sizing and scheduling model at an animal nutrition plant with sequence-dependent setup times. The model covers multiple periods and is based on the asymmetric travelling salesman problem (ATSP). It is applied initially to the case where the setup state is zeroed between periods, and then revised to model the carryover of the setup state from one period to the next. An iterative solution procedure based on subtour elimination is applied, and then enhanced by the inclusion of a subtour patching procedure. Case-based tests with actual plant data show that the subtour elimination is practicably fast where the setup state is zeroed between periods, but needs the patching procedure when the setup state is preserved, as is the situation at the plant. In this latter case, the subtour elimination and patching can be very fast, showing the method's viability for operational lot sizing and sequencing in animal nutrition plants of the kind studied. Tests on perturbed plant data show that further algorithmic development is needed to tackle certain challenging variants found in other plants. © Springer Science+Business Media, LLC 2009.

• Journal Article Type: Article
• Publication Date: Jan 1, 2010
• Deposit Date: Nov 2, 2010
• Journal: Journal of Scheduling
• Print ISSN: 1094-6136
• Electronic ISSN: 1099-1425
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 2
• Pages: 111-121
• DOI: https://doi.org/10.1007/s10951-009-0135-7
• Keywords: ot sizing, production scheduling, sequence-dependent setup times, asymmetric travelling salesman problem, animal nutrition industry, case-study
• Public URL: https://uwe-repository.worktribe.com/output/984001
• Publisher URL: http://dx.doi.org/10.1007/s10951-009-0135-7
• Related Public URLs: http://www.springerlink.com/content/g0v867g110026642/
• Contract Date: Nov 15, 2016