A Dynamic Model for the Optimal Loading of Linear Multi-Operation Shops

Salah E. Elmaghraby and Allen S. Ginsberg
Additional contact information
Salah E. Elmaghraby: Department of Industrial Administration, Yale University and The RAND Corporation
Allen S. Ginsberg: Department of Industrial Administration, Yale University and The RAND Corporation

Management Science, 1964, vol. MT-4, issue 1, 47-58

Abstract: Because of the stochastic nature of the parameters in the general job shop problem (e.g., estimates of processing times; estimates of delay times; the sequence of operations; the availability of processing units; etc.), Monte Carlo simulation has been the principal tool of analysis. In particular, a large proportion of studies was focused on the indirect control of the functions of scheduling and loading by the device of assigning priorities to the various jobs in the shop. In this paper, we depart from this tradition for two good reasons. First, the linear characteristic of flow eliminates an important disrupting factor present in the general problem treated by the other authors. Second, priority decision rules are perhaps the last sphere of decision open to managers and may have a very limited effect since they are seriously constrained by previously-made decisions. In fact, priority decisions, coming as they do at the "tail" of the decision process, may prove ineffectual in the face of previously-established sales quantities, promised due dates, capacity limitations, etc. Consequently, a study of the "higher echelon" decisions of scheduling and loading is necessitated. "Management Technology", ISSN 0542-4917, was published as a separate journal from 1960 to 1964. In 1965 it was merged into Management Science.

Date: 1964
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mantech.4.1.47 (application/pdf)

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:inm:ormnsc:v:mt-4:y:1964:i:1:p:47-58

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().