Polynomial transfer lot sizing techniques for batch processing on consecutive machines - Info and Reading Options
By Dan Trietsch
"Polynomial transfer lot sizing techniques for batch processing on consecutive machines" was published by Naval Postgraduate School in 1989 - Monterey, Calif and the language of the book is English.
“Polynomial transfer lot sizing techniques for batch processing on consecutive machines” Metadata:
- Title: ➤ Polynomial transfer lot sizing techniques for batch processing on consecutive machines
- Author: Dan Trietsch
- Language: English
- Publisher: Naval Postgraduate School
- Publish Date: 1989
- Publish Location: Monterey, Calif
“Polynomial transfer lot sizing techniques for batch processing on consecutive machines” Subjects and Themes:
- Subjects: BATCH PROCESSING
Edition Specifications:
- Pagination: 1 v. (various pagings) :
Edition Identifiers:
- The Open Library ID: OL25463939M - OL16838240W
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"Polynomial transfer lot sizing techniques for batch processing on consecutive machines" Description:
The Open Library:
Using transfer lots, we can overlap the processing of a batch on several consecutive machines, and thus reduce the makespan considerably. This in turn promotes work-in-process reduction. In this paper we investigate the transfer lots sizing problem for a given batch size under two operating procedures. Our objective is to minimize the makespan subject to a transferring budget. An important part of the solution involves partitioning the problem to subsets of machines without losing optimality. For each part (subset), the first and the last machines operate continuously while intermediate machines may idle intermittently. The first operating procedure we consider calls for the lots to be identical across all machines in each subset. The second operating procedure allows sub-lots for some of the machines or for some of the lots. Through more elaborate, the second operating procedure yields demonstrably superior results. The techniques provide satisfying feasible solutions, which can also serve as efficient bounds for an exact branch and bound inter linear programming model. (KR)
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