Dynamic Group Scheduling Heuristics in a Flow‐through Cell Environment*
作者:
Farzad Mahmoodi,
Edward J. Tierney,
Charles T. Mosier,
期刊:
Decision Sciences
(WILEY Available online 1992)
卷期:
Volume 23,
issue 1
页码: 61-85
ISSN:0011-7315
年代: 1992
DOI:10.1111/j.1540-5915.1992.tb00377.x
出版商: Blackwell Publishing Ltd
关键词: Cellular Manufacturing;Group Scheduling;Production/Operations Management;Simulation
数据来源: WILEY
摘要:
ABSTRACTThe increased use of cellular manufacturing configurations designed to grapple with increasing competitive pressures is providing manufacturing managers and engineers with a broad variety of operational challenges. Many questions concerning the best procedures and policies for the day‐to‐day operation of manufacturing cells are still unanswered. The primary objective of this study is to compare the performance of traditional single‐stage heuristics and the two‐stage group scheduling heuristics that have exhibited superior performance in previous studies in a flow‐through cell environment under a rigorous set of experimental conditions. Such a comparison is of great interest since each previous study has focused on proposing new heuristics and testing them against some particular baseline heuristic, often without comprehensive comparisons to the broad variety of previously proposed heuristics.Two single‐stage heuristics and four two‐stage heuristics are examined under sixteen experimental conditions (four experimental factors at two levels each). The experimental factors examined are shop load, due date tightness, setup to run‐time ratio, and interarrival time distribution. Results vary by experimental condition and performance criteria, but in general, two‐stage heuristics outperformed single‐stage heuristics under all experimental conditions, as well as being relatively insensitive to changing experimental conditions. In addition, two of the two‐stage heuristics displayed superior performance on all performance measures under most experimental conditions. Finally, the results indicated that interarrival time distribution does have a major impact on the performance of
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