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Dynamic Group Scheduling Heuristics in a Flow‐through Cell Environment *
Author(s) -
Mahmoodi Farzad,
Tierney Edward J.,
Mosier Charles T.
Publication year - 1992
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1992.tb00377.x
Subject(s) - heuristics , computer science , scheduling (production processes) , mathematical optimization , baseline (sea) , heuristic , operations research , reliability engineering , mathematics , engineering , artificial intelligence , oceanography , geology
The 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 scheduling heuristics.