Satisfying due dates in large job shops

Article Abstract:

Large job shop networks are faced with the difficult task of sequencing jobs, which is considered an NP-hard problem. A simulation-based approach to scheduling, which was based on the procedure discussed by Lawrence and Morton (1986), was developed to solve this problem. This analysis showed that this procedure offers optimal or near optimal schedules for the N-job, M-machine, maximum lateness problem, under certain conditions. The case that compelled this study involved a final assembly operation in a separate area of the company. There would be delays in the production schedules in this operation if maximum lateness is greater than zero. This investigation aimed to help the final assembly operation meet every due date, which was solved by reducing the maximum lateness. An effective lower bound computation for maximum lateness was formulated and an iterative scheduling procedure was developed.

Analysis, Machinery, Calendar, Machine shops

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Economic lot scheduling for multiple products on parallel identical processors

Article Abstract:

A heuristic process is suggested to address an identical, multiproduct, multiprocessor, lot-scheduling problem. The focus of the analysis is to reduce the average inventory and production costs per unit time subject to limits of no inference and no shortages among products. A mathematical formulation for the problem is developed, and computational results are reported after applying the heuristic process. Research results indicate that the heuristic process decomposes the entire problem into lot-size scheduling and allocation parts and improves one while holding the other part constant. Results also suggest that the process gave solutions with deviations of less than five percent of the lower bound for up to 10 processors and 100 products.

Research, Inventory control, Production control

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