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Dynamic scheduling for complex engineer-to-order products

Hicks, C.; Song, D. P. and Earl, C. F. (2007). Dynamic scheduling for complex engineer-to-order products. International Journal of Production Research, 45(15) pp. 3477–3503.

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The current paper considers dynamic production scheduling for manufacturing systems producing products with deep and complex product structures and complicated process routings. It is assumed that manufacturing and assembly processing times are deterministic. Dynamic scheduling problems may be either incremental (where the schedule for incoming orders does not affect the schedule for existing orders) or regenerative (where a new schedule is produced for both new and existing orders). In both situations, a common objective is to minimize total costs (the sum of work-in-progress holding costs, product earliness and tardiness costs). In this research, heuristic and evolutionary-strategy-based methods have been developed to solve incremental and regenerative scheduling problems. Case studies using industrial data from a company that produces complex products in low volume demonstrate the effectiveness of the methods. Evolution strategy (ES) provides better results than the heuristic method, but this is at the expense of significantly longer computation times. It was found that performing regenerative planning is better than incremental planning when there is high interaction between the new orders and the existing orders.

Item Type: Journal Item
ISSN: 0020-7543
Keywords: Manufacturers; Manufacturing processes; Heuristic; Case studies; Holding cost; Dynamic scheduling; Engineer to order; Evolution strategy; Optimization; Rescheduling;
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Innovation, Knowledge & Development research centre (IKD)
Item ID: 15611
Depositing User: Colin Smith
Date Deposited: 24 Apr 2009 09:06
Last Modified: 08 May 2019 13:30
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