Integrated scheduling on a batch machine to minimize production, inventory and distribution costs
Document Type
Article
Publication Date
4-1-2017
Abstract
We consider the problem of scheduling a set of jobs on a single batch-processing machine. Each job has a size and a processing time. The jobs are batched together and scheduled on the batch-processing machine, provided that the total size does not exceed the machine capacity. The processing time of the batch is the longest processing time among all the jobs in the batch. There is a single vehicle to deliver the final products to the customer. If the vehicle has not returned, completed batches will be put into the inventory. In this paper, we consider the problem of minimizing the production, delivery and inventory costs. We show that if the jobs have the same size, there is an O(nlog n)-time algorithm to find an optimal solution. If the jobs have the same processing time, there is a fast approximation algorithm with an absolute worst-case ratio less than 1.783 and an asymptotic worst-case ratio equal to 11/9. When the jobs have arbitrary sizes and arbitrary processing times, there is a fast approximation algorithm with absolute and asymptotic worst-case ratios less than or equal to 2, respectively.
Identifier
84994514681 (Scopus)
Publication Title
European Journal of Operational Research
External Full Text Location
https://doi.org/10.1016/j.ejor.2016.09.009
ISSN
03772217
First Page
104
Last Page
112
Issue
1
Volume
258
Grant
71131002
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Cheng, Ba Yi; Leung, Joseph Y.T.; and Li, Kai, "Integrated scheduling on a batch machine to minimize production, inventory and distribution costs" (2017). Faculty Publications. 9662.
https://digitalcommons.njit.edu/fac_pubs/9662
