Parallel machine scheduling with batch deliveries to minimize total flow time and delivery cost
Document Type
Article
Publication Date
9-1-2016
Abstract
Motivated by the flow of products in the iron and steel industry, we study an identical and parallel machine scheduling problem with batch deliveries, where jobs finished on the parallel machines are delivered to customers in batches. Each delivery batch has a capacity and incurs a cost. The objective is to find a coordinated production and delivery schedule that minimizes the total flow time of jobs plus the total delivery cost. This problem is an extension of the problem considered by Hall and Potts, Ann Oper Res 135 (2005) 41–64, who studied a two-machine problem with an unbounded number of transporters and unbounded delivery capacity. We first provide a dynamic programming algorithm to solve a special case with a given job assignment to the machines. A heuristic algorithm is then presented for the general problem, and its worst-case performance ratio is analyzed. The computational results show that the heuristic algorithm can generate near-optimal solutions. Finally, we offer a fully polynomial-time approximation scheme for a fixed number of machines. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 492–502, 2016.
Identifier
84995688342 (Scopus)
Publication Title
Naval Research Logistics
External Full Text Location
https://doi.org/10.1002/nav.21715
e-ISSN
15206750
ISSN
0894069X
First Page
492
Last Page
502
Issue
6
Volume
63
Recommended Citation
    Gong, Hua; Tang, Lixin; and Leung, Joseph Y.T., "Parallel machine scheduling with batch deliveries to minimize total flow time and delivery cost" (2016). Faculty Publications.  10304.
    
    
    
        https://digitalcommons.njit.edu/fac_pubs/10304
    
 
				 
					