Scheduling reentrant jobs on parallel machines with a remote server

• Published in: Computers & operations research Vol. 36; no. 9; pp. 2580 - 2589
• Main Authors: Chakhlevitch, K., Glass, C.A.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-09-2009; Elsevier; Pergamon Press Inc
• Subjects: Applied sciences; Benchmarks; Exact sciences and technology; Flows in networks. Combinatorial problems; Heuristic; Laboratories; Logistics; Microbiology laboratory; Operational research and scientific management; Operational research. Management science; Parallel identical machines; Parallel processing; Production scheduling; Reentrant jobs; Remote server; Scheduling; Studies; Microbiology laboratory; Scheduling; Remote server; Parallel identical machines; Reentrant jobs; Combinatorial problem; Task scheduling; Parallel machines; Combinatorial optimization; Workload; Reentrant phase; Heuristic method; NP hard problem; Logistics
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2008.11.007

This paper explores a specific combinatorial problem relating to reentrant jobs on parallel primary machines, with a remote server machine. A middle operation is required by each job on the server before it returns to its primary processing machine. The problem, which is new to the literature, is inspired by the logistics of a semi-automated microbiology laboratory. We establish the NP-hard nature of the problem, and demonstrate various structural properties. A heuristic is developed and tested on randomly generated benchmark data. No alternative heuristics are available in the literature for comparison, but results indicate solutions reliably within 1.5% of optimum. Moreover, tests of our heuristic on real-life data from the microbiology laboratory provide a 20% improvement in throughput relative to current practice.