Minimum queuing delay: an adaptive algorithm for scheduling in a dynamic job shop

Abstract

The problem of scheduling on the job shop floor is widely encountered in the manufacturing industry. However, generating good job shop schedules in a reasonable time remains a challenging problem, because of its inherent computational complexity. Dynamic job shop scheduling (DJSS) has been proven to be an intractable analytical problem and is largely solved by combinatorial analysis in traditional research. The NP-complete nature of the problem forces many assumptions to be made, which limit the use of analytical methods in practical problem solving. In this paper, the authors propose a new scheme named minimum queuing delay (MQD) for scheduling in a dynamic job shop derived from fair queuing service disciplines for asynchronous transfer mode (ATM) networks. This scheme combines the job process-time and work-content of jobs in the current queues into the dispatching methodology. The main advantage of this scheme is that the queuing delays suffered by all the jobs at every machine are minimized, leading to a minimized maximum completion time (make-span). A smaller queuing delay variation is also achieved using this algorithm. Results from experiments conducted on a testbed with several embedded controllers are presented.