Name
Abstract | ||
|---|---|---|
Job shops produce products on the basis of manufacturing orders which specify the due date and the volume. The orders accepted by the shop floor are put into a job pool. The job release decides when to start each job in the pool. It attempts not only to balance this time-varying demand against available capacity, but also manages to meet the due date constraints. The general job release policies, such as output-based or workload-based policies, have poor due date performance. A multi-time-periods release policy is proposed to match the time-varying demand. The due date pressure is distributed to every period. In each time period a near optimal short-term throughput of each product is obtained by an optimization model. The optimization problem is solved by an improved ant colony algorithm. In iteration processes of the algorithm ants are evaluated by the simulation which involves the setup and breakdown of machines. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/WSC.2014.7020065 | Winter Simulation Conference |
Keywords | Field | DocType |
workload-based policy,iteration process,due date constraint,ant colony optimisation,job release policy,time-varying systems,time-varying product mix,time-varying demand,ant colony algorithm,multitime-period release policy,job shop scheduling,job pool,shop floor,due date performance,manufacturing order,due date pressure,order processing,output-based policy,near optimal short-term throughput,job shop,iterative methods,algorithm ant | Ant colony optimization algorithms,Product mix,Job shop scheduling,Workload,Computer science,Simulation,Flow shop scheduling,Operations research,Throughput,Job queue,Optimization problem | Conference |
ISSN | ISBN | Citations |
0891-7736 | 978-1-4673-9741-4 | 0 |
PageRank | References | Authors |
0.34 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Zhang | 1 | 2 | 3.12 |
| Oliver Rose | 2 | 17 | 10.43 |