Name
Abstract | ||
|---|---|---|
This article addresses the flexible job-shop scheduling problem (FJSP) to minimize makespan. The FJSP is strongly NP-hard and consists of two sub-problems. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on all machines. To solve this problem, an artificial immune algorithm (AIA) based on integrated approach is proposed. This algorithm uses several strategies for generating the initial population and selecting the individuals for reproduction. Different mutation operators are also utilized for reproducing new individuals. To show the effectiveness of the proposed method, numerical experiments by using benchmark problems are conducted. Consequently, the computational results validate the quality of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.future.2009.10.004 | Future Generation Comp. Syst. |
Keywords | Field | DocType |
flexible job-shop,integrated approach,assigned operation,artificial immune algorithm,different mutation operator,computational result,scheduling,makespan,benchmark problem,capable machine,flexible job-shop scheduling problem | Population,Mathematical optimization,Job shop scheduling,Job shop scheduling problem,Scheduling (computing),Computer science,Flow shop scheduling,Artificial immune algorithm,Distributed computing,Mutation operator | Journal |
Volume | Issue | ISSN |
26 | 4 | Future Generation Computer Systems |
Citations | PageRank | References |
49 | 1.57 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Bagheri | 1 | 49 | 1.57 |
| M. Zandieh | 2 | 988 | 46.21 |
| Iraj Mahdavi | 3 | 388 | 32.30 |
| M. Yazdani | 4 | 145 | 6.72 |