Name
Abstract | ||
|---|---|---|
An estimation of distribution algorithm with probability model based on permutation information of neighboring operations for job shop scheduling problem was proposed. The probability model was given using frequency information of pair-wise operations neighboring. Then the structure of optimal individual was marked and the operations of optimal individual were partitioned to some independent sub-blocks. To avoid repeating search in same area and improve search speed, each sub-block was taken as a whole to be adjusted. Also, stochastic adjustment to the operations within each sub-block was introduced to enhance the local search ability. The experimental results show that the proposed algorithm is more robust and efficient. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-17563-3_77 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Job Shop scheduling problem,estimation of distribution algorithm,neighboring operations,probability model | Mathematical optimization,Job shop scheduling,Fair-share scheduling,Estimation of distribution algorithm,Computer science,Permutation,Flow shop scheduling,Rate-monotonic scheduling,Artificial intelligence,Local search (optimization),Dynamic priority scheduling,Machine learning | Conference |
Volume | ISSN | Citations |
6466 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaojuan He | 1 | 25 | 7.75 |
| Jianchao Zeng | 2 | 930 | 94.89 |
| Songdong Xue | 3 | 24 | 4.31 |
| Li-fang Wang | 4 | 10 | 2.94 |