| contributor author | H. Fujimoto | |
| contributor author | M. F. Sebaaly | |
| date accessioned | 2017-05-09T00:02:58Z | |
| date available | 2017-05-09T00:02:58Z | |
| date copyright | February, 2000 | |
| date issued | 2000 | |
| identifier issn | 1087-1357 | |
| identifier other | JMSEFK-27355#198_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/124026 | |
| description abstract | Assembly planning is the problem of finding the best or optimal sequence to assemble a product, starting from its design data. It is still solved manually in most advanced assembly plants, despite the large amount of related research. One of the main reasons might be the use of exact- and/or linear-solution approaches. This paper introduces a different approach by applying a modified genetic algorithm (GA). A “best” solution is generated without searching the complete candidate space, while search is performed on a sequence population basis. The GA is modified to cope with sequence nonlinearity and constraints. [S1087-1357(00)70401-1] | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | A New Sequence Evolution Approach to Assembly Planning | |
| type | Journal Paper | |
| journal volume | 122 | |
| journal issue | 1 | |
| journal title | Journal of Manufacturing Science and Engineering | |
| identifier doi | 10.1115/1.538897 | |
| journal fristpage | 198 | |
| journal lastpage | 205 | |
| identifier eissn | 1528-8935 | |
| keywords | Manufacturing | |
| tree | Journal of Manufacturing Science and Engineering:;2000:;volume( 122 ):;issue: 001 | |
| contenttype | Fulltext | |
