@article{oai:nagoya.repo.nii.ac.jp:00007342,
 author = {森, 敏彦 and MORI, Toshihiko and 広田, 健治 and HIROTA, Kenji and 宮脇, 舞 and MIYAWAKI, Mai and 平光, 真二 and HIRAMITSU, Shinji},
 issue = {682},
 journal = {日本機械学會論文集 C編},
 month = {Jun},
 note = {An automated design of bending process had been carried out by using a genetic algorithm, where a gene in an edge to be bent and a chromosome in an order of gene. It was considered as a kind of TSP and solved inversely in order to detect a interference easily. GA have been used successfully to solve continuous functional optimization problems, in which crossover operation typically involves only exchanging randomly selected gene of chromosome between two parents to create two children genotypes. However, these genetic operators are not suitable for routing type problems, because an optimal ordering of a list of objects must be found in order to solve the problem. Furthermore, often the selection of operations requires a deep insight into the nature of the specific problem and operations are not portable to real-problems in themselves. In this reports, seven kinds of crossovers were discussed and tested in automated designs of bending process.},
 pages = {1713--1718},
 title = {曲げ工程の自動設計に対する遺伝的アルゴリズム適用における交叉法に関する研究},
 volume = {69},
 year = {2003}
}