TY - JOUR
T1 - A sequence learning harmony search algorithm for the flexible process planning problem
AU - Luo, Kaiping
N1 - Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Flexible process planning involves selecting and sequencing the requisite operations, and assigning the right machine, tool and access direction to each selected operation for minimising the production cost or the completion time. It is one of the challenging combinatorial optimisation problems due to sequencing flexibility, processing flexibility and operation flexibility. A sequence learning harmony search algorithm is accordingly proposed. Distinctively, the well-designed algorithm searches for the optimal process plan by intelligently finding the proper immediate successor for each selected operation in turn rather than resorting to the common shifting and swapping operators in sequencing. The innovative algorithm does not also require extra efforts to plot the operational precedence graph or the AND/OR-network graph. The experimental results indicate that the proposed algorithm significantly outperforms other heuristics in terms of the quality of solution found and the convergence rate of the algorithm. For the large-scale complicated instances, the proposed algorithm establishes a challenging flag.
AB - Flexible process planning involves selecting and sequencing the requisite operations, and assigning the right machine, tool and access direction to each selected operation for minimising the production cost or the completion time. It is one of the challenging combinatorial optimisation problems due to sequencing flexibility, processing flexibility and operation flexibility. A sequence learning harmony search algorithm is accordingly proposed. Distinctively, the well-designed algorithm searches for the optimal process plan by intelligently finding the proper immediate successor for each selected operation in turn rather than resorting to the common shifting and swapping operators in sequencing. The innovative algorithm does not also require extra efforts to plot the operational precedence graph or the AND/OR-network graph. The experimental results indicate that the proposed algorithm significantly outperforms other heuristics in terms of the quality of solution found and the convergence rate of the algorithm. For the large-scale complicated instances, the proposed algorithm establishes a challenging flag.
KW - Flexible manufacturing systems
KW - computer-aided manufacturing
KW - flexible process planning
KW - harmony search
KW - sequence learning
UR - https://www.scopus.com/pages/publications/85104337839
U2 - 10.1080/00207543.2021.1912432
DO - 10.1080/00207543.2021.1912432
M3 - 文章
AN - SCOPUS:85104337839
SN - 0020-7543
VL - 60
SP - 3182
EP - 3200
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 10
ER -