TY - GEN
T1 - A Hybrid Multi-objective Genetic Algorithm Combined with Dispatching Rule for Wafer Test Scheduling
AU - Chen, Chun An
AU - Wang, Hung Kai
AU - Wu, Chia Le
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Wafer test, also known as wafer probe or wafer sort, is a critical process that ensures the quality of dies after the wafer has been fabricated. Wafer testing process involves multiple components, including tester, prober, load board (LB), and probe card (PC), and solving the wafer test scheduling problem (WTSP) can be challenging due to its complexity. Traditional algorithms often struggle with large-scale problems in this domain. To address this issue, this paper aims to propose a hybrid multi-objective generic algorithm combined with a dispatching rule to solve WTSP. In this paper we compared our algorithm with dispatching rules and non-dominated sorting genetic algorithm (NSGAII) combined with variable neighborhood descent algorithm (VND) in terms of minimizing tardy jobs and reducing the changeover of PC and LB. The results demonstrate that our algorithm is capable of effectively solving large-scale scheduling problems.
AB - Wafer test, also known as wafer probe or wafer sort, is a critical process that ensures the quality of dies after the wafer has been fabricated. Wafer testing process involves multiple components, including tester, prober, load board (LB), and probe card (PC), and solving the wafer test scheduling problem (WTSP) can be challenging due to its complexity. Traditional algorithms often struggle with large-scale problems in this domain. To address this issue, this paper aims to propose a hybrid multi-objective generic algorithm combined with a dispatching rule to solve WTSP. In this paper we compared our algorithm with dispatching rules and non-dominated sorting genetic algorithm (NSGAII) combined with variable neighborhood descent algorithm (VND) in terms of minimizing tardy jobs and reducing the changeover of PC and LB. The results demonstrate that our algorithm is capable of effectively solving large-scale scheduling problems.
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U2 - 10.1007/978-981-97-0194-0_10
DO - 10.1007/978-981-97-0194-0_10
M3 - Conference contribution
AN - SCOPUS:85193255367
SN - 9789819701933
T3 - Lecture Notes in Mechanical Engineering
SP - 81
EP - 87
BT - Proceedings of Industrial Engineering and Management - International Conference on Smart Manufacturing, Industrial and Logistics Engineering and Asian Conference of Management Science and Applications
A2 - Chien, Chen-Fu
A2 - Dou, Runliang
A2 - Luo, Li
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Smart Manufacturing, Industrial and Logistics Engineering, SMILE 2023 and the 7th Asian Conference of Management Science and Applications, ACMSA 2023
Y2 - 17 November 2023 through 19 November 2023
ER -