An effective detailed operation scheduling in MES based on hybrid genetic algorithm
L Zhou, Z Chen, S Chen - Journal of Intelligent Manufacturing, 2018 - Springer
L Zhou, Z Chen, S Chen
Journal of Intelligent Manufacturing, 2018•SpringerA detailed operation scheduling solution based on hybrid genetic algorithm is proposed and
integrated with the manufacturing execution system (MES) for multi-objective scheduling.
The constraints and influences from real-time production information collected by MES will
all be considered in scheduling procedures. Each order can be scheduled forward or
backward and the various constraints such as the ones from working calendar, processing
capacity of manufacturing resources and the connection type between the operation and the …
integrated with the manufacturing execution system (MES) for multi-objective scheduling.
The constraints and influences from real-time production information collected by MES will
all be considered in scheduling procedures. Each order can be scheduled forward or
backward and the various constraints such as the ones from working calendar, processing
capacity of manufacturing resources and the connection type between the operation and the …
Abstract
A detailed operation scheduling solution based on hybrid genetic algorithm is proposed and integrated with the manufacturing execution system (MES) for multi-objective scheduling. The constraints and influences from real-time production information collected by MES will all be considered in scheduling procedures. Each order can be scheduled forward or backward and the various constraints such as the ones from working calendar, processing capacity of manufacturing resources and the connection type between the operation and the previous operation will be obeyed in scheduling. A genetic algorithm is designed according to the features of the scheduling problem. Two methods of operation sequence (OS) initialization (named as OSIOP and ROSI) and three methods of manufacturing resource selection (named as RSAPT, RSWTB and RRS) are designed for population initialization. A variable neighborhood search is designed and implanted in the process of GA to improve the scheduling results. The experiments are made and the results have proved the feasibility of the hybrid GA. This scheduling solution is programmed in and applied to a commercial MES software successfully.
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