Solving satellite image data downlink scheduling problem with family attribute via a bi-stage differential evolutionary algorithm

Due to the asynchronous development of observation and transition capabilities, the original image data ( OID ) obtained by a one-time observation cannot be completely transmitted in one transmission cycle between the EOS and GS , which is named a visible time window ( VTW ). First, it is needed to segment the OID into several segmented image datasets ( SIDs ), which are then transmitted in several VTWs . Furthermore, this can cause the satellite image data downlink scheduling problem ( SIDSP ). This study defines an innovative SIDSP as a satellite image data downlink scheduling problem with the family attribute ( SIDSPFA ), where massive OID are segmented using a fast segmentation operator, and all SIDs and other no-segmented OID are transmitted in the second step. In addition, two optimization objectives, namely the failure rate ( FR ) and Segmentation Time ( ST ) of the image data transmission, are defined to formalize the SIDSPFA as a bi-objective discrete optimization model. Further, a bi-stage differential evolutionary algorithm ( DE-CD ) is developed. The results of the extensive simulation tests verify the efficiency of the models, strategies, algorithms, and operators used in this study.