  Observation scheduling problem for agile earth observation satellites
(OSPFAS) plays a critical role in management of agile earth observation
satellites (AEOSs). Active imaging enriches the extension of OSPFAS, we call
the novel problem as observation scheduling problem for AEOS with variable
image duration (OSWVID). A cumulative image quality and a detailed energy
consumption is proposed to build OSWVID as a bi-objective optimization model.
Three multi-objective memetic algorithms, PD+NSGA-II, LA+NSGA-II and
ALNS+NSGA-II, are then designed to solve OSWVID. Considering the heuristic
knowledge summarized in our previous research, several operators are designed
for improving these three algorithms respectively. Based on existing instances,
we analyze the critical parameters optimization, operators evolution, and
efficiency of these three algorithms according to extensive simulation
experiments.
