Abstract
This paper presents the research and development of the hybridization of a mathematical programming approach with a promising evolution on the daily imaging scheduling problem for the newest generation of low-orbit, earth observation satellite, FORMOSAT-2. This NP-hard satellite scheduling problem belongs to a class of single-machine scheduling problems with salient features of job-assembly characteristic, sequence-dependent setup effect, and constraint of operating time window. We construct innovative hybrid techniques that incorporate the best of Lagrangian relaxation and Tabu search solution approaches to solve this scheduling problem. Numerical results demonstrate that the proposed hybrid algorithms are effective and efficient in applications to the real problems.
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