The Bi-objective Active-Scan Agile Earth Observation Satellite Scheduling Problem: Modeling and Solution Approach

The active-scan agile earth observation satellite (AS-AEOS) is highly agile in three axis which enables in-motion imaging, allowing any imaging direction for a given ground target. Such a high agility drastically increases the difficulty of the scheduling problem. In this paper, we consider a bi-objective AS-AEOS scheduling problem such that we simultaneously maximize the total reward and the overall quality of the scheduled requests, seeking to maximize the profit gain of the satellite owners and the satisfaction of the customers. The main contributions of this paper are two folds: the proposal of a constrained optimization model for formulating the problem, and the design of a Hybrid Coding Based Multi-objective Differential Evolution (HCBMDE) method for the problem solution. In computational experiments, two category scenarios are designed to test the effectiveness of the proposed HCBMDE method. Computational results show that, the proposed method is able to achieve a high quality approximate Pareto front.