Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Three Scheduling Algorithms Applied to the Earth Observing Systems Domain
Management Science
A comparison of techniques for scheduling earth observing satellites
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Daily imaging scheduling of an Earth observation satellite
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computers and Operations Research
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EOSs (Earth Observing Satellites) circle the earth to take shotswhich are requested by customers. To make replete use of resourcesof EOSs, it is required to deal with the problem of united imagingscheduling of EOSs in a given scheduling horizon, which is acomplicated multi-objective combinatorial optimization problem. Inthis paper, we construct a mathematical model for the problem byabstracting imaging constraints of different EOSs. Then we propose anovel multi-objective EOSs imaging scheduling method, which is basedon the Strength Pareto Evolutionary Algorithm 2. The specialencoding technique and imaging constraint control are applied toguarantee feasibility of solutions. The approach is tested upon fourreal application problems of CBERS EOSs series. From the results, itis confirmed that the proposed approach is effective in solvingmulti-objective EOSs imaging scheduling problems.