Abstract
Multi-objective optimization focuses on simultaneous optimization of multiple targets. Evolutionary game theory transforms the optimization problem into game strategic problem and using adaptable dynamic game evolution process intelligently obtains the optimized strategy. The problem of multiple frequency offsets estimation in distributed multiple inputs and multiple outputs system is real-world multi-objective search and optimization problems which are naturally posed as non-linear programming problems having multiple objectives. Simulation results evidence the proposed algorithm is superior to other algorithms with more robust convergence and environmental applicability.
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