Simulation Based Multi-objective Extremal Optimization Algorithm for Electronic Reconnaissance Satellites Scheduling Problem

A multi-objective chance constrained programming model (MOCCPM) for electronic reconnaissance satellites scheduling problem (ERSSP) is presented. MOCCPM takes the uncertainties in the course of satellite electronic reconnaissance into account, as well as the capabilities and usage restrictions of the electronic reconnaissance satellites. Then a Monte Carlo simulation based multi-objective extremal optimization (MCSBMOEO) algorithm is proposed. Penalty function based fitness assignment ensures the efficient evolution. Problem specific mutation operator ensures the feasibility of the offspring so as to prevent the algorithm from falling into local optimum. External archive is to keep the non-dominated solutions and guarantee their diversity. Monte Carlo sampling is to address the stochastic nature of ERSSP. The experiment results testified that the algorithm can solve ERSSP effectively.