Evolutionary computation techniques for optimizing fuzzy cognitive maps in radiation therapy systems

Abstract. The optimization of a Fuzzy Cognitive Map model for the supervision and monitoring of the radiotherapy process is proposed. This is performed through the minimization of the corresponding objective function by using the Particle Swarm Optimization and the Differential Evolution algorithms. The proposed approach determines the cause–effect relationships among the concepts of the supervisor–Fuzzy Cognitive Map by computing its optimal weight matrix, through extensive experiments. Results are reported and discussed.