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In this paper, a new method for optimal locating multi-type FACTS devices in order to optimize multi-objective voltage stability problem is presented. The proposed methodology is based on a new variant of Particle Swarm Optimization (PSO) specialized in multi-objective optimization problem known as Non-dominated Sorting Particle Swarm Optimization (NSPSO). The crowding distance technique is used to maintain the Pareto front size at the chosen limit, without destroying its characteristics. To aid the decision maker choosing the best compromise solution from the Pareto front, the fuzzy-based mechanism is employed for this task. NSPSO is used to find the optimal location and setting of two types of FACTS namely: Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) that maximize Static Voltage Stability Margin (SVSM), reduce Real Power Losses (RPL), and Load Voltage Deviation (LVD). The optimization is carried out on two and three objective functions for various FACTS combinations. The thermal limits of lines and voltage limits of load buses are considered as security constraints. The simulation results show the effectiveness of the proposed NSPSO to solve the multiobjective optimization problem considered and capture Pareto optimal solutions with satisfactory diversity characteristics.