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This paper presents different modified particle swarm optimization (PSO) models for optimal market payment problem. The suggested PSO models use more particles' information to control the global optimal solution search. An adaptive strategy is proposed for choosing PSO parameters to assure the convergence of the proposed models. Also, the proposed models attempt to generate initial population that are scattered uniformly over the feasible solution space that is leads to the capable for obtaining higher quality solutions. The simulation results show that the proposed models prove practical for modelling the impact of different emergency conditions on the expected generation payment under the competitive environment.