Conventional intelligent optimization algorithms are inefficient or even impossible in finding feasible solutions to the reservoir optimal dispatch calculations with small time step and large number of calculation periods. On this basis, the damaged vector constraint, piecewise particle swarm optimization(PPSO) algorithm and multi-objective piecewise particle swarm optimization(MOPPSO) algorithm are proposed to successfully solve the problem. This method introduces the damaged vector constraints, piecewise operation and special mutation operation to enhance the quality of populations in the evolution process, thus improving the computational efficiency. Then the algorithms were applied to the multi-objective optimal dispatch of Jinxi cascade reservoirs in Minjiang River Basin. The results show that PPSO and MOPPSO have obvious advantages over other algorithms in the optimal dispatch of reservoirs with small time step and large number of calculation periods.