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The parameters used in harmony search algorithm and particle swarm optimization are found to be of importance to the results, however, there are no theoretical bases or formulae to determine the values of the parameters. A combinatorial method is proposed which combing the harmony search procedure and the particle swarm optimization for the determination of critical slip surfaces of soil slopes. The individuals in the harmony memory are divided into two equal groups, one of which is used to perform the particle swarm optimization algorithm, and the other is adopted in the generation of new harmony in harmony search algorithm, the optimums found by these two groups are compared and communal learning mechanism is formed. In addition, the dynamic adaptation strategy for the determination of values of parameters in these two algorithms is proposed. This combinatorial search algorithm is demonstrated to be efficient and effective for the slope stability analysis.