In order to solve a combinatorial optimization problem in discrete domains by using evolutionary algorithms, this study draws lessons from the design concept of genetic algorithm (GA), binary particle swarm optimization (BPSO) and binary differential evolution with hybrid encoding (HBDE), to propose a simple and practical method for designing discrete evolution algorithm (DisEA) based on the idea of mapping transformation. This method is named encoding transformation method (ETM). For illustrating the practicability of ETM, a discrete particle swarm optimization (DisPSO) algorithm based on ETM is presented. For showing the feasibility and effectiveness of ETM, GA, BPSO, HBDE and DisPSO are used to solve the set union knapsack problem (SUKP) and the discounted {0-1} knapsack problem (D{0-1}KP), respectively. The results show that for SUKP and D{0-1}KP, the discrete evolutionary algorithms based on ETM, i.e. BPSO, HBDE and DisPSO have better performance than GA. This indicates that the design of DisEA based on ETM is not only a feasible method, but also a very practical and efficient method.