Abstract: This paper presents a new parallel hybrid differential evolution (PHDE) algorithm for optimal scheduling of cascade reservoirs by combining a chaos algorithm (CA) and a shuffled leapfrog algorithm (SLFA) for their advantages in local search with parallel computation (PC) technique and using a basic framework of difference evolution (DE). PHDE is an organic fusion of DE, CA, SLFA and PC, i.e. conducting chaotic local search for better individuals and leapfrog local search for worse individuals, and its computation of DE, CA and SLFA is combined with PC so as to reduce running time. Therefore, this algorithm has three advantages: it reserves the simplicity and fast convergence of DE; it inherits the ergodicity from CA and SLFA so as to avoid premature convergence; it has a relative shorter computing time. The testing results of typical functions verified its better feasibility, efficiency and robustness. Case studies showed that it can achieve better optimization performance, thus offering an efficient tool for solving optimal operation model of cascade reservoirs.