Abstract This paper describes the fully-informed particle swarm optimization based economic dispatch among hydro-thermal units and compares the results with those obtained from existing heuristic and non-heuristic techniques. The short-term hydro-thermal scheduling is optimized using the meta-heuristic fully-informed particle swarm optimization (FIPSO) which is a variant of the canonical particle swarm optimization (CPSO). The FIPSO helps in finding a good approximation of an optimal solution for nonlinear multi-modal optimization problems by searching the complete search space. A global best (g-best) neighbourhood topology is compared with a local best (l-best) neighbourhood topology to describe the impact of particles’ neighbourhood on the convergence behaviour of the FIPSO algorithm. A standard two-generating-unit based system has been used to demonstrate the effectiveness of the FIPSO in economic scheduling of hydro and thermal units. The results, when compared with those from the literature, reveal the superiority of the proposed FIPSO algorithm.