Swarm behavior in nature has inspired the emergence of many heuristic optimization algorithms. They have attracted attention, particularly for complex problems due to high dimensionality, non-differentiability, and the like. In this study, a new heuristic algorithm is proposed, inspired from the prey finding/locating and communication behaviors of electric fish. Nocturnal electric fish have very poor eyesight and live in muddy murky water where visual sense is very limited. Therefore, they rely on their species-specific ability called electrolocation to perceive their environment. The active and passive electrolocation capability of such fish is believed to be a good candidate for balancing local and global search, hence modelled in this study. A new heuristic called Electric Fish Optimization (EFO) is introduced to the community.