Quasi opposition-based Hybrid Thunnus—Parupeneus cyclostomus Optimization Algorithm (QHTP) is applied for solving the Factual power loss reduction problem. In the Quasi opposition-based hybrid Thunnus- Parupeneus cyclostomus Optimization Algorithm (QHTP), stalking properties of Thunnus are hybridized with the tracking and prohibiting actions of Parupeneus cyclostomus. Quasi opposition-based learning approach is applied to the hybridized procedure. Systematic enactments of Thunnus have been utilized to formulate the algorithm. Thunnus is gluttonous and stalk the Dussumieria at gathering level. Thunnus algorithm competitor explication in the planned procedure and populace in the examination region is comprehensively impelled. Parupeneus cyclostomus Optimization algorithm has been formulated based on the actions of Parupeneus cyclostomus. Few Parupeneus cyclostomus will chase the quarry, others will act as prohibitors and quarry won’t realize to escape from the region. In assortment of principal and sub groups are premeditated. Validity of Quasi opposition-based Hybrid Thunnus—Parupeneus cyclostomus Optimization Algorithm (QHTP) is verified in IEEE 118 bus system and 220 kV network.