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In this paper, a new population based hybrid meta-heuristic algorithm called the Hybrid Whale-Particle Swarm Optimization Algorithm (HWPSO) for solving complex optimization problems has been proposed. The proposed algorithm tries to overcome the limitations associated in a Particle Swarm Optimization (PSO) exploration phase i.e. Stagnation Effect, by hybridizing with a whale optimization algorithm (WOA) in a novel way as WOA has been reported to have very good exploration capability. During hybridization, two novel techniques have been employed, namely ‘Forced’ Whale and ‘Capping’ Phenomenon. The ‘Forced’ WOA is introduced in exploration phase and it enables the WOA to guide PSO for better local optima avoidance and concurrently a new ‘Capping’ phenomenon is employed which restricts the WOA search mechanism during exploitation phase, thereby converging the solution faster to …