TY - JOUR A2 - Shahzad, N. AU - Singh, Narinder AU - Singh, S. B. PY - 2017 DA - 2017/11/16 TI - Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance SP - 2030489 VL - 2017 AB - A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum. SN - 1110-757X UR - https://doi.org/10.1155/2017/2030489 DO - 10.1155/2017/2030489 JF - Journal of Applied Mathematics PB - Hindawi KW - ER -