International Journal of Mathematics Trends and Technology
Volume 58 | Number 2 | Year 2018 | Article Id. IJMTT-V58P520 | DOI : https://doi.org/10.14445/22315373/IJMTT-V58P520
This paper presents a new modified Grey Wolf Optimization (GWO) Algorithm inspired by the Particle Swarm Optimization (PSO) algorithm. The main features of the proposed algorithm called PSO Inspired Grey Wolf Optimization (PSOIGWO) is the integration of global best and inertia weights into the basic GWO algorithm that allows the better searching capability and quicker convergence. The combination of well-established features of PSO into the newly developed GWO algorithm provides an efficient hybrid algorithm which comprises the best features of the both algorithms. Experiments on standard optimization problems show the usefulness of the combined approach and its ability to efficiently and quickly search the solution.
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Yogendra Singh Kushwah, R.K. Shrivastava, "Particle Swarm Optimization (PSO) Inspired Grey Wolf Optimization (GWO) Algorithm," International Journal of Mathematics Trends and Technology (IJMTT), vol. 58, no. 2, pp. 135-149, 2018. Crossref, https://doi.org/10.14445/22315373/IJMTT-V58P520
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