WSEAS Transactions on Computers
Print ISSN: 1109-2750, E-ISSN: 2224-2872
Volume 15, 2016
A Whale Optimization Algorithm with Inertia Weight
Authors: , ,
Abstract: Whale Optimization Algorithm (WOA) is a novel nature-inspired meta-heuristic optimization algorithm proposed by Seyedali Mirjalili and Andrew Lewis in 2016, which mimics the social behavior of humpback whales. A new control parameter, inertia weight, is introduced to tune the influence on the current best solution, and an improved whale optimization algorithm(IWOA) is obtained. IWOA is tested with 31 high-dimensional continuous benchmark functions. The numerical results demonstrate that the proposed IWOA is a powerful search algorithm. Optimization results prove that the proposed IWOA not only significantly improves the basic whale optimization algorithm but also performs much better than both the artificial bee colony algorithm(ABC) and the fruit fly optimization algorithm(FOA).
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Keywords: whale optimization algorithm, artificial bee colony algorithm, fruit fly optimization algorithm, inertia weight, benchmark functions
Pages: 319-326
WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 15, 2016, Art. #30