Abstract
The gravitational search algorithm (GSA) is a novel metaheuristics approach inspired by the laws of gravitation and motion. In GSA, a set of agents, called masses, searches the design space to find the optimal solution by simulation of Newtonian laws of gravity and motion. In this paper, a standard and an improved GSA (IGSA) approach based on a quasi-oppositional approach are presented and tested on a magnetic pole design benchmark. Results indicate that the performance of proposed IGSA on the magnetic pole design is better than that of classical GSA.
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