Abstract
Although GSA is an effective optimization algorithm, the best fitness found by GSA cannot be improved in every generation. In order to improve the performance of GSA, this paper proposed an improved gravitational search algorithm (IGSA). In IGSA, a crossover operation is introduced in IGSA so that each solution can inherit some useful information from the global best solution. The exploitation capability of the algorithm can be greatly enhanced. The linearly decreasing weight is used to balance the global and local search abilities. To verify the effectiveness of IGSA, numerical experiments are carried on ten benchmark problems from CEC2014. The experimental results show that IGSA is competitive with respect to other compared algorithms for solving optimization problems.
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