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An improved imperialist competition algorithm with adaptive differential mutation assimilation strategy for function optimization
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DOI：10.1016/j.eswa.2022.118686.png)
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Abstract
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In imperialist competition algorithm (ICA), the assimilation is an important step, which is responsible for exploring potential better position or solution for an optimization problem. In this paper, an improved ICA equipped with an adaptive differential mutation (ADM) assimilation strategy was proposed inspired by differential evolution (DE). The proposed algorithm is called ICA-ADM. The ADM assimilation strategy generates new positions for colonies in an empire using the ''DE/best/1'' mutation operator and crossover operator with adaptively varied mutation and crossover rate. Since the ''DE/best/1'' mutation and crossover can produce high quality solutions, ICA-ADM possesses good exploration capability. Meanwhile, since the mutation and crossover rates are adaptively varied, ICA-ADM also preserves a good population diversity. Thus, the performance of ICA-ADM is greatly increased. Optimization results on 16 well-known benchmark functions and comparisons verify that the proposed ICA-ADM exceeds the initial ICA and its several variants.
Keywords:
Imperialist competitive algorithm
Differential mutation
Crossover
Function optimization
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7.5
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3.0W
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10.2W
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