Abstract
The complex layout optimization problems with behavioral constraints belong to NP-hard problem in math. Due to its complexity, the general particle swarm optimization algorithm converges slowly and easily to local optima. Taking the layout problem of satellite cabins as background, a novel adaptive particle swarm optimizer based on multi-modified strategies is proposed in the paper, which can not only escape from the attraction of local optima of the later phase to heighten particle diversity, and avoid premature problem, but also maintain the characteristic of fast speed search in the early convergence phase to get global optimum, thus, the algorithm has a better search performance to deal with the constrained layout optimization problem. The proposed algorithm is tested and compared it with other published methods on constrained layout examples, demonstrated that the revised algorithm is feasible and efficient.
The work is supported by Key Project of Chinese Ministry of Education (104262).
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Lei, K. (2009). Research on Constrained Layout Optimization Problem Using Multi-adaptive Strategies Particle Swarm Optimizer. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_5
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DOI: https://doi.org/10.1007/978-3-642-05253-8_5
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