Abstract
The layout design with dynamic performance constraints belong to NP-hard problem in mathematics, optimized with the general particle swarm optimization (PSO), to slow down convergence and easy trap in local optima. This paper, taking the layout problem of satellite cabins as background, proposed an adaptive particle swarm optimizer with a excellent search performance, which employs a dynamic inertia factor, a dynamic graph planeradius and a set of dynamic search operator of space and velocity, to plan large-scale space global search and refined local search as a whole in optimization process, and to quicken convergence speed, avoid premature problem, economize computational expenses, and obtain global optimum. The experiment on the proposed algorithm and its comparison with other published methods on constrained layout examples demonstrate 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). Constrained Layout Optimization Based on Adaptive Particle Swarm Optimizer. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2009. Lecture Notes in Computer Science, vol 5821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04843-2_46
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DOI: https://doi.org/10.1007/978-3-642-04843-2_46
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