A human-computer cooperative particle swarm optimization based immune algorithm for layout design

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Zhao, Fengqiang
Li, Guangqiang
Yang, Chao
Abraham, Ajith
Liu, Hongbo

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Elsevier

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Abstract

Packing and layout problems have wide applications in engineering practice. However, they belong to NP (non-deterministic polynomial)-complete problems. In this paper, we introduce human intelligence into the computational intelligent algorithms, namely particle swarm optimization (PSO) and immune algorithms (IA). A novel human–computer cooperative PSO-based immune algorithm (HCPSO-IA) is proposed, in which the initial population consists of the initial artificial individuals supplied by human and the initial algorithm individuals are generated by a chaotic strategy. Some new artificial individuals are introduced to replace the inferior individuals of the population. HCPSO-IA benefits by giving free rein to the talents of designers and computers, and contributes to solving complex layout design problems. The experimental results illustrate that the proposed algorithm is feasible and effective.

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human–computer cooperation, genetic algorithms, immune function, particle swarm optimization, hybrid, layout

Citation

Neurocomputing. 2014, vol. 132, p. 68-78.