Title:
Parallel_Artificial_Immune_Algorithm_for_Large_Sca
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Description: This paper presents a parallel model termed as towerlike master slave model (TMSM) for artificial immune systems. Based on TMSM, the parallel immune memory clonal selection algorithm ( PIMCSA) is also designed for dealing with large scale TSP problems. TMSM is a two level coarse grained parallel artificial immune model with distributed immune response and dis
tributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than antibodies as has been done in parallel genetic algorithms, it is a good balance between the diversity maintenance of populations and the convergent speed of the algorithm. PIMCSA shows superiority over other compared approaches both in solution quality and computation time, and the
lager the problem size the more outstanding the predominance will be. TMSM is a good simulation of biological immune system, and PIMCSA is a parallel artificial immune algorithm with good extensibility, which is capable of solving large scale and c
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基于并行人工免疫算法的大规模TSP问题求解.pdf
