Combining the advantages of a genetic algorithm and an artificial immune system,a novel genetic algorithm named immune genetic algorithm based on quasi secondary response(IGA-QSR)is proposed.IGA-QSR employs a database to simulate the standard secondary response and the quasi secondary response.Elitist strategy,automatic extinction,clonal propagation,diversity guarantee,and selection based on comprehensive fitness are also used in the process of IGA-QSR.Theoretical analysis,numerical examples of three benchmark mathematical optimization problems and a traveling salesman problem all demonstrate that IGA-QSR is more effective not only on convergence speed but also on convergence probability than a simple genetic algorithm with the elitist strategy(SGA-ES).Besides,IGA-QSR allows the designers to stop and restart the optimization process freely without losing the best results that have already been obtained.These properties make IGA-QSR be a feasible,effective and robust search algorithm for complex engineering problems.
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机译:Protective Immune Response in BALB/c Mice Induced by the E72-296 Protein of Rubella VirusAU Li, Zhen-Mei Sun, Zi-Hao Wen, Hong-Ling Lin, Bin Chu, Fu-Lu Li, Guo-Hong Wang, Zhi-Yu (zhiyu.wang@sdu.edu.cn)
机译:AMT-2019-95: A GPS water vapor tomography method based on a genetic algorithm, by Fei Yang, Jiming Guo, Junbo Shi, Xiaolin Meng, Yinzhi Zhao, Lv Zhou, and Di Zhang