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Symbiotic Organisms Search for Constrained Optimization Problems
Yanjiao Wang,Huanhuan Tao,Zhuang Ma 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.1
Since constrained optimization algorithms are easy to fall into local optimum and their ability of searching areweak, an improved symbiotic organisms search algorithm with mixed strategy based on adaptive ε constrained(ε_SOSMS) is proposed in this paper. Firstly, an adaptive ε constrained method is presented to balance therelationship between the constrained violation degrees and fitness. Secondly, the evolutionary strategies ofsymbiotic organisms search algorithm are improved as follows. Selecting different best individuals accordingto the proportion of feasible individuals and infeasible individuals to make evolutionary strategy more suitablefor solving constrained optimization problems, and the individual comparison criteria is replaced withpopulation selection strategy, which can better enhance the diversity of population. Finally, numericalexperiments on 13 benchmark functions show that not only is ε_SOSMS able to converge to the global optimalsolution, but also it has better robustness.
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Contact toxicity of a new acaricide, SYP-9625, to the natural predator, Chrysopa pallens
Feng Yanjiao,Zhang Lisheng,Chen Hongyin,Wang Mengqing,Liu Chenxi,Li Yuyan,Song Yuquan,Mao Jianjun 한국응용곤충학회 2021 Journal of Asia-Pacific Entomology Vol.24 No.2
SYP-9625 is a novel acaricide synthesized by using cyenopyrafen as lead compound. It is characterized by high acaricidal activity and low toxicity to mammals and has been widely used in Chinese farming areas. However, to date, the toxicity of SYP-9625 to natural enemy insects remained unclear. Here, we evaluated the effects of SYP-9625 on survival, growth, metamorphosis and reproduction of a common natural predator, Chrysopa pallens. Contact toxicity bioassay revealed that SYP-9625 had no significant detrimental impacts on egg hatchability, larval survival and duration, pupation rate, pupal mass, emergence rate, digestive enzyme activity, reproductive output and offspring quality, but drastically reduced adult survival rate, adult lifespan, secondary follicle size and vitellogenin (Vg) transcripts by 27.8%, 15.4%, 33.4% and 59.4%, respectively, suggesting a low contact toxicity of SYP-9625 to C. pallens. This study will strengthen the compatibility of chemical acaricide and natural enemy insects in integrated pest management.
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Toyama Takashi,Wang Yanjiao,Kim Min-Seok,Takahashi Tsutomu,Naganuma Akira,Hwang Gi-Wook 한국독성학회 2021 Toxicological Research Vol.37 No.4
Methylmercury is an environmental pollutant that induces potent neurotoxicity. We previously identified transcription factor 3 (TCF3) as a transcription factor that is activated in the brains of mice treated with methylmercury, and reported that methylmercury sensitivity was increased in cells in which TCF3 expression was suppressed. However, the mechanisms involved in the activation of TCF3 by methylmercury and in the reduction of methylmercury toxicity by TCF3 remained unclear. We found that treatment of mouse neuronal C17.2 cells with methylmercury increased TCF3 protein levels and promoted the binding of TCF3 to DNA consensus sequences. In cells treated with actinomycin D, a transcription inhibitor, an increase in TCF3 protein levels was also observed under methylmercury exposure. However, in the presence of cycloheximide, a translation inhibitor, methylmercury delayed the degradation of TCF3 protein. In addition, treatment with MG132, a proteasome inhibitor, increased TCF3 protein levels, and there was not significant increase in TCF3 protein levels by methylmercury under these conditions. These results suggest that methylmercury may activate TCF3 by increasing its levels through inhibition of TCF3 degradation by the proteasome. It has been previously reported that the induction of apoptosis in neurons is involved in methylmercury-induced neuronal damage in the brain. Although apoptosis was induced in C17.2 cells treated with methylmercury, this induction was largely suppressed by overexpression of TCF3. These results indicate that TCF3, which is increased in the brain upon exposure to methylmercury, may be a novel defense factor against methylmercury-induced neurotoxicity.
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Adaptive Truncation technique for Constrained Multi-Objective Optimization
( Lei Zhang ),( Xiaojun Bi ),( Yanjiao Wang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.11
The performance of evolutionary algorithms can be seriously weakened when constraints limit the feasible region of the search space. In this paper we present a constrained multi-objective optimization algorithm based on adaptive ε-truncation (ε-T-CMOA) to further improve distribution and convergence of the obtained solutions. First of all, as a novel constraint handling technique, ε-truncation technique keeps an effective balance between feasible solutions and infeasible solutions by permitting some excellent infeasible solutions with good objective value and low constraint violation to take part in the evolution, so diversity is improved, and convergence is also coordinated. Next, an exponential variation is introduced after differential mutation and crossover to boost the local exploitation ability. At last, the improved crowding density method only selects some Pareto solutions and near solutions to join in calculation, thus it can evaluate the distribution more accurately. The comparative results with other state-of-the-art algorithms show that ε-T-CMOA is more diverse than the other algorithms and it gains better in terms of convergence in some extent.
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A Novel Multiobjective Optimization Method Based on Improved Artificial Bee Colony Algorithm
Wu Chunming,Li Tingting,Wang Yanjiao 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.3
In order to improve the convergence and diversity of multiobjective optimization algorithms, the harmonic average distance is employed to improve the aggregating function combined L-rank value. Selection model and searching scheme of artificial bee colony algorithm and diversity maintaining scheme are improved in this paper. This novel many objectives optimization method based on improved artificial bee colony algorithm (ABC) in this paper is compared with other three many objectives optimization methods on 3 to 8 objectives DTLZ. Simulation results show that the proposed algorithm is superior to other algorithms in the diversity and convergence of solutions.
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