为了解决因花授粉算法搜索方程存在的不足所导致的易早熟、后期收敛速度慢和寻优精度低的问题,提出了一种新授粉方式的花授粉算法(Flower Pollination Algorithm with New pollination Methods,NMFPA)。该算法把惯性权重和两组随机个体...为了解决因花授粉算法搜索方程存在的不足所导致的易早熟、后期收敛速度慢和寻优精度低的问题,提出了一种新授粉方式的花授粉算法(Flower Pollination Algorithm with New pollination Methods,NMFPA)。该算法把惯性权重和两组随机个体差异矢量融入到全局搜索,组成新的全局授粉,以保持种群的差异性,提高算法的全局探索能力;利用信息共享机制与两种新的变异策略构建新局部授粉策略,增强算法的局部开发能力;为了减少个体进化的盲目性,提高算法的收敛速度和精度,采用基于高斯变异的最优个体来引导其他种群个体的进化方向,并且引入非均匀变异机制增加种群的多样性,避免算法易陷入局部极值点,提升算法的全局优化性能。在22个测试函数上进行数值仿真实验,实验结果和统计分析验证了新算法较标准FPA算法,在收敛精度和速度上有明显提升,且能够较好地解决早熟问题。此外,与已有改进的FPA算法从多角度进行对比分析,实验结果表明改进算法是一种富有竞争力的新算法。同时,运用NMFPA算法求解置换流水车间调度问题,实验结果验证了新算法用于解决实际工程问题是可行的,且具有一定的优势。展开更多
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa...In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.展开更多
For the Boltzmann equation with an external force in the form of the gradient of a potential function in space variable, the stability of its stationary solutions as local Maxwellians was studied by S. Ukai et al. （2...For the Boltzmann equation with an external force in the form of the gradient of a potential function in space variable, the stability of its stationary solutions as local Maxwellians was studied by S. Ukai et al. （2005） through the energy method. Based on this stability analysis and some techniques on analyzing the convergence rates to stationary solutions for the compressible Navier-Stokes equations, in this paper, we study the convergence rate to the above stationary solutions for the Boltzmann equation which is a fundamental equation in statistical physics for non-equilibrium rarefied gas. By combining the dissipation from the viscosity and heat conductivity on the fluid components and the dissipation on the non-fluid component through the celebrated H-theorem, a convergence rate of the same order as the one for the compressible Navier-Stokes is obtained by constructing some energy functionals.展开更多
文摘为了解决因花授粉算法搜索方程存在的不足所导致的易早熟、后期收敛速度慢和寻优精度低的问题,提出了一种新授粉方式的花授粉算法(Flower Pollination Algorithm with New pollination Methods,NMFPA)。该算法把惯性权重和两组随机个体差异矢量融入到全局搜索,组成新的全局授粉,以保持种群的差异性,提高算法的全局探索能力;利用信息共享机制与两种新的变异策略构建新局部授粉策略,增强算法的局部开发能力;为了减少个体进化的盲目性,提高算法的收敛速度和精度,采用基于高斯变异的最优个体来引导其他种群个体的进化方向,并且引入非均匀变异机制增加种群的多样性,避免算法易陷入局部极值点,提升算法的全局优化性能。在22个测试函数上进行数值仿真实验,实验结果和统计分析验证了新算法较标准FPA算法,在收敛精度和速度上有明显提升,且能够较好地解决早熟问题。此外,与已有改进的FPA算法从多角度进行对比分析,实验结果表明改进算法是一种富有竞争力的新算法。同时,运用NMFPA算法求解置换流水车间调度问题,实验结果验证了新算法用于解决实际工程问题是可行的,且具有一定的优势。
基金Supported by the Major State Basic Research Development Program of China (2012CB720500)the National Natural Science Foundation of China (Key Program: U1162202)+1 种基金the National Natural Science Foundation of China (General Program:61174118)Shanghai Leading Academic Discipline Project (B504)
文摘In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
基金Project supported by the Grant-in-Aid for Scientific Research (C) (No. 136470207)the Japan Society for the Promotion of Science (JSPS)+1 种基金the Strategic Research Grant of City University of Hong Kong (No.7001608)the National Natural Science Foundation of China (No.10431060, No.10329101).
文摘For the Boltzmann equation with an external force in the form of the gradient of a potential function in space variable, the stability of its stationary solutions as local Maxwellians was studied by S. Ukai et al. （2005） through the energy method. Based on this stability analysis and some techniques on analyzing the convergence rates to stationary solutions for the compressible Navier-Stokes equations, in this paper, we study the convergence rate to the above stationary solutions for the Boltzmann equation which is a fundamental equation in statistical physics for non-equilibrium rarefied gas. By combining the dissipation from the viscosity and heat conductivity on the fluid components and the dissipation on the non-fluid component through the celebrated H-theorem, a convergence rate of the same order as the one for the compressible Navier-Stokes is obtained by constructing some energy functionals.
