To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individua...To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.展开更多
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
充分考虑实际生产过程中的批量生产形式,构建以最小最大完工时间为目标的置换流水车间分批调度问题的数学模型,并提出一种改进的人工兔优化算法。在编码阶段,采用最小位置值(smallest position value,SPV)规则实现连续解向离散解的转变...充分考虑实际生产过程中的批量生产形式,构建以最小最大完工时间为目标的置换流水车间分批调度问题的数学模型,并提出一种改进的人工兔优化算法。在编码阶段,采用最小位置值(smallest position value,SPV)规则实现连续解向离散解的转变;在解码阶段,采用动态策略对工件进行分批;通过NEH启发式规则改善初始种群的质量;引入差分进化算子提高解的多样性;提出基于交换和逆序的局部搜索策略增强算法跳出局部最优解的能力。将所提算法和其他对比算法对不同规模的算例进行求解,通过消融实验、对比实验、统计检验等证明了算法的有效性。最后对某汽车外饰件厂喷涂车间排产问题进行求解,求解结果优于其他对比算法,进一步证明了所提算法的有效性。展开更多
基金Project(2013CB733600) supported by the National Basic Research Program of ChinaProject(21176073) supported by the National Natural Science Foundation of China+2 种基金Project(20090074110005) supported by Doctoral Fund of Ministry of Education of ChinaProject(NCET-09-0346) supported by Program for New Century Excellent Talents in University of ChinaProject(09SG29) supported by "Shu Guang", China
文摘To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
文摘充分考虑实际生产过程中的批量生产形式,构建以最小最大完工时间为目标的置换流水车间分批调度问题的数学模型,并提出一种改进的人工兔优化算法。在编码阶段,采用最小位置值(smallest position value,SPV)规则实现连续解向离散解的转变;在解码阶段,采用动态策略对工件进行分批;通过NEH启发式规则改善初始种群的质量;引入差分进化算子提高解的多样性;提出基于交换和逆序的局部搜索策略增强算法跳出局部最优解的能力。将所提算法和其他对比算法对不同规模的算例进行求解,通过消融实验、对比实验、统计检验等证明了算法的有效性。最后对某汽车外饰件厂喷涂车间排产问题进行求解,求解结果优于其他对比算法,进一步证明了所提算法的有效性。
