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
This paper presents an improved gravitational search algorithm （IGSA） as a hybridization of a relatively recent evolutionary algorithm called gravitational search algorithm （GSA）, with the free search differential...This paper presents an improved gravitational search algorithm （IGSA） as a hybridization of a relatively recent evolutionary algorithm called gravitational search algorithm （GSA）, with the free search differential evolution （FSDE）. This combination incorporates FSDE into the optimization process of GSA with an attempt to avoid the premature convergence in GSA. This strategy makes full use of the exploration ability of GSA and the exploitation ability of FSDE. IGSA is tested on a suite of benchmark functions. The experimental results demonstrate the good performance of IGSA.展开更多
A novel and simple technique to control the search direction of the differential mutation was proposed.In order to verify the performance of this method,ten widely used benchmark functions were chosen and the results ...A novel and simple technique to control the search direction of the differential mutation was proposed.In order to verify the performance of this method,ten widely used benchmark functions were chosen and the results were compared with the original differential evolution(DE)algorithm.Experimental results indicate that the search direction controlled DE algorithm obtains better results than the original DE algorithm in term of the solution quality and convergence rate.展开更多
In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scena...In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scenario,on the basis of geometric relationship of each phase trajectory,the problem of trajectory planning is transformed to parameter optimizing,and then auxiliary population-based quantum differential evolution algorithm(AP-QDEA)is applied as a tool to optimize the objective function,and the design parameters of the whole homing trajectory are obtained.The proposed AP-QDEA combines the strengths of differential evolution algorithm(DEA)and quantum evolution algorithm(QEA),and the notion of auxiliary population is introduced into the proposed algorithm to improve the searching precision and speed.The simulation results show that the proposed AP-QDEA is proven its superior in both effectiveness and efficiency by solving a set of benchmark problems,and the multiphase homing scheme can fulfill the requirement of fixed-points and upwind landing in the process of homing which is simple in control and facile in practice as well.展开更多
A multi-objective optimization model for draft scheduling of hot strip mill was presented, rolling power minimizing, rolling force ratio distribution and good strip shape as the objective functions. A multi-objective ...A multi-objective optimization model for draft scheduling of hot strip mill was presented, rolling power minimizing, rolling force ratio distribution and good strip shape as the objective functions. A multi-objective differential evolution algorithm based on decomposition （MODE/D）. The two-objective and three-objective optimization experiments were performed respectively to demonstrate the optimal solutions of trade-off. The simulation results show that MODE/D can obtain a good Pareto-optimal front, which suggests a series of alternative solutions to draft scheduling. The extreme Pareto solutions are found feasible and the centres of the Pareto fronts give a good compromise. The conflict exists between each two ones of three objectives. The final optimal solution is selected from the Pareto-optimal front by the importance of objectives, and it can achieve a better performance in all objective dimensions than the empirical solutions. Finally, the practical application cases confirm the feasibility of the multi-objective approach, and the optimal solutions can gain a better rolling stability than the empirical solutions, and strip flatness decreases from （0± 63） IU to （0±45） IU in industrial production.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supported by the National Natural Science Foundation of China (70871081)the Shanghai Leading Academic Discipline Project of China (S1205YLXK)
文摘This paper presents an improved gravitational search algorithm （IGSA） as a hybridization of a relatively recent evolutionary algorithm called gravitational search algorithm （GSA）, with the free search differential evolution （FSDE）. This combination incorporates FSDE into the optimization process of GSA with an attempt to avoid the premature convergence in GSA. This strategy makes full use of the exploration ability of GSA and the exploitation ability of FSDE. IGSA is tested on a suite of benchmark functions. The experimental results demonstrate the good performance of IGSA.
基金Project(2011FJ3016)supported by the Research Foundation of Science & Technology Office of Hunan Province,China
文摘A novel and simple technique to control the search direction of the differential mutation was proposed.In order to verify the performance of this method,ten widely used benchmark functions were chosen and the results were compared with the original differential evolution(DE)algorithm.Experimental results indicate that the search direction controlled DE algorithm obtains better results than the original DE algorithm in term of the solution quality and convergence rate.
基金Project(61273138) supported by the National Natural Science Foundation of ChinaProjects(KJ2016A169,KJ2015A242) supported by the University Natural Science Research Key Project of Anhui Province,ChinaProject(ZRC2014444) supported by the Talents Program of Anhui Science and Technology University,China
文摘In order to realize safe and accurate homing of parafoil system,a multiphase homing trajectory planning scheme is proposed according to the maneuverability and basic flight characteristics of the vehicle.In this scenario,on the basis of geometric relationship of each phase trajectory,the problem of trajectory planning is transformed to parameter optimizing,and then auxiliary population-based quantum differential evolution algorithm(AP-QDEA)is applied as a tool to optimize the objective function,and the design parameters of the whole homing trajectory are obtained.The proposed AP-QDEA combines the strengths of differential evolution algorithm(DEA)and quantum evolution algorithm(QEA),and the notion of auxiliary population is introduced into the proposed algorithm to improve the searching precision and speed.The simulation results show that the proposed AP-QDEA is proven its superior in both effectiveness and efficiency by solving a set of benchmark problems,and the multiphase homing scheme can fulfill the requirement of fixed-points and upwind landing in the process of homing which is simple in control and facile in practice as well.
基金Projects(50974039,50634030)supported by the National Natural Science Foundation of China
文摘A multi-objective optimization model for draft scheduling of hot strip mill was presented, rolling power minimizing, rolling force ratio distribution and good strip shape as the objective functions. A multi-objective differential evolution algorithm based on decomposition （MODE/D）. The two-objective and three-objective optimization experiments were performed respectively to demonstrate the optimal solutions of trade-off. The simulation results show that MODE/D can obtain a good Pareto-optimal front, which suggests a series of alternative solutions to draft scheduling. The extreme Pareto solutions are found feasible and the centres of the Pareto fronts give a good compromise. The conflict exists between each two ones of three objectives. The final optimal solution is selected from the Pareto-optimal front by the importance of objectives, and it can achieve a better performance in all objective dimensions than the empirical solutions. Finally, the practical application cases confirm the feasibility of the multi-objective approach, and the optimal solutions can gain a better rolling stability than the empirical solutions, and strip flatness decreases from （0± 63） IU to （0±45） IU in industrial production.
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。
