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基于非支配排序遗传算法的的多学科鲁棒协同优化方法 被引量:4
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作者 李海燕 马明旭 井元伟 《控制理论与应用》 EI CAS CSCD 北大核心 2011年第4期561-566,共6页
针对鲁棒协同优化(robust collaborative optimization,RCO)具有两级优化结构和多目标形式的特点,提出基于非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA--Ⅱ)的RCO求解方法.在NSGA--II非支配排序中,根据个体的不... 针对鲁棒协同优化(robust collaborative optimization,RCO)具有两级优化结构和多目标形式的特点,提出基于非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA--Ⅱ)的RCO求解方法.在NSGA--II非支配排序中,根据个体的不可行度和不可行度阈值来决定其可行性,并给出随进化过程逐渐减小的不可行度阈值.在该阈值的作用下,在进化初期,保留较多的目标函数和标准差较小的个体,以便优化向全局极值点附近靠近;在进化后期,保留较多的学科间一致性好的个体,以便增强学科间的一致性.该方法在保证各子学科间一致性的前提下,可有效避免RCO优化结果易收敛到局部极值点的问题.利用典型算例对该方法进行了验证,结果表明该方法的优化性能良好. 展开更多
关键词 鲁棒协同优化 nsga--ⅱ算法 多目标 学科间一致性
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Multi-objective capacity allocation optimization method of photovoltaic EV charging station considering V2G 被引量:9
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作者 ZHENG Xue-qin YAO Yi-ping 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第2期481-493,共13页
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed... Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency. 展开更多
关键词 vehicle to grid (V2G) capacity configuration optimization time-to-use (TOU) price multi-objective optimization NSGA- algorithm NSGA-SA algorithm
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Dual-resource integrated scheduling method of AGV and machine in intelligent manufacturing job shop 被引量:7
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作者 YUAN Ming-hai LI Ya-dong +1 位作者 PEI Feng-que GU Wen-bin 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第8期2423-2435,共13页
In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in inte... In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective. 展开更多
关键词 dual resource integrated scheduling improved A* algorithm improved NSGA- algorithm competition mechanism
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