In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilizatio...Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilization of agricultural production and waste water resources.The results demonstrated that the difference of crop energy capture mainly depended on the development stage.Waste water with a certain concentration was able to promote crop growth,while excessive concentration inhibited crop growth.The correlation between water absorption rate and leaf area index was close(R=0.9498,p<0.01).The amount of bad seeds increased at a speed of 34.7·d^-1,when system irrigated randomly in the seedling stage,while it tended to remain stable at a speed of 0.3·d^-1 after plants entering the mature stage which impacted the total yields of crops.展开更多
This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations amo...This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.展开更多
为提高微电网应对新能源出力和负荷不确定性的能力,提出1种考虑灵活性资源的微电网优化控制策略。根据各类灵活性资源的源储荷特性进行分类,建立微电网双层优化调度模型。用户层引入用户侧灵活性资源,以用户费用和净负荷差值最小为优化...为提高微电网应对新能源出力和负荷不确定性的能力,提出1种考虑灵活性资源的微电网优化控制策略。根据各类灵活性资源的源储荷特性进行分类,建立微电网双层优化调度模型。用户层引入用户侧灵活性资源,以用户费用和净负荷差值最小为优化目标,决策变量为电动汽车和可平移负荷出力功率。源储层模型加入储能侧与发电侧灵活性资源,以微电网运营商成本和失负荷率最小为优化目标,决策变量为燃气轮机、主网联络线和储能单元出力功率。使用场景缩减的季节典型日数据进行算例仿真,采用改进后的基于分解的多目标进化MOEA/D(multi-objective evolutionary algorithm based on decomposition)算法对双层优化调度模型进行求解,年均用户费用降低6.85%,运营商年均总成本下降14.68%,年均失负荷率下降6.65%,验证了本文所提模型的合理性和有效性。展开更多
为研究考虑施工安全及心理资本的建筑工人资源调度问题,构建建筑工人项目成本最低、完工时间最短、安全绩效最高的多目标资源调度模型,基于多策略改进灰狼优化算法,改善基本灰狼优化算法存在的局部最优而早熟收敛、全局搜索能力差的问题...为研究考虑施工安全及心理资本的建筑工人资源调度问题,构建建筑工人项目成本最低、完工时间最短、安全绩效最高的多目标资源调度模型,基于多策略改进灰狼优化算法,改善基本灰狼优化算法存在的局部最优而早熟收敛、全局搜索能力差的问题,提高算法的全局寻优能力和求解精度,得到建筑工人资源配置方案。结果表明,与传统灰狼优化(Grey Wolf Optimization,GWO)算法和其他两种改进灰狼算法相比,多策略混合灰狼优化算法在模型求解精度方面更优秀,给出的建筑工人资源配置方案更高效安全。展开更多
针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。...针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。首先,建立日前鲁棒调度模型,充分挖掘火电机组、抽水蓄能等资源的灵活调节潜力,将火电灵活改造及抽水蓄能抽发状态作为模型的第一阶段决策变量,各灵活资源的出力作为第二阶段决策变量,并以灵活改造成本、碳排放成本及运行成本最小为优化目标。其次,在模型求解中,将所建立的两阶段鲁棒模型转化为相对独立的主问题和子问题,并采用列与约束生成(column and constraint generation,C&CG)算法和强对偶理论反复迭代,以逼近最优解。最后,通过算例验证,所提出的优化调度策略在满足灵活性需求的基础上,统筹各类资源,实现了系统中经济性、环保性、灵活性的均衡,并增强了对源荷不确定性风险的抵御能力。展开更多
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金Supported by the Science and Technology Research Project of the Ministry of Education(14YJCZH017)the Major State Basic Research Development Program of China(973 Program)(2017YFC0404503)+1 种基金Key Cultivation Project of Lingnan Normal University in 2019(LZ1903)Lingnan Normal University Special Talent Program(ZL2007)
文摘Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilization of agricultural production and waste water resources.The results demonstrated that the difference of crop energy capture mainly depended on the development stage.Waste water with a certain concentration was able to promote crop growth,while excessive concentration inhibited crop growth.The correlation between water absorption rate and leaf area index was close(R=0.9498,p<0.01).The amount of bad seeds increased at a speed of 34.7·d^-1,when system irrigated randomly in the seedling stage,while it tended to remain stable at a speed of 0.3·d^-1 after plants entering the mature stage which impacted the total yields of crops.
基金supported by the National Natural Science Foundation of China(7120116671201170)
文摘This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.
文摘为提高微电网应对新能源出力和负荷不确定性的能力,提出1种考虑灵活性资源的微电网优化控制策略。根据各类灵活性资源的源储荷特性进行分类,建立微电网双层优化调度模型。用户层引入用户侧灵活性资源,以用户费用和净负荷差值最小为优化目标,决策变量为电动汽车和可平移负荷出力功率。源储层模型加入储能侧与发电侧灵活性资源,以微电网运营商成本和失负荷率最小为优化目标,决策变量为燃气轮机、主网联络线和储能单元出力功率。使用场景缩减的季节典型日数据进行算例仿真,采用改进后的基于分解的多目标进化MOEA/D(multi-objective evolutionary algorithm based on decomposition)算法对双层优化调度模型进行求解,年均用户费用降低6.85%,运营商年均总成本下降14.68%,年均失负荷率下降6.65%,验证了本文所提模型的合理性和有效性。
文摘为研究考虑施工安全及心理资本的建筑工人资源调度问题,构建建筑工人项目成本最低、完工时间最短、安全绩效最高的多目标资源调度模型,基于多策略改进灰狼优化算法,改善基本灰狼优化算法存在的局部最优而早熟收敛、全局搜索能力差的问题,提高算法的全局寻优能力和求解精度,得到建筑工人资源配置方案。结果表明,与传统灰狼优化(Grey Wolf Optimization,GWO)算法和其他两种改进灰狼算法相比,多策略混合灰狼优化算法在模型求解精度方面更优秀,给出的建筑工人资源配置方案更高效安全。
文摘针对新能源电力系统中源荷不确定性导致的系统调度灵活性严重不足问题,文中提出了一种考虑源荷不确定性的电力系统两阶段鲁棒优化模型。根据源荷不确定性特征,结合K-means法和鲁棒优化理论,在多时间尺度对电力系统灵活性需求进行量化。首先,建立日前鲁棒调度模型,充分挖掘火电机组、抽水蓄能等资源的灵活调节潜力,将火电灵活改造及抽水蓄能抽发状态作为模型的第一阶段决策变量,各灵活资源的出力作为第二阶段决策变量,并以灵活改造成本、碳排放成本及运行成本最小为优化目标。其次,在模型求解中,将所建立的两阶段鲁棒模型转化为相对独立的主问题和子问题,并采用列与约束生成(column and constraint generation,C&CG)算法和强对偶理论反复迭代,以逼近最优解。最后,通过算例验证,所提出的优化调度策略在满足灵活性需求的基础上,统筹各类资源,实现了系统中经济性、环保性、灵活性的均衡,并增强了对源荷不确定性风险的抵御能力。
