Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an ...Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an interval-parameter fuzzy robust nonlinear programming (IFRNP) model was developed for water quality management to deal with such difficulties. The developed model incorporated interval nonlinear programming (INP) and fuzzy robust programming (FRP) methods within a general optimization framework. The developed IFRNP model not only could explicitly deal with uncertainties represented as discrete interval numbers and fuzzy membership functions, but also was able to deal with nonlinearities in the objective function.展开更多
【目的】基于虚拟电厂(virtual power plant,VPP)技术聚合区域电网内部分布式资源,能以低边际成本有效提高系统灵活性。然而,信息安全等因素导致的数据壁垒,以及分布式协调计算效率和调控资源的不确定性等问题给虚拟电厂辅助服务决策带...【目的】基于虚拟电厂(virtual power plant,VPP)技术聚合区域电网内部分布式资源,能以低边际成本有效提高系统灵活性。然而,信息安全等因素导致的数据壁垒,以及分布式协调计算效率和调控资源的不确定性等问题给虚拟电厂辅助服务决策带来困难。据此,分析VPP整体对外特性,包括关口功率、备用能力及运行成本,提出了一种VPP鲁棒调度特性可信量化方法,并构建多VPP博弈的协同调度模型。【方法】首先,考虑分布式电源和需求响应不确定因素影响,解析网络约束下的源荷备用潜力,从而建立VPP数学模型;其次,结合鲁棒优化和多参数规划理论,实现VPP关口功率调节空间、弹性备用能力和最优成本鲁棒可行域可信量化,建立VPP内部资源调控策略与对外交易结果的仿射关系,完成VPP等值聚合;进一步,构建了多VPP与主网有效互动的合作博弈模型;最后,通过3个测试算例验证了本文模型和方法的有效性。【结果】所量化的封装模型参与调度具有更高的计算效率,且保护了VPP内部信息隐私性。通过设计并行程序,封装模型量化过程计算效率得到了进一步提升。【结论】所提方法能有效支撑多重VPP主体协同大电网进行能量和辅助服务的交易,加强主网安全防御体系建设。展开更多
Design of a robust production facility layout with minimum handling cost （MHC） presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly...Design of a robust production facility layout with minimum handling cost （MHC） presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly change in each planning period. The objective of the design is to find the robust facility layout with minimum total material handling cost over the entire multiperiod planning horizon. This paper proposes a new mathematical model for designing robust machine layout in the stochastic dynamic environment of manufacturing systems using quadratic assignment problem （QAP） formulation. In this investigation, product demands are assumed to be normally distributed random variables with known expected value, variance, and covariance that randomly change from period to period. The proposed model was verified and validated using randomly generated numerical data and benchmark examples. The effect of dependent product demands and varying interest rate on the total cost function of the proposed model has also been investigated. Sensitivity analysis on the proposed model has been performed. Dynamic programming and simulated annealing optimization algorithms were used in solving the modeled example problems.展开更多
This paper employs a new second-order cone (SOC) model as the uncertainty set to capture non-Gaussian local variations. Then using robust gate sizing as an example, we describe the detailed procedures of robust design...This paper employs a new second-order cone (SOC) model as the uncertainty set to capture non-Gaussian local variations. Then using robust gate sizing as an example, we describe the detailed procedures of robust design with a budget of uncertainty. For a pre-selected probability level of yield protection, this robust method translates uncertainty budgeting problems into regular robust optimization problems. More importantly, under the assumption of non-Gaussian distributions, we show that within-die variations will lead to varying sizes of uncertainty sets at different nominal values. By using this new model of uncertainty estimation, the robust gate sizing problem can be formulated as a Geometric Program (GP) and therefore efficiently solved.展开更多
In this paper, the problem of program performance scheduling with accepting strategy is studied. Considering the uncertainty of actual situation, the duration of a program is expressed as a bounded interval. Firstly, ...In this paper, the problem of program performance scheduling with accepting strategy is studied. Considering the uncertainty of actual situation, the duration of a program is expressed as a bounded interval. Firstly, we decide which programs are accepted. Secondly, the risk preference coefficient of the decision maker is introduced. Thirdly, the min-max robust optimization model of the uncertain program show scheduling is built to minimize the performance cost and determine the sequence of these programs. Based on the above model, an effective algorithm for the original problem is proposed. The computational experiment shows that the performance’s cost (revenue) will increase (decrease) with decision maker’s risk aversion.展开更多
“双碳”目标的提出促进了绿色生产与低碳发展相结合的需求。围绕着商业园区的能量共享与低碳运行这一问题,提出了一种充电站、商业楼宇、光储电站的电-碳交易模型,研究了园区主体与电力交易中心、微网运营商、碳交易中心之间能量和信...“双碳”目标的提出促进了绿色生产与低碳发展相结合的需求。围绕着商业园区的能量共享与低碳运行这一问题,提出了一种充电站、商业楼宇、光储电站的电-碳交易模型,研究了园区主体与电力交易中心、微网运营商、碳交易中心之间能量和信息流动关系。在模型求解上,运用分布式鲁棒优化将商业园区电-碳分布式调度模型的非凸的机会约束问题转化为半正定规划问题。通过设定的3种方案从运营成本、碳排放量2个方面验证了所提方法在降成本、降碳排方面的有效性。最后,将所提方法与基于条件风险价值(conditional value at risk,CVaR)模型的线性规划方法对比,结果表明分布式鲁棒在决策结果方面更符合实际调度情况。展开更多
文摘Planning for water quality management is important for facilitating sustainable socio-economic development;however, the planning is also complicated by a variety of uncertainties and nonlinearities. In this study, an interval-parameter fuzzy robust nonlinear programming (IFRNP) model was developed for water quality management to deal with such difficulties. The developed model incorporated interval nonlinear programming (INP) and fuzzy robust programming (FRP) methods within a general optimization framework. The developed IFRNP model not only could explicitly deal with uncertainties represented as discrete interval numbers and fuzzy membership functions, but also was able to deal with nonlinearities in the objective function.
文摘【目的】基于虚拟电厂(virtual power plant,VPP)技术聚合区域电网内部分布式资源,能以低边际成本有效提高系统灵活性。然而,信息安全等因素导致的数据壁垒,以及分布式协调计算效率和调控资源的不确定性等问题给虚拟电厂辅助服务决策带来困难。据此,分析VPP整体对外特性,包括关口功率、备用能力及运行成本,提出了一种VPP鲁棒调度特性可信量化方法,并构建多VPP博弈的协同调度模型。【方法】首先,考虑分布式电源和需求响应不确定因素影响,解析网络约束下的源荷备用潜力,从而建立VPP数学模型;其次,结合鲁棒优化和多参数规划理论,实现VPP关口功率调节空间、弹性备用能力和最优成本鲁棒可行域可信量化,建立VPP内部资源调控策略与对外交易结果的仿射关系,完成VPP等值聚合;进一步,构建了多VPP与主网有效互动的合作博弈模型;最后,通过3个测试算例验证了本文模型和方法的有效性。【结果】所量化的封装模型参与调度具有更高的计算效率,且保护了VPP内部信息隐私性。通过设计并行程序,封装模型量化过程计算效率得到了进一步提升。【结论】所提方法能有效支撑多重VPP主体协同大电网进行能量和辅助服务的交易,加强主网安全防御体系建设。
基金Supported by the Ministry of Higher Education of Malaysia through the Foundation Research(Grant Scheme no.FRGS/1/2012/TK01/MMU/02/2)
文摘Design of a robust production facility layout with minimum handling cost （MHC） presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly change in each planning period. The objective of the design is to find the robust facility layout with minimum total material handling cost over the entire multiperiod planning horizon. This paper proposes a new mathematical model for designing robust machine layout in the stochastic dynamic environment of manufacturing systems using quadratic assignment problem （QAP） formulation. In this investigation, product demands are assumed to be normally distributed random variables with known expected value, variance, and covariance that randomly change from period to period. The proposed model was verified and validated using randomly generated numerical data and benchmark examples. The effect of dependent product demands and varying interest rate on the total cost function of the proposed model has also been investigated. Sensitivity analysis on the proposed model has been performed. Dynamic programming and simulated annealing optimization algorithms were used in solving the modeled example problems.
文摘This paper employs a new second-order cone (SOC) model as the uncertainty set to capture non-Gaussian local variations. Then using robust gate sizing as an example, we describe the detailed procedures of robust design with a budget of uncertainty. For a pre-selected probability level of yield protection, this robust method translates uncertainty budgeting problems into regular robust optimization problems. More importantly, under the assumption of non-Gaussian distributions, we show that within-die variations will lead to varying sizes of uncertainty sets at different nominal values. By using this new model of uncertainty estimation, the robust gate sizing problem can be formulated as a Geometric Program (GP) and therefore efficiently solved.
文摘In this paper, the problem of program performance scheduling with accepting strategy is studied. Considering the uncertainty of actual situation, the duration of a program is expressed as a bounded interval. Firstly, we decide which programs are accepted. Secondly, the risk preference coefficient of the decision maker is introduced. Thirdly, the min-max robust optimization model of the uncertain program show scheduling is built to minimize the performance cost and determine the sequence of these programs. Based on the above model, an effective algorithm for the original problem is proposed. The computational experiment shows that the performance’s cost (revenue) will increase (decrease) with decision maker’s risk aversion.
文摘“双碳”目标的提出促进了绿色生产与低碳发展相结合的需求。围绕着商业园区的能量共享与低碳运行这一问题,提出了一种充电站、商业楼宇、光储电站的电-碳交易模型,研究了园区主体与电力交易中心、微网运营商、碳交易中心之间能量和信息流动关系。在模型求解上,运用分布式鲁棒优化将商业园区电-碳分布式调度模型的非凸的机会约束问题转化为半正定规划问题。通过设定的3种方案从运营成本、碳排放量2个方面验证了所提方法在降成本、降碳排方面的有效性。最后,将所提方法与基于条件风险价值(conditional value at risk,CVaR)模型的线性规划方法对比,结果表明分布式鲁棒在决策结果方面更符合实际调度情况。
