Interval constraint propagation (ICP) algorithms allow to solve problems described as constraint satisfaction problems (CSP). ICP has been successfully applied to vehicle localization in the last few years. Once the l...Interval constraint propagation (ICP) algorithms allow to solve problems described as constraint satisfaction problems (CSP). ICP has been successfully applied to vehicle localization in the last few years. Once the localization problem has been stated, a large class of ICP solvers can be used. This paper compares a few ICP algorithms, using the same experimental data, in order to rank their performances in terms of accuracy and computing time.展开更多
The present paper aims to develop the Kuhn-Tucker and Fritz John criteria for saddle point optimality of interval-valued nonlinear programming problem.To achieve the study objective,we have proposed the definition of ...The present paper aims to develop the Kuhn-Tucker and Fritz John criteria for saddle point optimality of interval-valued nonlinear programming problem.To achieve the study objective,we have proposed the definition of minimizer and maximizer of an interval-valued non-linear programming problem.Also,we have introduced the interval-valued Fritz-John and Kuhn Tucker saddle point problems.After that,we have established both the necessary and sufficient optimality conditions of an interval-valued non-linear minimization problem.Next,we have shown that both the saddle point conditions(Fritz-John and Kuhn-Tucker)are sufficient without any convexity requirements.Then with the convexity requirements,we have established that these saddle point optimality criteria are the necessary conditions for optimality of an interval-valued non-linear programming with real-valued constraints.Here,all the results are derived with the help of interval order relations.Finally,we illustrate all the results with the help of a numerical example.展开更多
Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index ...Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index structures is that the dynamic operations of insertion and deletion can be operated on the new structure. The storage complexity of the tree is O(n), and the query I/O complexity is O(log n+t/B). To improve the performance of the inserting and deleting operations, some methods such as neighbored-constraint and update-late are applied. The I / O complexity of inserting and deleting operations is the same as that in B-tree, i.e., O(log n).展开更多
To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns...To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns. However, REILP lacks the capability to analyze the tradeoff between risks in the objective function and constraints. Therefore, a refined REILP model is proposed in this study to further enhance the decision support capability of the REILP approach for optimal watershed load reduction. By introducing a tradeofffactor （α） into the total risk function, the refined REILP can lead to different compromises between risks associated with the objective functions and the constraints. The proposed model was illustrated using a case study that deals with uncertainty- based optimal load reduction decision making for Lake Qionghai Watershed, China. A risk tradeoff curve with different values of a was presented to decision makers as a more flexible platform to support decision formulation. The results of the standard and refined REILP model were compared under 11 aspiration levels. The results demon- strate that, by applying the refined REILP, it is possible to obtain solutions that preserve the same constraint risk as that in the standard REILP but with lower objective risk, which can provide more effective guidance for decision makers.展开更多
随着风电接入电网的比例不断提高,风电的不确定性对电力系统的运行调度提出了严峻挑战。将满足一定置信水平的风电区间预测信息纳入到日前调度计划中有助于提高系统的安全性和经济性。为此提出了基于风电区间预测信息的随机安全约束机...随着风电接入电网的比例不断提高,风电的不确定性对电力系统的运行调度提出了严峻挑战。将满足一定置信水平的风电区间预测信息纳入到日前调度计划中有助于提高系统的安全性和经济性。为此提出了基于风电区间预测信息的随机安全约束机组组合模型(stochastic security-constrained unit commitment,SSCUC)。该模型将风电的不确定性用1个确定的预测风电场景和2个极限风电场景来表示,简化了问题的复杂度。同时,该模型引入了潮流约束和网络安全约束,保证了调度结果的可行性。为求解该模型,提出了基于广义Benders分解的计算方法。该方法将SSCUC问题分解为一个主问题和2T(T为调度周期)个约束潮流子问题,并通过交替迭代的方式获得原问题的最优解。4机9节点系统和改进118节点系统的计算结果验证了所提模型和算法的有效性。展开更多
文摘Interval constraint propagation (ICP) algorithms allow to solve problems described as constraint satisfaction problems (CSP). ICP has been successfully applied to vehicle localization in the last few years. Once the localization problem has been stated, a large class of ICP solvers can be used. This paper compares a few ICP algorithms, using the same experimental data, in order to rank their performances in terms of accuracy and computing time.
基金Taif University Researchers Supporting Project number(TURSP-2020/20),Taif University,Taif,Saudi Arabia。
文摘The present paper aims to develop the Kuhn-Tucker and Fritz John criteria for saddle point optimality of interval-valued nonlinear programming problem.To achieve the study objective,we have proposed the definition of minimizer and maximizer of an interval-valued non-linear programming problem.Also,we have introduced the interval-valued Fritz-John and Kuhn Tucker saddle point problems.After that,we have established both the necessary and sufficient optimality conditions of an interval-valued non-linear minimization problem.Next,we have shown that both the saddle point conditions(Fritz-John and Kuhn-Tucker)are sufficient without any convexity requirements.Then with the convexity requirements,we have established that these saddle point optimality criteria are the necessary conditions for optimality of an interval-valued non-linear programming with real-valued constraints.Here,all the results are derived with the help of interval order relations.Finally,we illustrate all the results with the help of a numerical example.
基金Supported by the National Natural Science Foundation of China under grant !Nos.69933010 and69773012.
文摘Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index structures is that the dynamic operations of insertion and deletion can be operated on the new structure. The storage complexity of the tree is O(n), and the query I/O complexity is O(log n+t/B). To improve the performance of the inserting and deleting operations, some methods such as neighbored-constraint and update-late are applied. The I / O complexity of inserting and deleting operations is the same as that in B-tree, i.e., O(log n).
基金This paper was supported by the National Natural Science Foundation of China （Grant No. 41222002）, Research Fund for the Doctoral Program of Higher Education of China （20100001120020） and ＂China National Water Pollution Control Program＂ （2013ZX07102-006）. Special thanks to Dr. Daniel Obenour in University of Michigan.
文摘To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns. However, REILP lacks the capability to analyze the tradeoff between risks in the objective function and constraints. Therefore, a refined REILP model is proposed in this study to further enhance the decision support capability of the REILP approach for optimal watershed load reduction. By introducing a tradeofffactor （α） into the total risk function, the refined REILP can lead to different compromises between risks associated with the objective functions and the constraints. The proposed model was illustrated using a case study that deals with uncertainty- based optimal load reduction decision making for Lake Qionghai Watershed, China. A risk tradeoff curve with different values of a was presented to decision makers as a more flexible platform to support decision formulation. The results of the standard and refined REILP model were compared under 11 aspiration levels. The results demon- strate that, by applying the refined REILP, it is possible to obtain solutions that preserve the same constraint risk as that in the standard REILP but with lower objective risk, which can provide more effective guidance for decision makers.
文摘随着风电接入电网的比例不断提高,风电的不确定性对电力系统的运行调度提出了严峻挑战。将满足一定置信水平的风电区间预测信息纳入到日前调度计划中有助于提高系统的安全性和经济性。为此提出了基于风电区间预测信息的随机安全约束机组组合模型(stochastic security-constrained unit commitment,SSCUC)。该模型将风电的不确定性用1个确定的预测风电场景和2个极限风电场景来表示,简化了问题的复杂度。同时,该模型引入了潮流约束和网络安全约束,保证了调度结果的可行性。为求解该模型,提出了基于广义Benders分解的计算方法。该方法将SSCUC问题分解为一个主问题和2T(T为调度周期)个约束潮流子问题,并通过交替迭代的方式获得原问题的最优解。4机9节点系统和改进118节点系统的计算结果验证了所提模型和算法的有效性。
