Two constraint violation stabilization methods are presented to solve the Euler Lagrange equations of motion of a multibody system with nonholonomic constraints. Compared to the previous works, the newly devised metho...Two constraint violation stabilization methods are presented to solve the Euler Lagrange equations of motion of a multibody system with nonholonomic constraints. Compared to the previous works, the newly devised methods can deal with more complicated problems such as those with nonholonomic constraints or redundant constraints, and save the computation time. Finally a numerical simulation of a multibody system is conducted by using the methods given in this paper.展开更多
Linear programming is a method for solving linear optimization problems with constraints, widely met in real-world applications. In the vast majority of these applications, the number of constraints is significantly l...Linear programming is a method for solving linear optimization problems with constraints, widely met in real-world applications. In the vast majority of these applications, the number of constraints is significantly larger than the number of variables. Since the crucial subject of these problems is to detect the constraints that will be verified as equality in an optimal solution, there are methods for investigating such constraints to accelerate the whole process. In this paper, a technique named proximity technique is addressed, which under a proposed theoretical framework gives an ascending order to the constraints in such a way that those with low ranking are characterized of high priority to be binding. Under this framework, two new Linear programming optimization algorithms are introduced, based on a proposed Utility matrix and a utility vector accordingly. For testing the addressed algorithms firstly a generator of 10,000 random linear programming problems of dimension n with m constraints, where , is introduced in order to simulate as many as possible real-world problems, and secondly, real-life linear programming examples from the NETLIB repository are tested. A discussion of the numerical results is given. Furthermore, already known methods for solving linear programming problems are suggested to be fitted under the proposed framework.展开更多
The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimiz...The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimization model for multibody system dynamics with multi-point contact and collision is established.The paper presents the study of the numerical solution scheme,in which particle swarm optimization method is used to deal with the corresponding optimization model.The article also presents the comparison of the Gauss optimization method(GOM)and the hybrid linear complementarity method(i.e.combining differential algebraic equations(DAEs)and linear complementarity problems(LCP)),commonly used to solve the dynamic contact problem of multibody systems with bilateral constraints.The results illustrate that,the GOM has the same advantage of dynamical modelling with LCP and when the redundant constraint exists,the GOM always has a unique solution and so no additional processing is needed,whereas the corresponding DAE-LCP method may have singular cases with multiple solutions or no solutions.Using numerical examples,the GOM is verified to effectively solve the dynamics of multibody systems with redundant unilateral and bilateral constraints without additional redundancy processing.The GOM can also be applied to the optimal control of systems in the future and combined with the parameter optimization of systems to handle dynamic problems.The work given provides the dynamics and control of the complex system with a new train of thought and method.展开更多
With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangemen...With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment(SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in largescale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then,an efficient redundant constraint identification(RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.展开更多
It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulat...It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulations are fed to a commercial solver. In addition, even if dimensions are kept the same, changes in formulations may largely influence solvability and quality of results. This becomes evident especially if redundant constraints are used. We propose a related framework for information collection based on these constraints. We exemplify by means of a well-known combinatorial optimization problem from the knapsack problem family, i.e., the multidimensional multiple-choice knapsack problem （MMKP）. This incorporates a relationship of the MMKP to some generalized set partitioning problems. Moreover, we investigate an application in maritime shipping and logistics by means of the dynamic berth allocation problem （DBAP）, where optimal solutions are reached from the root node within the solver.展开更多
In this paper, we introduce the concepts of redundant constraint and exceptional vertex which play an important role in the characterization of universal minimal total dominating functions (universal MTDFs), and estab...In this paper, we introduce the concepts of redundant constraint and exceptional vertex which play an important role in the characterization of universal minimal total dominating functions (universal MTDFs), and establish some further results on universal MTDFs in general graphs. By extending these results to trees, we get a necessary and sufficient condition for universal MTDFs and show that there is a good algorithm for deciding whether a given tree has a universal MTDF.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 19902006).
文摘Two constraint violation stabilization methods are presented to solve the Euler Lagrange equations of motion of a multibody system with nonholonomic constraints. Compared to the previous works, the newly devised methods can deal with more complicated problems such as those with nonholonomic constraints or redundant constraints, and save the computation time. Finally a numerical simulation of a multibody system is conducted by using the methods given in this paper.
文摘Linear programming is a method for solving linear optimization problems with constraints, widely met in real-world applications. In the vast majority of these applications, the number of constraints is significantly larger than the number of variables. Since the crucial subject of these problems is to detect the constraints that will be verified as equality in an optimal solution, there are methods for investigating such constraints to accelerate the whole process. In this paper, a technique named proximity technique is addressed, which under a proposed theoretical framework gives an ascending order to the constraints in such a way that those with low ranking are characterized of high priority to be binding. Under this framework, two new Linear programming optimization algorithms are introduced, based on a proposed Utility matrix and a utility vector accordingly. For testing the addressed algorithms firstly a generator of 10,000 random linear programming problems of dimension n with m constraints, where , is introduced in order to simulate as many as possible real-world problems, and secondly, real-life linear programming examples from the NETLIB repository are tested. A discussion of the numerical results is given. Furthermore, already known methods for solving linear programming problems are suggested to be fitted under the proposed framework.
基金This study was funded by the National Natural Science Foundation of China(Grant 11272167).
文摘The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimization model for multibody system dynamics with multi-point contact and collision is established.The paper presents the study of the numerical solution scheme,in which particle swarm optimization method is used to deal with the corresponding optimization model.The article also presents the comparison of the Gauss optimization method(GOM)and the hybrid linear complementarity method(i.e.combining differential algebraic equations(DAEs)and linear complementarity problems(LCP)),commonly used to solve the dynamic contact problem of multibody systems with bilateral constraints.The results illustrate that,the GOM has the same advantage of dynamical modelling with LCP and when the redundant constraint exists,the GOM always has a unique solution and so no additional processing is needed,whereas the corresponding DAE-LCP method may have singular cases with multiple solutions or no solutions.Using numerical examples,the GOM is verified to effectively solve the dynamics of multibody systems with redundant unilateral and bilateral constraints without additional redundancy processing.The GOM can also be applied to the optimal control of systems in the future and combined with the parameter optimization of systems to handle dynamic problems.The work given provides the dynamics and control of the complex system with a new train of thought and method.
基金supported by the National Key R&D Program of China (No.2017YFB0902200)。
文摘With the increase in the penetration rate of renewable energy, the planning and operation of power systems will face huge challenges. To ensure the sufficient utilization of renewable energy, the reasonable arrangement for the long-term power generation plan has become more crucial. Security-constrained unit commitment(SCUC) is a critical technical means to optimize the long-term power generation plan. However, the plentiful power sources and the complex grid structure in largescale power systems will bring great difficulties to long-term SCUC. In this paper, we propose a fast calculation method for long-term SCUC of large-scale power systems with renewable energy. First, a method for unit status reduction based on temporal decomposition is proposed, which will reduce plenty of binary variables and intertemporal constraints in SCUC. Then,an efficient redundant constraint identification(RCI) method is developed to reduce the number of network constraints. Furthermore, a joint accelerated calculation framework for status reduction and RCI is formed, which can reduce the complexity of long-term SCUC while ensuring a high-precision feasible solution. In case studies, numerical results based on two test systems ROTS2017 and NREL-118 are analyzed, which verify the effectiveness and scalability of the proposed calculation method.
文摘It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulations are fed to a commercial solver. In addition, even if dimensions are kept the same, changes in formulations may largely influence solvability and quality of results. This becomes evident especially if redundant constraints are used. We propose a related framework for information collection based on these constraints. We exemplify by means of a well-known combinatorial optimization problem from the knapsack problem family, i.e., the multidimensional multiple-choice knapsack problem （MMKP）. This incorporates a relationship of the MMKP to some generalized set partitioning problems. Moreover, we investigate an application in maritime shipping and logistics by means of the dynamic berth allocation problem （DBAP）, where optimal solutions are reached from the root node within the solver.
文摘In this paper, we introduce the concepts of redundant constraint and exceptional vertex which play an important role in the characterization of universal minimal total dominating functions (universal MTDFs), and establish some further results on universal MTDFs in general graphs. By extending these results to trees, we get a necessary and sufficient condition for universal MTDFs and show that there is a good algorithm for deciding whether a given tree has a universal MTDF.
