In this paper, a new augmented Lagrangian function with 4-piecewise linear NCP function is introduced for solving nonlinear programming problems with equality constrained and inequality constrained. It is proved that ...In this paper, a new augmented Lagrangian function with 4-piecewise linear NCP function is introduced for solving nonlinear programming problems with equality constrained and inequality constrained. It is proved that a solution of the original constrained problem and corresponding values of Lagrange multipliers can be found by solving an unconstrained minimization of the augmented Lagrange function. Meanwhile, a new Lagrangian multiplier method corresponding with new augmented Lagrangian function is proposed. And this method is implementable and convergent.展开更多
This paper presents an efficient algorithm for globally solving a generalized linear fractional programming problem.For establishing this algorithm,we firstly construct a two-level linear relaxation method,and by util...This paper presents an efficient algorithm for globally solving a generalized linear fractional programming problem.For establishing this algorithm,we firstly construct a two-level linear relaxation method,and by utilizing the method,we can convert the initial generalized linear fractional programming problem and its subproblems into a series of linear programming relaxation problems.Based on the branch-and-bound framework and linear programming relaxation problems,a branch-and-bound algorithm is presented for globally solving the generalized linear fractional programming problem,and the computational complexity of the algorithm is given.Finally,numerical experimental results demonstrate the feasibility and efficiency of the proposed algorithm.展开更多
The Filled Function Method is a class of effective algorithms for continuous global optimization. In this paper, a new filled function method is introduced and used to solve integer programming. Firstly, some basic de...The Filled Function Method is a class of effective algorithms for continuous global optimization. In this paper, a new filled function method is introduced and used to solve integer programming. Firstly, some basic definitions of discrete optimization are given. Then an algorithm and the implementation of this algorithm on several test problems are showed. The computational results show the algorithm is effective.展开更多
In this paper,a new transformation function was proposed for finding global minimizer of discrete optimization problems.We proved that under some general assumptions the new transformation function possesses the prope...In this paper,a new transformation function was proposed for finding global minimizer of discrete optimization problems.We proved that under some general assumptions the new transformation function possesses the properties of both the tunneling functions and the filled functions.Only one parameter was included in the proposed function,and it can be adjusted easily in the realization.Numerical results demonstrate the effectiveness of the proposed method.展开更多
In this paper we present an infeasible-interior-point algorithm, based on a new wide neighbourhood N（ t1, t2, η）, for linear programming over symmetric cones. We treat the classical Newton direction as the sum of t...In this paper we present an infeasible-interior-point algorithm, based on a new wide neighbourhood N（ t1, t2, η）, for linear programming over symmetric cones. We treat the classical Newton direction as the sum of two other directions. We prove that if these two directions are equipped with different and appropriate step sizes, then the new algorithm has a polynomial convergence for the commutative class of search directions. In particular, the complexity bound is O（r1.5 log ε-1） for the Nesterov-Todd （NT） direction, and O（r2 log ε-1） for the xs and sx directions, where r is the rank of the associated Euclidean Jordan algebra and ε 〉 0 is the required precision. If starting with a feasible point （x0, y0, s0） in N（t1, t2, η）, the complexity bound is O（ √ r log ε-1） for the NT direction, and O（r log ε-1） for the xs and sx directions. When the NT search direction is used, we get the best complexity bound of wide neighborhood interior-point algorithm for linear programming over symmetric cones.展开更多
This paper presents a class of primal-dual path-following interior-point algorithms for symmetric cone programming(SCP)based on wide neighborhoods and new directions with a parameterθ.When the parameterθ=1,the direc...This paper presents a class of primal-dual path-following interior-point algorithms for symmetric cone programming(SCP)based on wide neighborhoods and new directions with a parameterθ.When the parameterθ=1,the direction is exactly the classical Newton direction.When the parameterθis independent of the rank of the associated Euclidean Jordan algebra,the algorithm terminates in at most O(κr logε−1)iterations,which coincides with the best known iteration bound for the classical wide neighborhood algorithms.When the parameterθ=√n/βτand Nesterov–Todd search direction is used,the algorithm has O(√r logε−1)iteration complexity,the best iteration complexity obtained so far by any interior-point method for solving SCP.To our knowledge,this is the first time that a class of interior-point algorithms including the classical wide neighborhood path-following algorithm is proposed and analyzed over symmetric cone.展开更多
In this paper,we present an infeasible-interior-point algorithm,based on a new wide neighborhood for symmetric cone programming.We treat the classical Newton direction as the sum of two other directions,and equip them...In this paper,we present an infeasible-interior-point algorithm,based on a new wide neighborhood for symmetric cone programming.We treat the classical Newton direction as the sum of two other directions,and equip them with different step sizes.We prove the complexity bound of the new algorithm for the Nesterov-Todd(NT)direction,and the xs and sx directions.The complexity bounds obtained here are the same as small neighborhood infeasible-interior-point algorithms over symmetric cones.展开更多
The Douglas–Peaceman–Rachford–Varga operator splitting methods are a class ofefficient methods for finding a zero of the sum of two maximal monotone operatorsin a real Hilbert space;however, they are sometimes diff...The Douglas–Peaceman–Rachford–Varga operator splitting methods are a class ofefficient methods for finding a zero of the sum of two maximal monotone operatorsin a real Hilbert space;however, they are sometimes difficult or even impossible tosolve the subproblems exactly. In this paper, we suggest an inexact version in whichsome relative error criterion is discussed. The corresponding convergence propertiesare established, and some preliminary numerical experiments are reported to illustrateits efficiency.展开更多
文摘In this paper, a new augmented Lagrangian function with 4-piecewise linear NCP function is introduced for solving nonlinear programming problems with equality constrained and inequality constrained. It is proved that a solution of the original constrained problem and corresponding values of Lagrange multipliers can be found by solving an unconstrained minimization of the augmented Lagrange function. Meanwhile, a new Lagrangian multiplier method corresponding with new augmented Lagrangian function is proposed. And this method is implementable and convergent.
基金the National Natural Science Foundation of China(Nos.11871196,12071133 and 12071112)the China Postdoctoral Science Foundation(No.2017M622340)+1 种基金the Key Scientific and Technological Research Projects of Henan Province(Nos.202102210147 and 192102210114)the Science and Technology Climbing Program of Henan Institute of Science and Technology(No.2018JY01).
文摘This paper presents an efficient algorithm for globally solving a generalized linear fractional programming problem.For establishing this algorithm,we firstly construct a two-level linear relaxation method,and by utilizing the method,we can convert the initial generalized linear fractional programming problem and its subproblems into a series of linear programming relaxation problems.Based on the branch-and-bound framework and linear programming relaxation problems,a branch-and-bound algorithm is presented for globally solving the generalized linear fractional programming problem,and the computational complexity of the algorithm is given.Finally,numerical experimental results demonstrate the feasibility and efficiency of the proposed algorithm.
基金Foundation item： the National Science Foundation of China（7A14178） the Science Fund of Shanghai University of Engineering Science for Young Scholars（2005Q23） the Natural Science Foundation of Education Commission of Shanghai （No.05NZ07）.
文摘The Filled Function Method is a class of effective algorithms for continuous global optimization. In this paper, a new filled function method is introduced and used to solve integer programming. Firstly, some basic definitions of discrete optimization are given. Then an algorithm and the implementation of this algorithm on several test problems are showed. The computational results show the algorithm is effective.
基金the National Natural Science Foundation of China(Nos.11471102 and 10971053).
文摘In this paper,a new transformation function was proposed for finding global minimizer of discrete optimization problems.We proved that under some general assumptions the new transformation function possesses the properties of both the tunneling functions and the filled functions.Only one parameter was included in the proposed function,and it can be adjusted easily in the realization.Numerical results demonstrate the effectiveness of the proposed method.
基金Supported by the National Natural Science Foundation of China(No.11471102)the Key Basic Research Foundation of the Higher Education Institutions of Henan Province(No.16A110012)
文摘In this paper we present an infeasible-interior-point algorithm, based on a new wide neighbourhood N（ t1, t2, η）, for linear programming over symmetric cones. We treat the classical Newton direction as the sum of two other directions. We prove that if these two directions are equipped with different and appropriate step sizes, then the new algorithm has a polynomial convergence for the commutative class of search directions. In particular, the complexity bound is O（r1.5 log ε-1） for the Nesterov-Todd （NT） direction, and O（r2 log ε-1） for the xs and sx directions, where r is the rank of the associated Euclidean Jordan algebra and ε 〉 0 is the required precision. If starting with a feasible point （x0, y0, s0） in N（t1, t2, η）, the complexity bound is O（ √ r log ε-1） for the NT direction, and O（r log ε-1） for the xs and sx directions. When the NT search direction is used, we get the best complexity bound of wide neighborhood interior-point algorithm for linear programming over symmetric cones.
基金the National Natural Science Foundation of China(No.11471102)the Key Basic Research Foundation of the Higher Education Institutions of Henan Province(No.16A110012)。
文摘This paper presents a class of primal-dual path-following interior-point algorithms for symmetric cone programming(SCP)based on wide neighborhoods and new directions with a parameterθ.When the parameterθ=1,the direction is exactly the classical Newton direction.When the parameterθis independent of the rank of the associated Euclidean Jordan algebra,the algorithm terminates in at most O(κr logε−1)iterations,which coincides with the best known iteration bound for the classical wide neighborhood algorithms.When the parameterθ=√n/βτand Nesterov–Todd search direction is used,the algorithm has O(√r logε−1)iteration complexity,the best iteration complexity obtained so far by any interior-point method for solving SCP.To our knowledge,this is the first time that a class of interior-point algorithms including the classical wide neighborhood path-following algorithm is proposed and analyzed over symmetric cone.
基金the National Natural Science Foundation of China(Nos.11471102,11426091,and 61179040)the Natural Science Foundation of Henan University of Science and Technology(No.2014QN039)Key Basic Research Foundation of the Higher Education Institutions of Henan Province(No.16A110012).
文摘In this paper,we present an infeasible-interior-point algorithm,based on a new wide neighborhood for symmetric cone programming.We treat the classical Newton direction as the sum of two other directions,and equip them with different step sizes.We prove the complexity bound of the new algorithm for the Nesterov-Todd(NT)direction,and the xs and sx directions.The complexity bounds obtained here are the same as small neighborhood infeasible-interior-point algorithms over symmetric cones.
基金This work was partially supported by the National Natural Science Foundations of China(Nos.11471102 and 11701150)the Key Basic Research Foundation of the Higher Education Institutions of Henan Province(No.16A110012).
文摘The Douglas–Peaceman–Rachford–Varga operator splitting methods are a class ofefficient methods for finding a zero of the sum of two maximal monotone operatorsin a real Hilbert space;however, they are sometimes difficult or even impossible tosolve the subproblems exactly. In this paper, we suggest an inexact version in whichsome relative error criterion is discussed. The corresponding convergence propertiesare established, and some preliminary numerical experiments are reported to illustrateits efficiency.
