The DFP method is one of the most famous numerical algorithms for unconstrained optimization. For uniformly convex objective functions convergence properties of the DFP method are studied. Several conditions that can ...The DFP method is one of the most famous numerical algorithms for unconstrained optimization. For uniformly convex objective functions convergence properties of the DFP method are studied. Several conditions that can ensure the global convergence of the DFP method are given.展开更多
This paper presents a unified bination algorithms （such as FrankWolfe problems. Global convergence results are framework of the nonmonotone convex comAlgorithm） for solving the traffic assignment established under m...This paper presents a unified bination algorithms （such as FrankWolfe problems. Global convergence results are framework of the nonmonotone convex comAlgorithm） for solving the traffic assignment established under mild conditions. The line search procedure used in our algorithm includes the nonmonotone Armijo rule, the non- monotone Goldstein rule and the nonmonotone Wolfe rule as special cases. So, the new algorithm can be viewed as a generalization of the regular convex combination algorithm.展开更多
基金the project "large-scale scientific computing" of State Commission of Science and Technology, China
文摘The DFP method is one of the most famous numerical algorithms for unconstrained optimization. For uniformly convex objective functions convergence properties of the DFP method are studied. Several conditions that can ensure the global convergence of the DFP method are given.
基金This research is partly supported by National Outstanding Young Investigator Grant(70225005) of National Natural Science Foundation of China and the Project(70471088) of National Natural Science Foundation of China.
文摘This paper presents a unified bination algorithms （such as FrankWolfe problems. Global convergence results are framework of the nonmonotone convex comAlgorithm） for solving the traffic assignment established under mild conditions. The line search procedure used in our algorithm includes the nonmonotone Armijo rule, the non- monotone Goldstein rule and the nonmonotone Wolfe rule as special cases. So, the new algorithm can be viewed as a generalization of the regular convex combination algorithm.
