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Solving a Class of Nonlinear Programming Problems via a Homotopy Continuation Method 被引量:1
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作者 苏孟龙 吕显瑞 《Northeastern Mathematical Journal》 CSCD 2008年第3期265-274,共10页
In this paper we present a homotopy continuation method for finding the Karush-Kuhn-Tucker point of a class of nonlinear non-convex programming problems. Two numerical examples are given to show that this method is ef... In this paper we present a homotopy continuation method for finding the Karush-Kuhn-Tucker point of a class of nonlinear non-convex programming problems. Two numerical examples are given to show that this method is effective. It should be pointed out that we extend the results of Lin et al. (see Appl. Math. Comput., 80(1996), 209-224) to a broader class of non-convex programming problems. 展开更多
关键词 homotopy continuation method Karush-Kuhn-Tucker point non-convex programming problem
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Finding Symbolic and All Numerical Solutions for Design Optimization Based on Monotonicity Analysis and Solving Polynomial Systems 被引量:1
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作者 Chen Yong Li Bailin School of Mechanical Engineering , Southwest Jiaotong University, Chengdu 610031, China 《Journal of Modern Transportation》 1996年第1期16-23,共8页
A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equ... A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equivalent to the subproblem of the design optimization is taken as the symbolic (analytical) expression of the optimum solution for the symbolic optimization, i.e. the problem with symbolic coefficients. A method based on substituting and eliminating for determining Groebner Bases is also proposed, and method for finding all numerical optimum solutions is discussed. Finally an example is given, demonstrating the strategy and efficiency of the method. 展开更多
关键词 design optimization symbolic optimum solution monotonicity analysis Groebner Bases homotopy continuation method
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Efficiently Counting Affine Roots of Mixed Trigonometric Polynomial Systems
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作者 JIAO Libin DONG Bo YU Bo 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2017年第4期967-982,共16页
Estimating the number of isolated roots of a polynomial system is not only a fundamental study theme in algebraic geometry but also an important subproblem of homotopy methods for solving polynomial systems. For the m... Estimating the number of isolated roots of a polynomial system is not only a fundamental study theme in algebraic geometry but also an important subproblem of homotopy methods for solving polynomial systems. For the mixed trigonometric polynomial systems, which are more general than polynomial systems and rather frequently occur in many applications, the classical B6zout number and the multihomogeneous Bezout number are the best known upper bounds on the number of isolated roots. However, for the deficient mixed trigonometric polynomial systems, these two upper bounds are far greater than the actual number of isolated roots. The BKK bound is known as the most accurate upper bound on the number of isolated roots of a polynomial system. However, the extension of the definition of the BKK bound allowing it to treat mixed trigonometric polynomial systems is very difficult due to the existence of sine and cosine functions. In this paper, two new upper bounds on the number of isolated roots of a mixed trigonometric polynomial system are defined and the corresponding efficient algorithms for calculating them are presented. Numerical tests are also given to show the accuracy of these two definitions, and numerically prove they can provide tighter upper bounds on the number of isolated roots of a mixed trigonometric polynomial system than the existing upper bounds, and also the authors compare the computational time for calculating these two upper bounds. 展开更多
关键词 BKK bound homotopy continuation method mixed trigonometric polynomial system mixed volume polynomial system upper bound.
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