The complexity of linear programming is discussed in the "integer" and "real number" models of computation. Even though the integer model is widely used in theoretical computer science, the real number model is more useful for estimating an algorithm's running time in actual computation. Although...
摘要原文 The complexity of linear programming is discussed in the “integer” and “real number” models of computation. Even though the integer model is widely used in theoretical computer science, the real number model is more useful for estimating an algorithm's running time in actual computati...
formulation of the underlying norm complexity result in Section 2, we present NP-hardness results for checking properties of interval matrices (Section 3), computing enclosures (Section 4), solvability of rectangular linear interval systems (Section 5), and linear and quadratic programming (Section 6...
This book describes the rapidly developing field of interior point methods (IPMs). An extensive analysis is given of path-following methods for linear programming, quadratic programming and convex programming. These methods, which form a subclass of interior point methods, follow the central path, wh...
The speed is at least an order of magnitude faster than GLPK in small-dimensional LP (<10) with a large constraints number (>100). This solver is adapted from the linear-fractional programming (LFP) from Mike Hohmeyer at UC Berkeley based on Raimund Seidel's algorithm. Kernel functions are...
Recently much effort has been devoted to determining the computational complexity for a variety of integer programming problems. In this paper a general integer programming problem is shown to be NP-complete; the proof given for this result uses only elementary linear algebra. Complexity results are...
The size of the complete set of unifiers is exponential, but membership in that set can be determined in polynomial time. For any goal (not just varity 1) we give a NEXPTIME algorithm. 展开 会议名称: Logic for programming, artificial intelligence, and reasoning: 8th international conference, ...
Interestingly, several constants that appear when developing complexity results hide the dimensions of the problem. This work organizes several results in literature about bounds that appear in derivative-free trust-region algorithms based on linear and quadratic models. All the constants are given ...
We also prove that the approximate solution of linear two-stage stochastic programs with random recourse is strongly #P-hard.doi:10.18452/8446Grani A. HanasusantoDaniel KuhnWolfram WiesemannSpringer Berlin HeidelbergMathematical ProgrammingHanasusanto, G. A., Kuhn, D., and Wiesemann, W. (2016). ...
4d; P < 10−6 and P = 0.01 for monkeys G and B, respectively, linear regression). Together, these results provide strong corroboration for the classification of solutions and demonstrate that deliberation times reflected the complexity of the underlying mental process. Fig. 4: ...