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...
摘要: It is proved that the computation of , the constrained gradient is equivalent (in a coMplexity, theoretic sense), to quadratic programming. Since the *latter is an NP—hard problem, the constrained gradient method is not a 'good' method for linear programming unless P = AT....
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...
Computer science - Algorithms, Complexity, Programming: An algorithm is a specific procedure for solving a well-defined computational problem. The development and analysis of algorithms is fundamental to all aspects of computer science: artificial intell
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...
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: ...
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, ...
In this paper, we present a method to exactly certify the computational complexity of standard suboptimal branch-and-bound (B&B) algorithms for computing suboptimal solutions to mixed-integer linear programming (MILP) problems. Three well-known approaches for suboptimal B&B are considered. This work ...
foregoing all-vs-all sequence alignments in favor of a dynamic data structure implemented in GoldRush, a de novo long read genome assembly algorithm with linear time complexity. We tested GoldRush on Oxford Nanopore Technologies long sequencing read datasets with different base error profiles sourced ...
P versus NP problem, in computational complexity (a subfield of theoretical computer science and mathematics), the question of whether all so-called NP problems are actually P problems. A P problem is one that can be solved in “polynomial time,” which