Winnowing Algorithm – A Novel Natural Computing Algorithm for Portfolio Weight Optimization

2019 ◽  
Author(s):  
Bharat Chawda ◽  
Jayeshkumar M. Patel
Keyword(s):  
Natural Computing ◽  
Weight Optimization ◽  
Computing Algorithm ◽  
Portfolio Weight

scholarly journals Enhanced Membrane Computing Algorithm for SAT Problems Based on the Splitting Rule

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1412
Author(s):  
Hao ◽  
Liu
Keyword(s):  
Membrane Computing ◽  
Space Complexity ◽  
Natural Computing ◽  
Sat Problem ◽  
Computing Algorithm ◽  
Complete Problems ◽  
Np Complete ◽  
Splitting Rule ◽  
Np Problems ◽  
Time And Space Complexity

Boolean propositional satisfiability (SAT) problem is one of the most widely studied NP-complete problems and plays an outstanding role in many domains. Membrane computing is a branch of natural computing which has been proven to solve NP problems in polynomial time with a parallel compute mode. This paper proposes a new algorithm for SAT problem which combines the traditional membrane computing algorithm of SAT problem with a classic simplification rule, the splitting rule, which can divide a clause set into two axisymmetric subsets, deal with them respectively and simultaneously, and obtain the solution of the original clause set with the symmetry of their solutions. The new algorithm is shown to be able to reduce the space complexity by distributing clauses with the splitting rule repeatedly, and also reduce both time and space complexity by executing one-literal rule and pure-literal rule as many times as possible.

Link Weight Optimization Scheme for Link Reinforcement in IP Networks

2017 ◽  
Vol E100.B (3) ◽  
pp. 417-425 ◽  
Author(s):  
Stephane KAPTCHOUANG ◽  
Hiroki TAHARA ◽  
Eiji OKI
Keyword(s):  
Ip Networks ◽  
Weight Optimization ◽  
Optimization Scheme ◽  
Link Weight

Co-Training Framework for Feature Weight Optimization of Statistic Machine Translation

2014 ◽  
Vol 23 (12) ◽  
pp. 3101-3114
Author(s):  
Shu-Jie LIU ◽  
Chi-Ho LI ◽  
Mu LI ◽  
Ming ZHOU
Keyword(s):  
Machine Translation ◽  
Weight Optimization ◽  
Feature Weight

Prepregnancy weight optimization and care

2013 ◽  
pp. 55-68
Author(s):  
Annunziata Lapolla ◽  
Maria Grazia Dalfra
Keyword(s):  
Weight Optimization ◽  
Prepregnancy Weight

A parallel biological computing algorithm to solve the vertex coloring problem with polynomial time complexity

2021 ◽  
pp. 1-11
Author(s):  
Zhaocai Wang ◽  
Dangwei Wang ◽  
Xiaoguang Bao ◽  
Tunhua Wu
Keyword(s):  
Time Complexity ◽  
Optimization Problems ◽  
Combinatorial Problem ◽  
Vertex Coloring ◽  
Intelligent Computing ◽  
Coloring Problem ◽  
Combinatorial Optimization Problems ◽  
Computing Algorithm ◽  
Vertex Coloring Problem ◽  
Dna Algorithm

The vertex coloring problem is a well-known combinatorial problem that requires each vertex to be assigned a corresponding color so that the colors on adjacent vertices are different, and the total number of colors used is minimized. It is a famous NP-hard problem in graph theory. As of now, there is no effective algorithm to solve it. As a kind of intelligent computing algorithm, DNA computing has the advantages of high parallelism and high storage density, so it is widely used in solving classical combinatorial optimization problems. In this paper, we propose a new DNA algorithm that uses DNA molecular operations to solve the vertex coloring problem. For a simple n-vertex graph and k different kinds of color, we appropriately use DNA strands to indicate edges and vertices. Through basic biochemical reaction operations, the solution to the problem is obtained in the O (kn2) time complexity. Our proposed DNA algorithm is a new attempt and application for solving Nondeterministic Polynomial (NP) problem, and it provides clear evidence for the ability of DNA calculations to perform such difficult computational problems in the future.

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