数学理论与应用 ›› 2017, Vol. 37 ›› Issue (2): 97-104.

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顶点加权最大团问题的加权分治算法

黄飞1 ,宁爱兵1 ,刘志民1 ,何咏梅1 ,王永斐2 ,张惠珍1   

  1. 1.上海理工大学管理学院,上海,200093; 2.58安居客,上海,200127
  • 出版日期:2017-06-30 发布日期:2020-09-23
  • 基金资助:

    国家自然科学基金(71401106);

    上海市一流学科建设项目资助(S1201YLXK);

    高等学校博士学科点专项科研基金联合资助课题(20123120120005)


Measure and Conquer Approach for the Maximum Vertex Weighted Clique Problem

Huang Fei 1 ,Ning Aibing1, Liu Zhimin1, He Yongmei 1, Wang Yongfei 2, Zhang Huizhen1   

  1. 1.School of Business,University of Shanghai for Science and Technology,Shanghai 200093,China; 2.58Anjuke,Shanghai 200127,China

  • Online:2017-06-30 Published:2020-09-23

摘要: 分支降阶被广泛用来求解NP-Hard问题,该技术的核心思想是将原问题分解成若干个子问题并递归求解这些子问题,但是用来分析算法时间复杂度的常规分析技术不够精确,无法得到较好的时间复杂度.本文设计了一个基于分支降阶的递归算法求解加权最大团问题,对于提出的精确算法,首先运用常规技术对该算法进行时间复杂度分析,得出其时间复杂度为O(1.4656np(n)),其中n 代表图中结点总个数,p(n)代表n的多项式函数;然后运用加权分治技术对原算法进行时间复杂度分析,将该算法的时间复杂性由原来的O(1.4656np(n))降为O(1.3765np(n)).研究结果表明运用加权分治技术能够得到较为精确的时间复杂度.

关键词:

"> 分支降阶算法, 顶点加权最大团问题, 时间复杂度, 加权分治, 图论

Abstract:

Branching and order-reducing are widely used for solving NP-Hard Problems.The main idea of the approach is to solve the problem by decomposing it into two or more sub-problems,and the sub-problems can be recursively solved.But we cannot get a better result by using the normal complexity analyticalmethod since it is not so accurate.The measure and conquer approach is a new technique for algorithm design and complexity analysis.This paper designs an algorithm to solve the weighted maximum clique problem and uses traditional analysis technology to analyze the worst-case running time of the algorithm and gets O(1.4656np(n))running time,where p(n)is the polynomial function of node number nin the problem.We employ the measure and conquer approach to improve the time complexity of the algorithm from O(1.4656np(n)) to O (1.3765np(n))without modifying the algorithm. Our results show that the measure and conquer approach can give more precise time complexity.

Key words:

Branching and order-reducing algorithm, Weighted maximum clique, Time complexity, Measure and conquer, Graph theory