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A problem reduction based approach to discrete optimization algorithm design

机译:基于问题减少的离散优化算法设计方法

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摘要

The paper presents a novel approach to formal algorithm design for a typical class of discrete optimization problems. Using a concise set of program calculation rules, our approach reduces a problem into subproblems with less complexity based on function decompositions, constructs the problem reduction graph that describes the recurrence relations between the problem and subproblems, from which a provably correct algorithm can be mechanically derived. Our approach covers a large variety of algorithms and bridges the relationship between conventional methods for designing efficient algorithms (including dynamic programming and greedy) and some effective methods for coping with intractability (including approximation and parameterization).
机译:本文针对典型的一类离散优化问题提出了一种形式化算法设计的新方法。通过使用一组简洁的程序计算规则,我们的方法基于函数分解将问题分解为复杂度较低的子问题,构造描述问题和子问题之间的递归关系的问题减少图,从中可以机械地推导出可证明正确的算法。我们的方法涵盖了各种各样的算法,并在设计有效算法的常规方法(包括动态编程和贪婪)与应对复杂性(包括近似和参数化)的某些有效方法之间架起了桥梁。

著录项

  • 来源
    《Computing》 |2010年第2期|31-54|共24页
  • 作者

    Yujun Zheng; Jinyun Xue;

  • 作者单位

    Institute of Software, Chinese Academy of Sciences, #4 South Fourth Street, Zhong Guan Cun, Beijing 100080, China;

    Provincial Key Lab of High-Performance Computing, Jiangxi Normal University, Nanchang 330023, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    discrete optimization; program calculation; problem reduction graph (PRG); algorithm design;

    机译:离散优化程序计算;问题减少图(PRG);算法设计;

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