Scaling Algorithms for M-Convex Function Minimization(Special Section on Discrete Mathematics and Its Applications)

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概要

• 論文の詳細を見る

• M-convex functions have various desirable properties as convexity in discrete optimization. We can find a global minimum of an M-convex function by a greedy algorithm, i.e., so-called descent algorithms work for the minimization. In this paper, we apply a scaling technique to a greedy algorithm and propose an efficient algorithm for the minimization of an M-convex function. Computational results are also reported.

• 社団法人電子情報通信学会の論文
• 2002-05-01

著者

• Murota Kazuo

  The Author Is With Graduate School Of Information Science And Technology University Of Tokyo

• Moriguchi S

  The Author Is With Department Of Mathematical And Computing Sciences Tokyo Institute Of Technology

• MORIGUCHI Satoko

  The author is with Department of Mathematical and Computing Sciences, Tokyo Institute of Technology

• SHIOURA Akiyoshi

  The author is with Graduate School of Information Sciences, Tohoku University

• Shioura Akiyoshi

  The Author Is With Graduate School Of Information Sciences Tohoku University

関連論文

• Scaling Algorithms for M-Convex Function Minimization(Special Section on Discrete Mathematics and Its Applications)
• Level Set Characterization of M-convex Functions(Special Section on Discrete Mathematics and Its Applications)

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