, 43:146 | Cite as

Algorithms for separable convex optimization with linear ascending constraints

  • P T AkhilEmail author
  • Rajesh Sundaresan


The paper considers the minimization of a separable convex function subject to linear ascending constraints. The problem arises as the core optimization in several resource allocation scenarios, and is a special case of an optimization of a separable convex function over the bases of a polymatroid with a certain structure. The paper generalizes a prior algorithm to a wider class of separable convex objective functions that need not be smooth or strictly convex. The paper also summarizes the state-of-the-art algorithms that solve this optimization problem. When the objective function is a so-called \(d{\text {-}}\)separable function, a simpler linear time algorithm solves the problem.


Convex programming OR in telecommunications ascending constraints linear constraints polymatroid 



This work was supported by the Indo-French Centre for Promotion of Advanced Research under Project Number 5100-IT1.


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Copyright information

© Indian Academy of Sciences 2018

Authors and Affiliations

  1. 1.Department of Electrical Communication EngineeringIndian Institute of ScienceBangaloreIndia
  2. 2.Robert Bosch Centre for Cyber Physical SystemsIndian Institute of ScienceBangaloreIndia

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