A Class of Convex Quadratic Nonseparable Resource Allocation Problems with Generalized Bound Constraints

Martijn H.H. Schoot Uiterkamp*, Marco E. T. Gerards, Johann L. Hurink

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

We study a convex quadratic nonseparable resource allocation problem that arises in the area of decentralized energy management (DEM), where unbalance in electricity networks has to be minimized. In this problem, the given resource is allocated over a set of activities that is divided into subsets, and a cost is assigned to the overall allocated amount of resources to activities within the same subset. We derive two efficient algorithms with O(nlog n) worst-case time complexity to solve this problem. For the special case where all subsets have the same size, one of these algorithms even runs in linear time given the subset size. Both algorithms are inspired by well-studied breakpoint search methods for separable convex resource allocation problems. Numerical evaluations on both real and synthetic data confirm the theoretical efficiency of both algorithms and demonstrate their suitability for integration in DEM systems.
Original languageEnglish
Pages (from-to)215-247
JournalINFORMS Journal on Optimization
Volume4
Issue number2
DOIs
Publication statusPublished - 28 Feb 2022

Keywords

  • Resource allocation
  • Energy management
  • Nonseparable optimization
  • 2023 OA procedure

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