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On Min-Max Graph Balancing with Strict Negative Correlation Constraints

Authors Ting-Yu Kuo, Yu-Han Chen, Andrea Frosini , Sun-Yuan Hsieh , Shi-Chun Tsai , Mong-Jen Kao



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Ting-Yu Kuo
  • Dept. of Computer Science, National Yang-Ming Chiao-Tung University, Hsinchu, Taiwan
Yu-Han Chen
  • Dept. of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan
Andrea Frosini
  • Dept. of Mathematics and Informatics, University of Florence, Italy
Sun-Yuan Hsieh
  • Dept. of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan
  • Dept. of Computer Science and Information Engineering, National Chi-Nan University, Puli, Taiwan
Shi-Chun Tsai
  • Dept. of Computer Science, National Yang-Ming Chiao-Tung University, Hsinchu, Taiwan
Mong-Jen Kao
  • Dept. of Computer Science, National Yang-Ming Chiao-Tung University, Hsinchu, Taiwan

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Ting-Yu Kuo, Yu-Han Chen, Andrea Frosini, Sun-Yuan Hsieh, Shi-Chun Tsai, and Mong-Jen Kao. On Min-Max Graph Balancing with Strict Negative Correlation Constraints. In 34th International Symposium on Algorithms and Computation (ISAAC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 283, pp. 50:1-50:15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ISAAC.2023.50

Abstract

We consider the min-max graph balancing problem with strict negative correlation (SNC) constraints. The graph balancing problem arises as an equivalent formulation of the classic unrelated machine scheduling problem, where we are given a hypergraph G = (V,E) with vertex-dependent edge weight function p: E×V ↦ ℤ^{≥0} that represents the processing time of the edges (jobs). The SNC constraints, which are given as edge subsets C_1,C_2,…,C_k, require that the edges in the same subset cannot be assigned to the same vertex at the same time. Under these constraints, the goal is to compute an edge orientation (assignment) that minimizes the maximum workload of the vertices. In this paper, we conduct a general study on the approximability of this problem. First, we show that, in the presence of SNC constraints, the case with max_{e ∈ E} |e| = max_i |C_i| = 2 is the only case for which approximation solutions can be obtained. Further generalization on either direction, e.g., max_{e ∈ E} |e| or max_i |C_i|, will directly make computing a feasible solution an NP-complete problem to solve. Then, we present a 2-approximation algorithm for the case with max_{e ∈ E} |e| = max_i |C_i| = 2, based on a set of structural simplifications and a tailored assignment LP for this problem. We note that our approach is general and can be applied to similar settings, e.g., scheduling with SNC constraints to minimize the weighted completion time, to obtain similar approximation guarantees. Further cases are discussed to describe the landscape of the approximability of this prbolem. For the case with |V| ≤ 2, which is already known to be NP-hard, we present a fully-polynomial time approximation scheme (FPTAS). On the other hand, we show that the problem is at least as hard as vertex cover to approximate when |V| ≥ 3.

Subject Classification

ACM Subject Classification
  • Theory of computation → Scheduling algorithms
Keywords
  • Unrelated Scheduling
  • Graph Balancing
  • Strict Correlation Constraints

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