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Solving multi-objective constrained minimum weighted bipartite assignment problem: a case study on energy-aware radio broadcast scheduling

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Abstract

This paper proposes a multi-objective constrained minimum weighted bipartite assignment problem (MCMWBAP), which is considered an extension of the classical bipartite matching problem (BMP). We first provide the formulation of the MCMWBAP and prove that it is an NP-hard combinatorial optimization problem. Based on this formulation, multi-objective energy-aware shortwave radio broadcast resource allocation problem (MSRBRAP) application is studied. The goal of this problem is to allocate radio programs to transmission devices to broadcast all radio programs felicitously with a maximized objective of total qualified monitoring sites and a minimized objective of energy consumption. Then, a novel multi-objective hybrid evolutionary algorithm (MOHEA), which is integrated with push and pull initialization, the dynamic resource allocation strategy, and the aggregate local search procedure, is developed to solve the problem. The proposed method is evaluated using two categories of benchmarks for MCMWBAP together with a real scenario case study for MSRBRAP. Furthermore, the key components of MOHEA are analyzed, and the experimental results demonstrate that MOHEA outperforms two classical multi-objective evolutionary algorithms (NSGA-II and MOEA/D), improving working efficiency.

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Author notes

  1. Feifei MA and Minghao YIN have the same contribution to this work.

Authors and Affiliations

  1. College of Information Science and Technology, Northeast Normal University, Changchun, 130117, China

    Yupeng Zhou, Mingjie Fan & Minghao Yin

  2. Laboratory of Parallel Software and Computational Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China

    Feifei Ma

  3. State Key laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China

    Feifei Ma

Authors
  1. Yupeng Zhou
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  2. Mingjie Fan
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  3. Feifei Ma
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  4. Minghao Yin
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Correspondence to Feifei Ma or Minghao Yin.

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Zhou, Y., Fan, M., Ma, F. et al. Solving multi-objective constrained minimum weighted bipartite assignment problem: a case study on energy-aware radio broadcast scheduling. Sci. China Inf. Sci. 65, 182101 (2022). https://doi.org/10.1007/s11432-019-3017-9

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  • DOI: https://doi.org/10.1007/s11432-019-3017-9

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