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The robust machine availability problem

Author

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  • Guopeng Song
  • Daniel Kowalczyk
  • Roel Leus

Abstract

We define and solve the robust machine availability problem in a parallel machine environment, which aims to minimize the number of identical machines required while completing all the jobs before a given deadline. Our formulation preserves a user-defined robustness level regarding possible deviations in the job durations. For better computational performance, a branch-andprice procedure is proposed based on a set covering reformulation. We use zero-suppressed binary decision diagrams (ZDDs) for solving the pricing problem, which enable us to manage the difficulty entailed by the robustness considerations as well as by extra constraints imposed by branching decisions. Computational results are reported that show the effectiveness of a pricing solver with ZDDs compared with a MIP solver.

Suggested Citation

  • Guopeng Song & Daniel Kowalczyk & Roel Leus, 2017. "The robust machine availability problem," Working Papers of Department of Decision Sciences and Information Management, Leuven 585093, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
    • Handle: RePEc:ete:kbiper:585093
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    Keywords

    Parallel machine scheduling; Machine availability; Robust optimization; Branch and price; ZDD;
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