The robust machine availability problem

Guopeng Song, Daniel Kowalczyk and Roel Leus

No 585093, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

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.

Keywords: Parallel machine scheduling; Machine availability; Robust optimization; Branch and price; ZDD (search for similar items in EconPapers)
Date: 2017-06
New Economics Papers: this item is included in nep-cmp
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Published in FEB Research Report KBI_1708

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