Empowering the Configuration-IP - New PTAS Results for Scheduling with Setups Times

Authors Klaus Jansen, Kim-Manuel Klein, Marten Maack, Malin Rau



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Author Details

Klaus Jansen
  • Department of Computer Science, Kiel University, Kiel, Germany
Kim-Manuel Klein
  • Department of Computer Science, Kiel University, Kiel, Germany
Marten Maack
  • Department of Computer Science, Kiel University, Kiel, Germany
Malin Rau
  • Department of Computer Science, Kiel University, Kiel, Germany

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Klaus Jansen, Kim-Manuel Klein, Marten Maack, and Malin Rau. Empowering the Configuration-IP - New PTAS Results for Scheduling with Setups Times. In 10th Innovations in Theoretical Computer Science Conference (ITCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 124, pp. 44:1-44:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ITCS.2019.44

Abstract

Integer linear programs of configurations, or configuration IPs, are a classical tool in the design of algorithms for scheduling and packing problems, where a set of items has to be placed in multiple target locations. Herein a configuration describes a possible placement on one of the target locations, and the IP is used to chose suitable configurations covering the items. We give an augmented IP formulation, which we call the module configuration IP. It can be described within the framework of n-fold integer programming and therefore be solved efficiently. As an application, we consider scheduling problems with setup times, in which a set of jobs has to be scheduled on a set of identical machines, with the objective of minimizing the makespan. For instance, we investigate the case that jobs can be split and scheduled on multiple machines. However, before a part of a job can be processed an uninterrupted setup depending on the job has to be paid. For both of the variants that jobs can be executed in parallel or not, we obtain an efficient polynomial time approximation scheme (EPTAS) of running time f(1/epsilon) x poly(|I|) with a single exponential term in f for the first and a double exponential one for the second case. Previously, only constant factor approximations of 5/3 and 4/3 + epsilon respectively were known. Furthermore, we present an EPTAS for a problem where classes of (non-splittable) jobs are given, and a setup has to be paid for each class of jobs being executed on one machine.

Subject Classification

ACM Subject Classification
  • Theory of computation → Scheduling algorithms
  • Theory of computation → Discrete optimization
Keywords
  • Parallel Machines
  • Setup Time
  • EPTAS
  • n-fold integer programming

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References

  1. Ali Allahverdi, Jatinder ND Gupta, and Tariq Aldowaisan. A review of scheduling research involving setup considerations. Omega, 27(2):219-239, 1999. Google Scholar
  2. Ali Allahverdi, CT Ng, TC Edwin Cheng, and Mikhail Y Kovalyov. A survey of scheduling problems with setup times or costs. European journal of operational research, 187(3):985-1032, 2008. Google Scholar
  3. Noga Alon, Yossi Azar, Gerhard J Woeginger, and Tal Yadid. Approximation schemes for scheduling on parallel machines. Journal of Scheduling, 1(1):55-66, 1998. Google Scholar
  4. Bo Chen. A better heuristic for preemptive parallel machine scheduling with batch setup times. SIAM Journal on Computing, 22(6):1303-1318, 1993. Google Scholar
  5. Bo Chen, Yinyu Ye, and Jiawei Zhang. Lot-sizing scheduling with batch setup times. Journal of Scheduling, 9(3):299-310, 2006. Google Scholar
  6. Lin Chen, Dániel Marx, Deshi Ye, and Guochuan Zhang. Parameterized and approximation results for scheduling with a low rank processing time matrix. In LIPIcs-Leibniz International Proceedings in Informatics, volume 66. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2017. Google Scholar
  7. José Correa, Alberto Marchetti-Spaccamela, Jannik Matuschke, Leen Stougie, Ola Svensson, Víctor Verdugo, and José Verschae. Strong LP formulations for scheduling splittable jobs on unrelated machines. Mathematical Programming, 154(1-2):305-328, 2015. Google Scholar
  8. José Correa, Victor Verdugo, and José Verschae. Splitting versus setup trade-offs for scheduling to minimize weighted completion time. Operations Research Letters, 44(4):469-473, 2016. Google Scholar
  9. Friedrich Eisenbrand, Christoph Hunkenschröder, and Kim-Manuel Klein. Faster Algorithms for Integer Programs with Block Structure. In 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018, July 9-13, 2018, Prague, Czech Republic, pages 49:1-49:13, 2018. Google Scholar
  10. Paul C Gilmore and Ralph E Gomory. A linear programming approach to the cutting-stock problem. Operations research, 9(6):849-859, 1961. Google Scholar
  11. Michel X Goemans and Thomas Rothvoß. Polynomiality for bin packing with a constant number of item types. In Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete algorithms, pages 830-839. SIAM, 2014. Google Scholar
  12. Raymond Hemmecke, Shmuel Onn, and Lyubov Romanchuk. N-fold integer programming in cubic time. Mathematical Programming, pages 1-17, 2013. Google Scholar
  13. Dorit S Hochbaum and David B Shmoys. Using dual approximation algorithms for scheduling problems theoretical and practical results. Journal of the ACM (JACM), 34(1):144-162, 1987. Google Scholar
  14. Klaus Jansen, Kim-Manuel Klein, Marten Maack, and Malin Rau. Empowering the Configuration-IP - New PTAS Results for Scheduling with Setups Times. CoRR, abs/ 1801.06460v2, 2018. URL: http://arxiv.org/abs/1801.06460.
  15. Klaus Jansen, Kim-Manuel Klein, and José Verschae. Closing the Gap for Makespan Scheduling via Sparsification Techniques. In 43rd International Colloquium on Automata, Languages, and Programming, ICALP 2016, July 11-15, 2016, Rome, Italy, pages 72:1-72:13, 2016. Google Scholar
  16. Klaus Jansen and Felix Land. Non-preemptive Scheduling with Setup Times: A PTAS. In European Conference on Parallel Processing, pages 159-170. Springer, 2016. Google Scholar
  17. Ravi Kannan. Minkowski’s convex body theorem and integer programming. Mathematics of operations research, 12(3):415-440, 1987. Google Scholar
  18. Dusan Knop and Martin Koutecký. Scheduling meets n-fold Integer Programming. Journal of Scheduling, pages 1-11, 2017. Google Scholar
  19. Dusan Knop, Martin Koutecký, and Matthias Mnich. Combinatorial n-fold Integer Programming and Applications. In 25th Annual European Symposium on Algorithms, ESA 2017, September 4-6, 2017, Vienna, Austria, pages 54:1-54:14, 2017. Google Scholar
  20. Martin Koutecký, Asaf Levin, and Shmuel Onn. A Parameterized Strongly Polynomial Algorithm for Block Structured Integer Programs. In 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018, July 9-13, 2018, Prague, Czech Republic, pages 85:1-85:14, 2018. Google Scholar
  21. Hendrik W Lenstra Jr. Integer programming with a fixed number of variables. Mathematics of operations research, 8(4):538-548, 1983. Google Scholar
  22. Alexander Mäcker, Manuel Malatyali, Friedhelm Meyer auf der Heide, and Sören Riechers. Non-preemptive scheduling on machines with setup times. In Workshop on Algorithms and Data Structures, pages 542-553. Springer, 2015. Google Scholar
  23. Clyde L Monma and Chris N Potts. Analysis of heuristics for preemptive parallel machine scheduling with batch setup times. Operations Research, 41(5):981-993, 1993. Google Scholar
  24. Shmuel Onn. Nonlinear discrete optimization. Zurich Lectures in Advanced Mathematics, European Mathematical Society, 2010. Google Scholar
  25. Frans Schalekamp, René Sitters, Suzanne Van Der Ster, Leen Stougie, Víctor Verdugo, and Anke Van Zuylen. Split scheduling with uniform setup times. Journal of scheduling, 18(2):119-129, 2015. Google Scholar
  26. Petra Schuurman and Gerhard J Woeginger. Preemptive scheduling with job-dependent setup times. In Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms, pages 759-767. Society for Industrial and Applied Mathematics, 1999. Google Scholar
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