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International Conference on Soft Computing, Intelligence Systems, and Information Technology

ICSIIT 2015: Intelligence in the Era of Big Data pp 89–97Cite as

ACO-LS Algorithm for Solving No-wait Flow Shop Scheduling Problem

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Part of the Communications in Computer and Information Science book series (CCIS,volume 516)

Abstract

In this paper, we propose a metaheuristic approach for the no-wait flow shop scheduling problem with respect to the makespan criterion. In the literature, this problem is known NP-hard type. In the literature, several algorithms have been proposed to solve this problem. We propose a hybridization of ant colony optimization (ACO) algorithm with local search (LS) in order to solve this scheduling problem, and then we call this as ACO-LS algorithm. This local search technique contributes to improve the quality of the resulting solutions. In addition, the mechanism of insert-remove technique is developed to help the searching of solution escape from the local optimum. The proposed algorithm is tested with the 31 well-known flow shop benchmark instance. The computational results based on well-known benchmarks and statistical performance comparisons are also reported. It is shown that the proposed ACO-LS algorithm is more effective than hybrid differential evolution (HDE) algorithm [Qian B., et.al, Computer & Industrial Engineering, 2009].

Keywords

  • Metaheuristic
  • No-wait flow shop scheduling
  • Makespan
  • Ant Colony Optimization
  • Local search

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Wijaya Putra, Jl.Raya Benowo No. 1-3, Surabaya, 60197, Indonesia

    Ong Andre Wahyu Riyanto

  2. Department of Industrial Engineering, Institut Teknologi Sepuluh Nopember, Kampus ITS, Sukolilo, Surabaya, 60111, Indonesia

    Budi Santosa

Authors
  1. Ong Andre Wahyu Riyanto
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  2. Budi Santosa
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Corresponding author

Correspondence to Ong Andre Wahyu Riyanto .

Editor information

Editors and Affiliations

  1. Informatics, Petra Christian University, Surabaya, Indonesia

    Rolly Intan

  2. CSIRO, Hobart, Tasmania, Australia

    Chi-Hung Chi

  3. Informatics, Petra Christian University, Surabaya, Indonesia

    Henry N. Palit

  4. Informatics, Petra Christian University, Surabaya, Indonesia

    Leo W. Santoso

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© 2015 Springer-Verlag Berlin Heidelberg

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Riyanto, O.A.W., Santosa, B. (2015). ACO-LS Algorithm for Solving No-wait Flow Shop Scheduling Problem. In: Intan, R., Chi, CH., Palit, H., Santoso, L. (eds) Intelligence in the Era of Big Data. ICSIIT 2015. Communications in Computer and Information Science, vol 516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46742-8_8

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  • DOI: https://doi.org/10.1007/978-3-662-46742-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46741-1

  • Online ISBN: 978-3-662-46742-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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