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A Novel Hybrid Dynamic Programming Algorithm for a Two-Stage Supply Chain Scheduling Problem

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Book cover Learning and Intelligent Optimization (LION 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8426))

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Abstract

This study addresses a two-stage supply chain scheduling problem, where the jobs need to be processed on the manufacturer’s serial batching machine and then transported by vehicles to the customer for further processing. The size and processing time of the jobs are varying due to the differences of types, and setup time is needed before processing one batch. For the problem with minimizing the makespan, we formalize it as a mixed integer programming model. In addition, the structural properties and lower bound of the problem are provided. Based on the analysis above, a novel hybrid dynamic programming algorithm, combining dynamic programming and heuristics, is proposed to solve the problem. Furthermore, its time complexity is also analyzed. By comparing the experimental results of our proposed algorithm with the heuristics \(BFF\) and \(LFF\), we demonstrate that our proposed algorithm has better performance and can solve the problem in a reasonable time.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Nos. 71231004, 71171071, 71131002). Panos M. Pardalos is partially supported by LATNA laboratory, NRU HSE, RF government grant, ag. 11.G34.31.0057.

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, China

    Jun Pei, Xinbao Liu, Wenjuan Fan & Lin Liu

  2. Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, 32601, USA

    Jun Pei & Panos M. Pardalos

  3. Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education, Hefei, 230009, China

    Xinbao Liu & Lin Liu

  4. Department of Computer Science, North Carolina State University, Raleigh, 27695-7534, USA

    Wenjuan Fan

Authors
  1. Jun Pei
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  2. Xinbao Liu
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  3. Wenjuan Fan
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  4. Panos M. Pardalos
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  5. Lin Liu
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Corresponding author

Correspondence to Jun Pei .

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Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. AT&T Labs Research, Middletown, New Jersey, USA

    Mauricio G.C. Resende

  3. University of Florida, Gainesville, Florida, USA

    Chrysafis Vogiatzis

  4. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Jose L. Walteros

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Pei, J., Liu, X., Fan, W., Pardalos, P.M., Liu, L. (2014). A Novel Hybrid Dynamic Programming Algorithm for a Two-Stage Supply Chain Scheduling Problem. In: Pardalos, P., Resende, M., Vogiatzis, C., Walteros, J. (eds) Learning and Intelligent Optimization. LION 2014. Lecture Notes in Computer Science(), vol 8426. Springer, Cham. https://doi.org/10.1007/978-3-319-09584-4_23

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  • DOI: https://doi.org/10.1007/978-3-319-09584-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09583-7

  • Online ISBN: 978-3-319-09584-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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