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

  • Jun PeiEmail author
  • Xinbao Liu
  • Wenjuan Fan
  • Panos M. Pardalos
  • Lin Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8426)


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.


Supply chain scheduling Batching Dynamic programming Heuristic algorithm 



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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jun Pei
    • 1
    • 2
    Email author
  • Xinbao Liu
    • 1
    • 3
  • Wenjuan Fan
    • 1
    • 4
  • Panos M. Pardalos
    • 2
  • Lin Liu
    • 1
    • 3
  1. 1.School of ManagementHefei University of TechnologyHefeiChina
  2. 2.Center for Applied Optimization, Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  3. 3.Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of EducationHefeiChina
  4. 4.Department of Computer ScienceNorth Carolina State UniversityRaleighUSA

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