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An improved branch-and-bound algorithm for seru scheduling problems with DeJong's learning effect

Author

Listed:
  • Ran Li
  • Zhe Zhang
  • Xiaoling Song
  • Xue Gong

Abstract

Seru production system (SPS), which is an effective production mode to respond to ever-changing market demand quickly, has gained increasing attention due to its adaptability and efficiency in practice. This paper aims to address the seru scheduling problem considering DeJong's learning effect to minimise total tardiness. An integer programming (IP) model is formulated, and an improved branch-and-bound (B%B) algorithm based on depth-first search is developed to find the optimal solution. Several dominance properties, a heuristic upper bound algorithm and two lower bounds are devised to improve the efficiency of B%B algorithm. Computational experiments are made finally, and results show that the problem can be optimally solved within a short computational time. The effectiveness of proposed B%B algorithm for the seru scheduling problem is also verified. [Received: 10 August 2023; accepted: 20 March 2024]

Suggested Citation

  • Ran Li & Zhe Zhang & Xiaoling Song & Xue Gong, 2026. "An improved branch-and-bound algorithm for seru scheduling problems with DeJong's learning effect," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 22(1), pages 22-52.
    • Handle: RePEc:ids:eujine:v:22:y:2026:i:1:p:22-52
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