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Application of enhanced benders decomposition algorithm in circular assembly line balancing problem with task

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  • 1School of Artificial Intelligence, Dongguan City University, Dongguan, Guangdong, China.

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|October 6, 2025
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We developed an Enhanced Benders Decomposition (EBD) framework to solve the complex Circular Assembly Line Balancing Problem with Task-Splitting (CALBP-TS). EBD significantly reduces runtime and improves solution quality for manufacturing optimization.

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Area of Science:

  • Operations Research
  • Industrial Engineering
  • Manufacturing Systems

Background:

  • Assembly lines are crucial for manufacturing efficiency.
  • The Circular Assembly Line Balancing Problem with Task-Splitting (CALBP-TS) presents a complex optimization challenge.
  • Existing methods struggle with the high-dimensional complexity of CALBP-TS.

Purpose of the Study:

  • Introduce and solve the novel CALBP-TS.
  • Develop an efficient optimization framework for circular assembly lines.
  • Enhance resource utilization in space-constrained production systems.

Main Methods:

  • Propose an Enhanced Benders Decomposition (EBD) framework.
  • Decompose CALBP-TS into a master problem (MP) and subproblem (SP).
  • Utilize algorithmic accelerators: Heuristic Infeasibility Proof (HIP) and Enhanced Benders Cuts (EBC) with Local Branching.

Main Results:

  • EBD achieves significant runtime reductions (up to 97.8%) compared to MILP, GA+LP, and Greedy+LP.
  • Solution quality is improved by up to 41.3%.
  • HIP and EBC enhance computational efficiency by 13.7%.

Conclusions:

  • EBD effectively addresses the CALBP-TS.
  • The methodology optimizes resource utilization in circular production systems.
  • This work provides a robust solution for complex assembly line balancing problems.