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Accelerated Benders decomposition algorithm for the sequence-dependent cost-oriented assembly line balancing problem
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DOI：10.1080/0305215X.2026.2647968.png)
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Abstract
En 中文
The sequence-dependent cost-oriented assembly line balancing (SDCALB) problem is an NP-hard optimization problem. To solve this problem, a position-based mathematical model is formulated, and then the pure Benders decomposition (PBD) algorithm is proposed. Two acceleration methods are also suggested to improve the convergence rate and reduce solution time for the PBD algorithm: combinatorial Benders cuts (CBCs) and a heuristic algorithm that generates feasible solutions and optimality cuts when the subproblem is infeasible. The efficacy of these methods is evaluated by incorporating them separately and collectively with the PBD algorithm and analysing their performance. The results show that both CBCs and the heuristic algorithm methods improve the convergence rate and solution time. Moreover, the accelerated Benders algorithm demonstrates superior performance to commercial solvers and existing decomposition methods.
Keywords:
Combinatorial optimization
assembly line balancing problem
sequence-dependent set-up time
Benders decomposition algorithm
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2.2
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105
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3.8K
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