4.7 Article

Simultaneous machine selection and buffer allocation in large unbalanced series-parallel production lines

Journal

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 60, Issue 7, Pages 2103-2125

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2021.1884306

Keywords

Simultaneous buffer and server allocation; series-parallel production lines; decomposition-coordination; optimisation; large-scale

Funding

  1. China Postdoctoral Science Foundation [2020M682621]
  2. National Natural Science Foundation of China [51775120, 51805096,61973089,71972053]

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Simultaneously optimizing machines and buffers in a large series-parallel production line is a challenging NP-hard problem. This study proposes a decomposition-coordination method to efficiently generate allocation solutions, and numerical experiments demonstrate its performance and the influences of target system parameters.
Simultaneous optimisation of machines and buffers in a large series-parallel production line is an NP-hard problem. The formulated optimisation model in this study is used to minimise the total investment cost subject to the desired throughput rate and cycle time by optimising the machine types, number of parallel machines, and buffer capacities. To solve this kind of design problem, a decomposition-coordination method is proposed to efficiently and accurately generate allocation solutions for large production lines. The proposed method includes two iterative processes: the decomposition process decouples the original line into several small lines and optimises them separately, while the coordination process ensures that the optimisation problems of the decomposed lines are similar to the corresponding part of the original. The performance of this approach is demonstrated through numerical experiments by comparisons with the simulated annealing algorithm and non-dominated sorting genetic algorithm-II. Finally, the sets of numerical results and a multi-factorial experimental analysis illustrate the influences of target system parameters on the resource configurations.

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