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Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

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  • Lian-hui Li
  • Rong Mo

Abstract

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Suggested Citation

  • Lian-hui Li & Rong Mo, 2015. "Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-24, September.
    • Handle: RePEc:plo:pone00:0134343
    DOI: 10.1371/journal.pone.0134343
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    Cited by:

    1. Imad Hassan & Ibrahim Alhamrouni & Nurul Hanis Azhan, 2023. "A CRITIC–TOPSIS Multi-Criteria Decision-Making Approach for Optimum Site Selection for Solar PV Farm," Energies, MDPI, vol. 16(10), pages 1-26, May.
    2. Lingjie Sun & Yingyi Liu & Boyang Zhang & Yuwei Shang & Haiwen Yuan & Zhao Ma, 2016. "An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers," Energies, MDPI, vol. 9(9), pages 1-22, August.

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