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EPQ models with bivariate random imperfect proportions and learning-dependent production and demand rates

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  • S. Ganesan
  • R. Uthayakumar

Abstract

In this paper, three production inventory models are constructed for an imperfect manufacturing system by considering a warm-up production run, shortages during the hybrid maintenance period, and the rework of imperfect items. The proportions of imperfect items produced during the warm-up and regular production runs are random and they are represented using a bivariate random variable. The shortage quantity is partially backordered and the supply of backorder quantity is planned simultaneously with regular demand satisfaction. The learning models are designed to accommodate the different learning capabilities of workers in unit production time during warm-up and regular production periods. The production and demand rates of these models are made dependent on the learning exponents. As the resulting models are highly nonlinear in the decision variable, they are optimized using a genetic algorithm. The models are illustrated using numerical examples and sensitivity studies are performed to find the influence of the key parameters.

Suggested Citation

  • S. Ganesan & R. Uthayakumar, 2021. "EPQ models with bivariate random imperfect proportions and learning-dependent production and demand rates," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 134-170, January.
    • Handle: RePEc:taf:tjmaxx:v:8:y:2021:i:1:p:134-170
    DOI: 10.1080/23270012.2020.1818320
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    Cited by:

    1. Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Dagoberto Garza-Núñez & Gerardo Treviño-Garza & Armando Céspedes-Mota & Imelda de Jesús Loera-Hernández & Neale R. Smith & Amir Hossein Nobil, 2023. "Machine Downtime Effect on the Warm-Up Period in an Economic Production Quantity Problem," Mathematics, MDPI, vol. 11(7), pages 1-23, April.
    2. S. Ganesan & R. Uthayakumar, 2023. "An EPQ model for a single-machine multiproduct imperfect production system using a hybrid logarithmic barrier method," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1121-1152, September.
    3. Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Imelda de Jesús Loera-Hernández & Neale R. Smith & Gerardo Treviño-Garza & Armando Céspedes-Mota & Amir Hossein Nobil, 2023. "Sustainability Economic Production Quantity with Warm-Up Function for a Defective Production System," Sustainability, MDPI, vol. 15(2), pages 1-19, January.

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