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An inventory model for deteriorating items under inflation and permissible delay in payments by genetic algorithm

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  • Sanjey Kumar
  • Neeraj Kumar

Abstract

Inventory models play a leading role in analyzing a lot of realistic situations arising at places like, food and vegetable markets, market yards, oil exploration industries, etc. In the present article, we developed an inventory model for deteriorating items with permissible delay in payment under inflation. In the given model, demand rate is considered as stock-dependent and deterioration rate of each item follows Weibull distribution. The model is developed under two different circumstances depending on whether the credit period is (1) less than the cycle time (2) greater than the cycle time. Also, a new algorithm is developed under these scenarios to obtain the EOQ. Finally results are analyzed and demonstrated with illustrative examples by Genetic Algorithm.

Suggested Citation

  • Sanjey Kumar & Neeraj Kumar, 2016. "An inventory model for deteriorating items under inflation and permissible delay in payments by genetic algorithm," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1239605-123, December.
    • Handle: RePEc:taf:oabmxx:v:3:y:2016:i:1:p:1239605
    DOI: 10.1080/23311975.2016.1239605
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    Cited by:

    1. Tapan Kumar Datta & Sayantan Datta & Adrijit Goswami, 2024. "A sustainable bi-objective inventory model with source-based emissions and plan-based green investments under inflation and the present value of money," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(1), pages 91-117.
    2. Haider Ali & Reshma Nasreen & Neetu Arneja & Chandra K. Jaggi, 2023. "Optimization of a periodically assessing model with manageable lead time under SLC with back order rebate for deteriorating items," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 241-266, February.

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