Research Article Open Access

Multi-Product Multi-Constraint Inventory Control Systems with Stochastic Replenishment and Discount under Fuzzy Purchasing Price and Holding Costs

Ata Allah Taleizadeh, Seyed Taghi Akhavan Niaki and Mir-Bahador Aryanezhad

Abstract

While in multi-periodic inventory control problems the usual assumption are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this research, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space, budget and service level constraints, incremental discount is considered to purchase products and a combination of back-order and lost-sales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixed-integer nonlinear programming type and in order to solve it, a hybrid method of fuzzy simulation and genetic algorithm approach is used. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology in real world inventory control problems.

American Journal of Applied Sciences
Volume 6 No. 1, 2009, 1-12

DOI: https://doi.org/10.3844/ajassp.2009.1.12

Submitted On: 21 February 2008 Published On: 31 January 2009

How to Cite: Taleizadeh, A. A., Niaki, S. T. A. & Aryanezhad, M. (2009). Multi-Product Multi-Constraint Inventory Control Systems with Stochastic Replenishment and Discount under Fuzzy Purchasing Price and Holding Costs . American Journal of Applied Sciences, 6(1), 1-12. https://doi.org/10.3844/ajassp.2009.1.12

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Keywords

  • genetic algorithm
  • Inventory control
  • stochastic replenishment
  • discount
  • fuzzy mixed-integer nonlinear programming
  • fuzzy simulation
  • genetic algorithm