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A parameter-tuned genetic algorithm to optimize two-echelon continuous review inventory systems

Pasandideh, S. H. R ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1016/j.eswa.2011.03.056
  3. Publisher: 2011
  4. Abstract:
  5. This paper deals with a two-echelon inventory system for a non-repairable item where the system consists of one warehouse and m identical retailers and uses continuous-review (R, Q) ordering policy. To find an effective stocking policy for this system, a mathematical model with the objective of minimizing the total annual inventory investment subject to constraints on the average annual order frequency, expected number of backorders, and budget is formulated. The mathematical model of the problem at hand is shown to be nonlinear integer-programming and hence a parameter-tuned genetic algorithm is proposed to solve it efficiently. A numerical example is provided at the end to illustrate the applicability of the proposed methodology
  6. Keywords:
  7. Continuous review policy ; Backorders ; Continuous review ; Continuous-review inventory systems ; Inventory investment ; Meta heuristic algorithm ; Multi-echelon inventory ; Nonlinear-integer programming ; Numerical example ; Ordering policies ; Repairable items ; Two-echelon inventory ; Genetic algorithms ; Heuristic algorithms ; Heuristic methods ; Integer programming ; Inventory control ; Optimization ; Parameter estimation ; Mathematical models
  8. Source: Expert Systems with Applications ; Volume 38, Issue 9 , September , 2011 , Pages 11708-11714 ; 09574174 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0957417411004647