A Fuzzy-stochastic Inventory Model without Backorder under Uncertainty in Customer Demand

Pankaj Dutta, Madhukar Nagare

2013

Abstract

In the current business scenario, a vital aspect of a realistic inventory model is to accurately estimate the customer demand especially in uncertain environment. Keeping this fact in mind recent trend of research includes uncertain demand, either random or fuzzy. In this paper, we amalgamate both random behavior and fuzzy perception into the optimization setting in modeling an inventory model without backorder. Treating customer demand as fuzzy random variable, we aim at providing an approach of modeling uncertainty that is closer to real situations. In addition, a distinct characteristic of this study is that the decision maker’s degree of optimism is incorporated in this model using possibilistic mean value approach. The objective is to determine the optimal order quantity associated with cost minimization. An illustrative numerical example is presented to clarify the reality of the model.

References

  1. Carlsson, C., Fuller, R., 2001. On possibilistic mean value and variance of fuzzy numbers, Fuzzy Sets and Systems 122, 315-326.
  2. Chang, H. C., Yao, J. S., Ouyang, L. Y., 2006. Fuzzy mixture inventory model involving fuzzy random variable lead-time demand and fuzzy total demand, European Journal of Operational Research 169, 65- 80.
  3. Chen, S. H., Wang, C. C.,1996. Backorder fuzzy inventory model under functional principle, Information Sciences 95, 71-79.
  4. Dutta, P., Chakraborty, D.,2010. Incorporating one-way substitution policy into the newsboy problem with imprecise customer demand, European Journal of Operational Research 200, 99-110.
  5. Dutta, P., Chakraborty, D., Roy, A. R. 2005. A single period inventory model with fuzzy random variable demand, Mathematical and Computer Modeling41, 915-922.
  6. Dutta, P., Chakraborty, D., Roy, A. R. 2007a. An inventory model for single period products with reordering opportunities under fuzzy demand, Computers and Mathematics with Applications 53,1502-1517.
  7. Dutta, P., Chakraborty, D., Roy, A. R., 2007b. Continuous review inventory model in mixed fuzzy and stochastic environment, Applied Mathematics and Computation 188, 970-980.
  8. Dutta, P., Roy, A. R. 2007. Decision on back order inventory model under mixed uncertainty, Tamsui Oxford Journal of Management Sciences 23, 59-70.
  9. Dutta, P., Chakraborty, D.,Roy, A. R., 2012. Uncertain Demand in (Q, r) inventory systems: A fuzzy optimization approach, The Journal of Fuzzy Mathematics 20, 501-514.
  10. Feng,Y., Hu, L., Shu, H., 2001.The variance and covariance of fuzzy random variables and their applications, Fuzzy Sets and Systems 120, 117-127.
  11. Hsieh, C. H., 2002. Optimization of fuzzy production inventory models, Information Sciences 146, 29-40.
  12. Lee, H. M., Yao, J. S., 1999a. Economic order quantity in fuzzy sense for inventory without backorder model, Fuzzy Sets and Systems 105, 12-31.
  13. Lee, H. M., Yao, J. S.,1999b. Fuzzy inventory with or without backorder order quantity with trapezoid fuzzy number, Fuzzy Sets and Systems 105, 311-337.
  14. Lopez-Diaz, M., Gil, M. A. 1998. The -average value of the expected value of a fuzzy random variable, Fuzzy Sets and Systems 99, 347-391.
  15. Luhandjula, M. K. 2004. Fuzzy random variable: A mathematical tool for combining randomnessand fuzziness, Journal of Fuzzy Mathematics 12,755-764.
  16. Nagare, M., Dutta, P. 2012. On solving single-period inventory model under hybrid uncertainty, International Journal of Economics and Management Sciences 6, 290-295.
  17. Yao, J. S., Chang, S. C., Su, J. S., 2000. Fuzzy inventory without backorder for fuzzy order quantity and fuzzy total demand quantity, Computers and Operations Research 27, 935-962.
  18. Yao, J. S., Chiang, J., 2003. Inventory without backorder with fuzzy total cost and fuzzy storing cost defuzzified by centroid and signed distance, European Journal of Operational Research 148, 401-409.
Download


Paper Citation


in Harvard Style

Dutta P. and Nagare M. (2013). A Fuzzy-stochastic Inventory Model without Backorder under Uncertainty in Customer Demand . In Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8565-40-2, pages 109-114. DOI: 10.5220/0004342801090114


in Bibtex Style

@conference{icores13,
author={Pankaj Dutta and Madhukar Nagare},
title={A Fuzzy-stochastic Inventory Model without Backorder under Uncertainty in Customer Demand},
booktitle={Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2013},
pages={109-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004342801090114},
isbn={978-989-8565-40-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - A Fuzzy-stochastic Inventory Model without Backorder under Uncertainty in Customer Demand
SN - 978-989-8565-40-2
AU - Dutta P.
AU - Nagare M.
PY - 2013
SP - 109
EP - 114
DO - 10.5220/0004342801090114