E. Teimoury, H. Ansari , M. Fathi ,
Volume 22, Issue 1 (3-2011)
Abstract
The importance of reliable supply is increasing with supply chain network extension and just-in-time (JIT) production. Just in time implications motivate manufacturers towards single sourcing, which often involves problems with unreliable suppliers. If a single and reliable vendor is not available, manufacturer can split the order among the vendors in order to simultaneously decrease the supply chain uncertainty and increase supply reliability. In this paper we discuss with the aim of minimizing the shortage cost how we can split orders among suppliers with different lead times. The (s,S) policy is the basis of our inventory control system and for analyzing the system performance we use the fuzzy queuing methodology. After applying the model for the case study (SAPCO), the result of the developed model will be compared in the single and multiple cases and finally we will find that order splitting in optimized condition will conclude in the least supply risk and minimized shortage cost in comparison to other cases .
E. Teimoury, I.g. Khondabi , M. Fathi ,
Volume 22, Issue 3 (9-2011)
Abstract
Discrete facility location, Distribution center, Logistics, Inventory policy, Queueing theory, Markov processes, |
The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with a M/M/1 finite queueing system plus balking and reneging. The distribution center uses one for one inventory policy, where each arrival demand orders a unit of product to the distribution center and the distribution center refers this demand to its supplier. The matrix geometric method is applied to model the queueing system in order to obtain the steady-state probabilities and evaluate some performance measures. A cost model is developed to determine the best location for the distribution center and its optimal storage capacity and a numerical example is presented to determine the computability of the results derived in this study .
