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Increasing competition in the market generally leads to affect the fluctuation in the product’s demand. Such fluctuations pose a serious concern for the decision maker at each stage of the supply chain. Moreover, the capacity constraint at any level of the supply chain would make the situation more critical by elevating the Bullwhip Effect. The present article introduces a new algorithm i.e. “Iterative Proportional Algorithm (IPA)” under above mentioned situation, which instead of elevating, discourages the bullwhip effect. A comparative analysis of the proposed algorithm with the policies defined in [6] has been provided to explain the bottlenecks of existing policies.  It has been established numerically, that application of IPA is beneficial for both retailers as well as supplier, as the combined profit (loss) of all the retailers increases (decreases) and subsequently minimizes the bull whip effect of the supplier. We have incorporated the concept of Product Fill Rate (PFR) through which it is shown that IPA gives better results as compared to other allocation mechanisms.

Quantitative analysis for measuring and suppressing bullwhip effect