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Abstract order batching in supply chains provides economic benefit, where it is beneficial economically for a company to produce large batches, since it can reduce the number of facility set-ups and improve manufacturing efficiency. However, rounding of orders to achieve a batch size is recognized as a source of the bullwhip effect problem within supply chains. Previous researches revealed that by choosing a batch size that is multiple of the average demand, order rates could be close to the actual demand, producing little demand amplification, thus bullwhip effect is reduced. This thesis considers a supply chain consisting of a supplier feeding more than one retailer in batches to cover demand for a number of future time units. Stochastic demand and price are described by a first order autoregressive AR(1) time series process. Aggregate bullwhip effect resulting from the synergistic effect between retailers demand is considered depending on demand and price parameters of the retailers along with the number of forecasting time units. Optimum batch size is selected based on the minimum mean square error (MMSE) demand forecasting method, such that aggregate bullwhip effect is less than the sum of separate bullwhip effect for each retailer. Keywords: Bullwhip effect BWE, order batching, demand forecasting, separate bullwhip effect, aggregate bullwhip effect. |