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This paper describes a two-phase simulation-based optimisation procedure that integrates the Genetic Algorithm and Response Surface-based Linear Search algorithm for developing optimal power-of-two replenishment policy in multi-echelon environment during the maturity phase of the life cycle of a product. The problem involves a search in high dimensional space with different ranges for decision variables scales, multiple objective functions and problem specific constraints, such as power-of-twodoi:10.1504/ijspm.2010.032654 fatcat:d4ruqviv3ncdpl5lwgzr6rtztq