Over the years, most or many companies have focused their attention to the effectiveness and efficiency of their business units. As a new way of doing business, these companies have begun to realize the strategic importance of planning, controlling, and designing their own supply chain system. This paper analyzes the coordination issues in supply chains that consist of one manufacturer and multiple retailers operating under uncertain end customer demand and delivery lead-time. We use the Genetic Algorithm (GA) to determine the appropriate ordering and inventory level at which the manufacturer and multiple retailers can maximize the profit of the chain. This is performed under three controlling policies: the traditionally centralized controlling policy under the manufacturer's perspective, the entire chain’s perspective, and lastly the coordinating controlling policy with an incentive scheme. The outcome from the study reveals that the coordinating controlling policy with an incentive scheme can outperform the traditional centralized controlling policies by creating a win-win situation in which all members of the chain benefit from higher profit, thus resulting in more willingness from all members to join the chain.
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