Q: order quantity · R: reorder point
Inventory control must balance two kinds of failure: holding too much stock for too long and running out while customers are still buying. A reorder policy simplifies the repeated decision by specifying when to place an order and how much to request.
The introduction follows a warehouse through delivery, sales, depletion, and replenishment. Later acts vary the reorder trigger and the order size, showing how each choice changes delivery frequency, average stock, and shortage risk. Ordering too late exposes the system to demand during the replenishment delay; ordering too much ties up space and capital. The final comparison searches for a good policy for the particular simulated demand and cost assumptions. Its insight is a balance rather than a universally best number. The policy is useful because it converts a complex stream of daily decisions into a rule that can be monitored and adjusted as demand and supply conditions change.
Customer purchases may change only slightly, yet orders sent farther up a supply chain can swing dramatically. The bullwhip effect describes this amplification. Each organization sees orders from its immediate customer rather than the final consumer, and each tries to protect itself against shortages, delivery delays, and uncertain future demand.
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Cities already contain many passenger trips while delivery fleets drive additional routes to serve parcels. Crowdsourced delivery asks whether some parcels can travel on trips that were going to happen anyway, reducing the work assigned to dedicated vehicles.
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A factory may have enough total capacity and still fail to satisfy orders. If one production line is assigned only to a product whose demand is falling, that line can sit idle while another line is overwhelmed by a product whose demand is rising. This is a mismatch of capability, not necessarily a shortage of machines.
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