Dynamic Network for Air Freight Forwarder’s Stochastic Capacity Management
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Abstract
A freight forwarder, a key player in the air cargo service chain, collects individual packages from shippers and transports consolidated shipments to air carriers, some of which have long-term block space agreements with the forwarder. If, on any day, the total demand from the consolidated shipment exceeds the allotment specified in the block space agreement, the forwarder may need to purchase additional space in the spot market, where the freight rate is often higher. Alternatively, the forwarder may opt to delay some shipments, storing them overnight at a warehouse and incurring inventory holding costs. On the other hand, if the total demand is less than the allotment, the forwarder is required to pay at least the minimum charge. For each destination and each day of the week, demand exhibits significant week-to-week variation, while the capacity supply on each day of the week remains fixed over the contract duration. In the long-term problem, the forwarder must decide on the allotment before knowing the random daily demand. In the short-term problem, it determines how to allocate the realized demand to multiple carriers with different freight rates. The problem is formulated as a two-stage stochastic program, embedding the multi-day network of time-varying demand. The proposed solution is compared to the current approach in a case study, utilizing historical demand data from one of Thailand’s largest forwarders. Based on the top four destinations from April 2020 to July 2021, our proposed solution yields significant cost savings.
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