A bidding advisory model for less-than-truckload combinatorial auctions with stochastic demand is proposed. The context of less-than-truckload combinatorial auctions is formulated and the first less-than-truckload bidding model is proposed; truckload models are improved by bidding with value-based pricing, volume segmentation, and uncertain demand and capacity. The less-than-truckload bidding model efficiently solves stochastic minimum-cost flow problems to construct profitable bids. Numerical experiments demonstrate its application and benefits.
Pricing and Segmentation of Stochastic Demand in Less-Than-Truckload Combinatorial Bids
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2567 , 1 ; 28-37
01.01.2016
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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