01592814

Component

https://doi.org/10.3141/2567-04

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.

01618747

16-2656

English

pp 28–37

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309441261

Print

Figures (3) ; References (35) ; Tables (2)

Bids; Combinatorial analysis; Less than truckload traffic; Logistics; Pricing; Stochastic programming

Data and Information Technology; Finance; Freight Transportation; Planning and Forecasting

TRIS, TRB, ATRI

Jan 12 2016 5:10PM

• Analysis of Advanced Management of Curbside Parking
• Data-Driven Prediction Methodology of Origin–Destination Demand in Large Network for Real-Time Service
• Deployment and Calibration Considerations for Large-Scale Regional Dynamic Traffic Assignment: Case Study for Sydney, Australia
• Dynamic Optimal Vehicle Relocation in Carshare Systems
• Genetic Algorithm–Based Routing Problem Considering the Travel Reliability Under Asymmetrical Travel Time Distributions
• Impact of Autonomous Vehicles on Traffic Management: Case of Dynamic Lane Reversal
• Implications of Cost Equity Consideration in Hazmat Network Design
• Modeling Freeway Work Zones with Mesoscopic Dynamic Traffic Simulator: Validation, Gaps, and Guidance
• Optimal Heterogeneous Sensor Deployment Strategy for Dynamic Origin–Destination Demand Estimation
• Parallel All-Pairs Shortest Path Algorithm: Network Decomposition Approach
• Path Finding in Stochastic Time Varying Networks with Spatial and Temporal Correlations for Heterogeneous Travelers
• Planning of Resource Replenishment Location for Service Trucks Under Network Congestion and Routing Constraints
• Solving Continuous Network Design Problem with Generalized Geometric Programming Approach
• Use of Concepts of Regret and Disappointment to Model Dynamic Route Choice Behavior Under Uncertainty