Coordinating Spot and Contract Supply in Freight Marketplaces

2026-03-25

AI Summary

This study addresses the joint procurement optimization of long-term contracted capacity and short-term spot capacity in freight markets, aiming to minimize total procurement costs. It introduces a novel formulation that couples contract allocation with spot pricing—a first in the literature—and proposes an efficient solution method based on the dual Frank-Wolfe algorithm. The approach dynamically coordinates the two capacity types via shadow prices and requires only black-box access to spot pricing mechanisms, ensuring both scalability and modular design. Empirical validation on semi-synthetic data from a large digital freight platform demonstrates that the proposed method reduces procurement costs by approximately 10% compared to prevailing benchmarks, while maintaining low relative regret and high computational efficiency.

Technology Category

• Search and Optimization: Algorithm Configuration
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

The freight industry is undergoing a digital revolution, with an ever-growing volume of transactions being facilitated by digital marketplaces. A core capability of these marketplaces is the fulfillment of demand for truckload movements (loads) by procuring the services of carriers who execute them. Notably, these services are procured both through long-term contracts, where carriers commit capacity to execute loads (e.g., contracted fleet of drivers or lane-level commitments), and through short-term spot marketplaces, where carriers can agree to move individual loads for the offered price. This naturally couples two canonical problems of the transportation industry: contract assignment and spot pricing. In this work, we model and analyze the problem of coordinating long-term contract supply and short-term spot supply to minimize total procurement costs. We develop a Dual Frank Wolfe algorithm to compute shadow prices which allow the spot pricing policy to account for the committed contract capacity. We show that our algorithm achieves small relative regret against the optimal -- but intractable -- dynamic programming benchmark when the size of the market is large. Importantly, our Dual Frank Wolfe algorithm is computationally efficient, modular, and only requires oracle access to spot-pricing protocols, making it ideal for large-scale markets. Finally, we evaluate our algorithm on semi-synthetic data from a major Digital Freight Marketplace, and find that it yields significant savings ($\approx 10\%$) compared to a popular status-quo method.

Problem

• freight marketplace
• contract supply
• spot pricing
• supply coordination
• procurement cost

Innovation

• Dual Frank Wolfe algorithm
• freight marketplace coordination
• contract and spot supply integration
• shadow pricing
• computational efficiency