Training a machine to automate spot pricing of logistics services in a large-scale network

US10332032B2 · kind B2 · utility

Assignee

• International Business Machines Corporation · US

Inventors

• Pawan R. Chowdhary · San Jose, US
• Markus Ettl · Ossining, US
• Roger D. Lederman · Ossining, US
• Tim Nonner · Zürich, CH
• Ulrich B. Schimpel · Nuremberg, DE
• Zhengliang Xue · Yorktown Heights, US
• Hongxia Yang · Beijing, CN

Key dates

• Filing date: Nov 1, 2016
• Grant date: Jun 25, 2019
• Expiry date: Nov 1, 2036

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/02
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.