Online Multimodal Transportation Planning using Deep Reinforcement Learning

05/18/2021
by   Amirreza Farahani, et al.
0

In this paper we propose a Deep Reinforcement Learning approach to solve a multimodal transportation planning problem, in which containers must be assigned to a truck or to trains that will transport them to their destination. While traditional planning methods work "offline" (i.e., they take decisions for a batch of containers before the transportation starts), the proposed approach is "online", in that it can take decisions for individual containers, while transportation is being executed. Planning transportation online helps to effectively respond to unforeseen events that may affect the original transportation plan, thus supporting companies in lowering transportation costs. We implemented different container selection heuristics within the proposed Deep Reinforcement Learning algorithm and we evaluated its performance for each heuristic using data that simulate a realistic scenario, designed on the basis of a real case study at a logistics company. The experimental results revealed that the proposed method was able to learn effective patterns of container assignment. It outperformed tested competitors in terms of total transportation costs and utilization of train capacity by 20.48 the cost and by 7.51 results within 2.7 solution generated by an Integer Linear Programming solver in an offline setting.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 6

page 7

06/14/2018

Deep Reinforcement Learning for Dynamic Urban Transportation Problems

We explore the use of deep learning and deep reinforcement learning for ...
06/24/2020

Deep Reinforcement Learning for Joint Beamwidth and Power Optimization in mmWave Systems

This paper studies the joint beamwidth and transmit power optimization p...
10/26/2021

The Difficulty of Passive Learning in Deep Reinforcement Learning

Learning to act from observational data without active environmental int...
02/08/2020

RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning

This paper presents a deep reinforcement learning algorithm for online a...
10/11/2018

A Resource Allocation based Approach for Corporate Mobility as a Service

Corporate mobility is often based on fixed assignments of vehicles to em...
03/16/2021

Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design

This paper develops a hierarchical reinforcement learning architecture f...
06/25/2020

Mobility operator resource-pooling contract design to hedge against network disruptions

Public transportation delays due to systematic failures have a major imp...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.