Heuristics for dynamic and stochastic routing in industrial shipping

Authors:
Gregorio Tirado;Lars Magnus Hvattum;Kjetil Fagerholt;Jean-FrançOis Cordeau
Affiliations:
Universidad Complutense de Madrid, Spain;Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Norway;Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Norway and Norwegian Marine Technology Research Institute (MARINTEK), Norway;Canada Research Chair in Logistics and Transportation, HEC Montréal, Canada
Venue:
Computers and Operations Research
Year:
2013

Citing 13
Cited 0

Drive: Dynamic Routing of Independent Vehicles

Operations Research
Ship Routing and Scheduling: Status and Perspectives

Transportation Science
A computer-based decision support system for vessel fleet scheduling: experience and future research

Decision Support Systems
Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers

Operations Research
Solving a Dynamic and Stochastic Vehicle Routing Problem with a Sample Scenario Hedging Heuristic

Transportation Science
Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching

Transportation Science
A branch-and-regret heuristic for stochastic and dynamic vehicle routing problems

Networks
Waiting Strategies for Anticipating Service Requests from Known Customer Locations

Transportation Science
A Branch-and-Price-and-Cut Method for Ship Scheduling with Limited Risk

Transportation Science
Reoptimization Approaches for the Vehicle-Routing Problem with Stochastic Demands

Operations Research
Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports

Computers and Operations Research
Online traveling salesman problems with service flexibility

Networks
Development of a maritime transportation planning support system for car carriers based on genetic algorithm

Applied Intelligence

Quantified Score

Hi-index	0.01

Visualization

Abstract

Maritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing problems have been extensively studied in the last decades and can now be solved effectively with metaheuristics, many industrial applications are both dynamic and stochastic. In this spirit, this paper addresses a dynamic and stochastic maritime transportation problem arising in industrial shipping. Three heuristics adapted to this problem are considered and their performance in minimizing transportation costs is assessed. Extensive computational experiments show that the use of stochastic information within the proposed solution methods yields average cost savings of 2.5% on a set of realistic test instances.