@inproceedings{85e7884a4ae14d839d90c3dbb1b31b7e,
title = "Pickup and delivery problem with transshipment for inland waterway transport",
abstract = "Inland waterway transport is becoming attractive due to its minimum environmental impact in comparison with other transportation modes. Fixed timetables and routes are adopted by most barge operators, avoiding the full utilization of the available resources. Therefore a flexible model is adopted to reduce the transportation cost and environmental impacts. This paper regards the route optimization of barges as a pickup and delivery problem (PDP). A Mixed Integer Programming (MIP) model is proposed to formulate the PDP with transshipment of barges, and an Adaptive Large Neighborhood Search (ALNS) is developed to solve the problem efficiently. The approach is evaluated based on a case study in the Rhine Alpine corridor and it is shown that ALNS is able to find good solutions in reasonable computation times. The results show that the cost is lower when there is more flexibility. Moreover, the cost comparison shows that transshipment terminals can reduce the cost for barge companies.",
keywords = "Adaptive large neighborhood search, Inland waterway transport, Pickup and delivery problem, Transshipment",
author = "Yimeng Zhang and Bilge Atasoy and Dimitris Souravlias and Negenborn, {Rudy R.}",
year = "2020",
doi = "10.1007/978-3-030-59747-4_2",
language = "English",
isbn = "978-3-030-59746-7",
series = "Lecture Notes in Computer Science ",
publisher = "Springer",
pages = "18--35",
editor = "Eduardo Lalla-Ruiz and Martijn Mes and Stefan Vo{\ss}",
booktitle = "Computational Logistics",
note = "11th International Conference on Computational Logistics, ICCL 2020 ; Conference date: 28-09-2020 Through 30-09-2020",
}