Fleet design optimisation from historical data using constraint programming and large neighbourhood search

DOI10.1007/S10601-015-9203-0zbMath1334.90085OpenAlexW1137265463MaRDI QIDQ265693

Philip Kilby, Tommaso Urli

Publication date: 12 April 2016

Published in: Constraints (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10601-015-9203-0

zbMATH Keywords

mixed integer programmingvehicle routing problemconstraint programmingpre-processingfleet size and mixlarge neighbourhood search

Mathematics Subject Classification ID

Mixed integer programming (90C11) Transportation, logistics and supply chain management (90B06)

Related Items (3)

A concise guide to existing and emerging vehicle routing problem variants ⋮ A column‐generation‐based approach to fleet design problems mixing owned and hired vehicles ⋮ Multimodal processes prototyping subject to grid-like network and fuzzy operation time constraints

Uses Software

• Gurobi
• VRP
• Gecode
• SPOT
• json2run

Cites Work

• Unnamed Item
• Balancing bike sharing systems with constraint programming
• An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
• Handbook of transportation science.
• A unified solution framework for multi-attribute vehicle routing problems
• The Vehicle Routing Problem
• Split delivery routing
• The Split Delivery Vehicle Routing Problem: A Survey
• Savings by Split Delivery Routing

This page was built for publication: Fleet design optimisation from historical data using constraint programming and large neighbourhood search