Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Abstract This paper presents the first results of an agent-based model aimed at solving a Capacitated Vehicle Routing Problem (CVRP) for inbound logistics using a novel Ant Colony Optimization (ACO) algorithm, developed and implemented in the NetLogo multi-agent modelling environment. The proposed m...

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Bibliographic Details
Main Authors: Giovanni Calabrò, Vincenza Torrisi, Giuseppe Inturri, Matteo Ignaccolo
Format: Article
Language:English
Published: SpringerOpen 2020-04-01
Series:European Transport Research Review
Subjects:
Ant Colony optimization
Vehicle routing problem
Multi-agent simulation, logistics
Online Access:http://link.springer.com/article/10.1186/s12544-020-00409-7

Internet

http://link.springer.com/article/10.1186/s12544-020-00409-7

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