Freight transportation broker agent based on constraint logic programming

We propose an agent-based freight brokering system that provides an intelligent logistics brokerage service focusing on the transport activity for the efficient allocation of transport resources (vehicles or trucks) to the transport applications. The freight broker has the role to coordinate transpo...

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Bibliographic Details
Published in:Evolving systems Vol. 11; no. 3; pp. 363 - 382
Main Authors: Bǎdicǎ, Costin, Leon, Florin, Bǎdicǎ, Amelia
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020
Subjects:
Artificial Intelligence
Complex Systems
Complexity
Engineering
Original Paper
Constraint logic programming
Search and optimization
Pickup and delivery problem
Intelligent agent
ISSN:1868-6478, 1868-6486
Online Access:Get full text
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Summary:We propose an agent-based freight brokering system that provides an intelligent logistics brokerage service focusing on the transport activity for the efficient allocation of transport resources (vehicles or trucks) to the transport applications. The freight broker has the role to coordinate transportation arrangements of transport customers with transport resource providers. In this paper we focus on the fundamental function of this business that aims to find available trucks and to define their feasible routes for transporting requested customer loads. Our main achievement is the proposal of a knowledge-based freight broker based on agents and constraint programming. We describe the multi-agent architecture and the interaction protocol of the freight broker. The brokering function is defined as a special type of vehicle routing with pickup and delivery problem. This function is achieved by proposing an optimization agent based on constraint logic programming. We present in detail our novel declarative optimization model, as well as the components of the optimization agent. This model was implemented and evaluated using the state-of-the-art ECLiPSe-CLP engine. The experimental results that we obtained for sample benchmark problems are promising and they support the effectiveness of our approach in a practical setting.
ISSN:1868-6478
1868-6486
DOI:10.1007/s12530-018-9230-3