2014/08/29 by A. Zidi, Amir Zidi, Zidi, Amir +6
Agricultural and Biological Sciences · Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Data Management and Algorithms #FOS: Computer and information sciences #Food Supply Chain Traceability #Urban and Freight Transport Logistics #cs.AI
paper · pdf · doi:10.48550/arxiv.1409.0069
openalex publication_date 2014/08/29 · arxiv created 2014/08/30 · arxiv updated 2014/09/02 · openalex created_date 2025/10/27 · openalex updated_date 2026/07/28
There is a relatively small amount of research covering urban freight movements. Most research dealing with the subject of urban mobility focuses on passenger vehicles, not commercial vehicles hauling freight. However, in many ways, urban freight transport contributes to congestion, air pollution, noise, accident and more fuel consumption which raises logistic costs, and hence the price of products. The main focus of this paper is to propose a new solution for congestion in order to improve the distribution process of goods in urban areas and optimize transportation cost, time of delivery, fuel consumption, and environmental impact, while guaranteeing the safety of goods and passengers. A novel technique for personalization in itinerary search based on city logistics ontology and rules is proposed to overcome this problem. The integration of personalization plays a key role in capturing or inferring the needs of each stakeholder (user), and then satisfying these needs in a given context. The proposed approach is implemented to an itinerary search problem for freight transportation in urban areas to demonstrate its ability in facilitating intelligent decision support by retrieving the best itinerary that satisfies the most users preferences (stakeholders).