Abstract
End distribution has always been an obstacle in logistics operations. This paper finds that intelligent logistics can have the functions of visualization, prediction, control and decision-making through the rational use of big data and artificial intelligence technologies. At the same time, this paper combines the sustainable development concept of green logistics to further study the green vehicle routing problem based on traffic flow. Intelligent logistics systems help control costs, improve energy efficiency, reduce carbon emissions, and improve customer satisfaction.
Highlights
Sustainable development has become one of the key topics in today’s world, and the pursuit of a green economy plays an important role in building a sustainable planet [1]–[2]
(2) The advantage of smart logistics lies in their flexibility, as they can accommodate the concept of green logistics and build a new modern logistics system
Based on the perspective of smart logistics, this paper further considers the customer satisfaction cost based on the time window from the perspective of practice
Summary
Sustainable development has become one of the key topics in today’s world, and the pursuit of a green economy plays an important role in building a sustainable planet [1]–[2]. The increase in customer demands, the complexity of the traffic situation, information asymmetry and cost uncontrollability are important obstacles affecting logistics distribution. With the use of visualization technology, through the realtime monitoring of vehicle and environmental information, smart logistics can effectively predict emergencies, which may occur at any time, and provide guidance for the supply centre in making timely response decisions. In response to an uncontrollable environment, smart logistics can reduce uncontrollable costs and improve distribution efficiency by rationally controlling vehicles. This paper extends such thinking to logistics and distribution This adaptive system has three primary aspects: (1) it recognizes the interactions among different constraints, (2) it makes rational vehicle routing decisions, and (3) it predicts and avoids subsequent financial losses. This paper studies how smart logistics systems can help managers make decisions under complex traffic conditions to reduce costs, carbon emissions and fuel consumption and improve customer satisfaction
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