Decision-focused learning (DFL) is an emerging paradigm that integrates machine learning
(ML) and constrained optimization to enhance decision quality by training ML models in an …

A number of technological advances have led to a renewed interest in dynamic vehicle
routing problems. This survey classifies routing problems from the perspective of information …

Online vehicle routing is an important task of the modern transportation service provider.
Contributed by the ever-increasing real-time demand on the transportation system …

With the rapid development of logistics industry, vehicle scheduling is the key to the
optimization of transportation links. Vehicle transportation route planning is becoming more …

Research on dynamic and stochastic vehicle routing problems received increasing interest
in the last decade. It considers a novel problem class, aiming at an appropriate handling of …

This paper surveys the vehicle routing problems met in cities for good distribution. It applies
the following methodology. First, it gives an overview of the literature devoted to vehicle …

This paper presents a methodology for classifying the literature of the Vehicle Routing
Problem (VRP). VRP as a field of study and practice is defined quite broadly. It is considered …

Lately, the Vehicle Routing Problem (VRP) in the city, known as City VRP, has gained
popularity with its importance in city logistics. Similar to city logistics, City VRP mainly differs …

This paper examines the use of deep recurrent neural networks to classify traffic patterns in
smart cities. We propose a novel approach to traffic pattern classification based on deep …

Abstract An Online Vehicle Routing Problem is a formation of Capacitated Vehicle Routing
Problem with re-routing strategy to resolve the problem of inefficient vehicle routing caused …