Many real-life applications of the vehicle routing problem (VRP) occur in scenarios subject to
uncertainty or dynamic conditions. Thus, for instance, traveling times or customers' demands …

In this study, we present a deep reinforcement learning framework for solving scenario-
based two-stage stochastic programming problems. Stochastic programs have numerous …

One of the most applicable versions of the Vehicle Routing Problem (VRP) which has been
widely studied in logistic services is Capacitated Vehicle Routing Problem (CVRP). There …

We study the routing of Unmanned Aerial Vehicles (UAVs) in the presence of the risk of
enemy threats. The main goal is to find optimal routes that consider targets visited, threat …

A number of technological improvements have prompted a great concern on 'dynamism'in
vehicle routing problems (VRP). In real-world applications, the dynamic information happens …

Freight transportation is the backbone of urban economies and plays a critical role in the
smooth functioning of cities. As such, devising efficient methods for freight transportation …

Purpose As a critical problem in sophisticated distribution systems, vehicle routing plays a
pivotal role in dealing with time windows and capacities constraints. The purpose of this …

We present an optimization procedure based on a hybrid version of an evolutionary multi-
objective decision-making algorithm for its application in urban freight transportation …

This paper proposes a decomposition-based heuristic for a network delivery problem in
which relief workers acquire valuable emergency supplies from relief warehouses, and …

The application of graph theory can be used to solve distribution optimization problems,
especially the Vehicle Routing Problems (VRP). One variant of VRP is the Vehicle Routing …