To solve the low-carbon vehicle routing problem (VRP) with sustainable development background, VRP considering impact of speed on carbon emissions is studied. A optimization model aims to minimize total cost distribution, penalty and emission cost. In model, driving time are calculated basis varying matching real road network. Moreover, improved genetic algorithm applied optimize in this paper....

The VRP’s main objective is to obtain the lowest-cost set of routes to deliver demand to customers, but we can also think about reducing the cardinality of the set of routes. In addition, we can contemplate other objectives like the makespan, workload balance, and some others [10]. This means that we can consider VRP as a multi-objective problem. Moreover, VRP has several variants of increased ...

Distribution is a substantial cost in many companies and in some sectors it contributes a high percentage of the value added to goods. Therefore the potential for savings is large, and there is much interest in improving distribution eeciency. The Vehicle Routing Problem (vrp) is an abstraction of a class of problems that has been studied both as a theoretical problem and for its practical rele...

This paper introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non–Gaussian Ornstein–Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented. Further we study the effect of the SVV on the leverage effect and on the presence of long memory. One of the key results ...

In the Vehicle Routing Problem (VRP), the aim is to design a set of m minimum cost vehicle routes through n customer locations, so that each route starts and ends at a common location and some side constraints are satisfied. Common application arise in newspaper and food delivery, and in milk collection. This paper summarizes the main known results for the classical VRP in which only vehicle ca...

The ship routing problem (SRP) is a special variant of the classical vehicle routing problems (VRPs), which is different from both the VRP with backhauls (VRPB) and the VRP with pickup and delivery (VRPPD). This paper proposes a new immune genetic algorithm for the large scale SRP. The backhaul and time window constraints are also considered. The immune GA is innovated based on the classic GA a...

Providing safe transportation for Hazardous Materials (Hazmat) is a concern that attracts a wide range of resaerchers. Different types of problems have been defined in the literature in order to cope as much as possible with real situations. Most of existing studies consider the transportation between two points, while few of them considered resolving the Vehicle Routing Problem (VRP) in the co...

To solve the problem of easily trapped into local optimization and instable calculation results, a new fine-adjustment mechanism-based particle swarm optimized algorithm applicable to solution seeking of VRP model is presented in this paper. This algorithm introduces the fine-adjustment mechanism so as to get adapt to the judgment base of function directional derivative value. By adjusting the ...

We consider the vehicle routing problem with stochastic demands (VRPSD). We give randomized approximation algorithms achieving approximation guarantees of 1 + for split-delivery VRPSD, and 2 + for unsplit-delivery VRPSD; here  is the best approximation guarantee for the traveling salesman problem. These bounds match the best known for even the respective deterministic problems [Altinkemer, K...