Survey on Ten Years of Multi-Depot Vehicle Routing Problems: Mathematical Models, Solution Methods and Real-Life Applications

A crucial practical issue encountered in logistics management is the circulation of final products from depots to end-user customers. When routing and scheduling systems are improved, they will not only improve customer satisfaction but also increase the capacity to serve a large number of customers minimizing time. On the assumption that there is only one depot, the key issue of distribution is generally identified and formulated as VRP standing for Vehicle Routing Problem. In case, a company having more than one depot, the suggested VRP is most unlikely to work out. In view of resolving this limitation and proposing alternatives, VRP with multiple depots and multi-depot MDVRP have been a focus of this paper. Carrying out a comprehensive analytical literature survey of past ten years on cost-effective Multi-Depot Vehicle Routing is the main aim of this research. Therefore, the current status of the MDVRP along with its future developments is reviewed at length in the paper

A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification

The growth of environmental awareness and more robust enforcement of numerous regulations to reduce greenhouse gas (GHG) emissions have directed efforts towards addressing current environmental challenges. Considering the Vehicle Routing Problem (VRP), one of the effective strategies to control greenhouse gas emissions is to convert the fossil fuel-powered fleet into Environmentally Friendly Vehicles (EFVs). Given the multitude of constraints and assumptions defined for different types of VRPs, as well as assumptions and operational constraints specific to each type of EFV, many variants of environmentally friendly VRPs (EF-VRP) have been introduced. In this paper, studies conducted on the subject of EF-VRP are reviewed, considering all the road transport EFV types and problem variants, and classifying and discussing with a single holistic vision. The aim of this paper is twofold. First, it determines a classification of EF-VRP studies based on different types of EFVs, i.e., Alternative-Fuel Vehicles (AFVs), Electric Vehicles (EVs) and Hybrid Vehicles (HVs). Second, it presents a comprehensive survey by considering each variant of the classification, technical constraints and solution methods arising in the literature. The results of this paper show that studies on EF-VRP are relatively novel and there is still room for large improvements in several areas. So, to determine future insights, for each classification of EF-VRP studies, the paper provides the literature gaps and future research needs

Planning of Truck Platoons: a Literature Review and Directions for Future Research

A truck platoon is a set of virtually linked trucks that drive closely behind one another using automated driving technology. Benefits of truck platooning include cost savings, reduced emissions, and more efficient utilization of road capacity. To fully reap these benefits in the initial phases requires careful planning of platoons based on trucks’ itineraries and time schedules. This paper provides a framework to classify various new transportation planning problems that arise in truck platooning, surveys relevant operations research models for these problems in the literature and identifies directions for future research

Road-based goods transportation : a survey of real-world logistics applications from 2000 to 2015

The vehicle routing problem has been widely studied from a technical point of view for more than 50 years. Many of its variants are rooted in practical settings. This paper provides a survey of the main real-life applications of road-based goods transportation over the past 15 years. It reviews papers in the areas of oil, gas and fuel transportation, retail, waste collection and management, mail and package delivery and food distribution. Some perspectives on future research and applications are discussed

Investigating the effect of carbon tax and carbon quota policy to achieve low carbon logistics operations

Developing a low-carbon economy and reducing carbon dioxide emission have become a consensus for both academics and practitioners. However, the existing literature did not pay enough attention in interrogating the impacts of Carbon Tax (CT) and Carbon Quota (CQ) policy on distribution costs and carbon dioxide emission in the field of vehicle routing problem. Moreover, the investigated subsidies factor is also incomplete. This research stands on the position of the company to study the impact of CT and CQ policy on aforementioned two aspects. A mathematical model is developed to achieve the best low carbon vehicle routing under the optimal policy. The optimization goal of this research is to minimize the total cost that includes vehicle-using, transportation, CT, CQ, and raw material subsidy costs. An improved optimization algorithm, namely Genetic Algorithm-Tabu Search (GA-TS), is proposed to solve a given business case. In the simulation experiments, GA-TS and a traditional GA are compared and the results show the advantage of GA-TS on reducing the total cost and carbon dioxide emission. Furthermore, the experiments also explore the total cost and carbon dioxide emission under three scenarios (Benchmark, CT and CQ), incorporating four policies: CT, Carbon Tax Subsidy (CTS), CQ, and Carbon Quota Subsidy (CQS). It is concluded that CQS is the ideal policy to minimize distribution cost and carbon dioxide emission. In addition, the impact of vehicles’ capacities on the total cost and carbon dioxide emission is also analyzed in this research. This research also aimed at assisting practitioners in better formulating delivery routes, as well as policy makers in developing carbon policies. Finally, the limitations and the future research directions of this research are also discussed

A hybrid GRASP-VNS for Ship Routing and Scheduling Problem with Discretized Time Windows

This paper addresses the Ship Routing and Scheduling Problem with Discretized Time Windows. Being one of the most relevant and challenging problems faced by decision makers from shipping companies, this tramp shipping problem lies in determining the set of contracts that should be served by each ship and the time windows that ships should use to serve each contract, with the aim of minimizing total costs. The use of discretized time windows allows for the consideration of a broad variety of features and practical constraints in a simple way. In order to solve this problem we propose a hybridazation of a Greedy Randomized Adaptive Search Procedure and a Variable Neighborhood Search, which improves previous heuristics results found in literature and requires very short computational time. Moreover, this algorithm is able to achieve the optimal results for many instances, demonstrating its good performance