scholarly journals Multi-Depot Green Vehicle Routing Problem to Minimize Carbon Emissions

2020 ◽  
Vol 12 (8) ◽  
pp. 3500 ◽  
Author(s):  
Weiheng Zhang ◽  
Yuvraj Gajpal ◽  
Srimantoorao. S. Appadoo ◽  
Qi Wei
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Optimization Problem ◽  
Alternative Fuel ◽  
Total Carbon ◽  
Ant Colony System ◽  
Routing Problem ◽  
Acceptable Solution ◽  
Time Optimization

A Multi-Depot Green Vehicle Routing Problem (MDGVRP) is considered in this paper. In MDGVRP, Alternative Fuel-powered Vehicles (AFVs) start from different depots, serve customers, and, at the end, return to the original depots. The limited fuel tank capacity of AFVs forces them to visit Alternative Fuel Stations (AFS) for refueling. The objective is to minimize the total carbon emissions. A Two-stage Ant Colony System (TSACS) is proposed to find a feasible and acceptable solution for this NP-hard (Non-deterministic polynomial-time) optimization problem. The distinct characteristic of the proposed TSACS is the use of two distinct types of ants for two different purposes. The first type of ant is used to assign customers to depots, while the second type of ant is used to find the routes. The solution for the MDGVRP is useful and beneficial for companies that employ AFVs to deal with the various inconveniences brought by the limited number of AFSs. The numerical experiments confirm the effectiveness of the proposed algorithms in this research.

scholarly journals Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions

2020 ◽  
Vol 12 (24) ◽  
pp. 10537
Author(s):  
Jin Li ◽  
Feng Wang ◽  
Yu He
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Hill Climbing ◽  
Neighborhood Search ◽  
Battery Life ◽  
Routing Problem ◽  
Crossover And Mutation

In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the energy consumption and carbon emissions of electric vehicles. Second, we propose a mixed integer programming model to minimize the total costs related to electric vehicle energy consumption and travel time. To solve this model efficiently, we develop an adaptive genetic algorithm based on hill climbing optimization and neighborhood search. The crossover and mutation probabilities are designed to adaptively adjust with the change of population fitness. The hill climbing search is used to enhance the local search ability of the algorithm. In order to satisfy the constraints of battery life and battery swapping stations, the neighborhood search strategy is applied to obtain the final optimal feasible solution. Finally, we conduct numerical experiments to test the performance of the algorithm. Computational results illustrate that a routing arrangement that accounts for power consumption and travel time can reduce carbon emissions and total logistics delivery costs. Moreover, we demonstrate the effect of adaptive crossover and mutation probabilities on the optimal solution.

scholarly journals A Model for Sustainable Courier Services: Vehicle Routing with Exclusive Lanes

2020 ◽  
Vol 12 (3) ◽  
pp. 1077
Author(s):  
Keyju Lee ◽  
Junjae Chae ◽  
Bomi Song ◽  
Donghyun Choi
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Southeast Asian ◽  
Routing Problem ◽  
Heterogeneous Fleet ◽  
Proposed Model ◽  
Asian Cities

In Southeast Asian cities, it is common for logistic companies to operate a heterogeneous fleet of delivery vehicles with motorcycles being the preferred vehicle to handle the final phase of delivery. In such scenarios, heterogeneous fleet vehicle routing problem (HFVRP) is generally applied to plan an optimal delivery. However, in many downtown cores of large and rapidly developing Southeast Asian cities, HFVRP is neither viable nor reliable because of road usage restrictions. The purpose of this article is to develop and test a different approach that accurately takes these restrictions into account and provides viable and more sustainable results. Restrictions in this paper refer to situations of urban areas in Vietnam where (i) certain vehicle types are prohibited in specified areas or where narrow alleyways limit the utilization of vehicles that exceed the road capacity and (ii) certain roads are exclusive to certain vehicle types. In networks, limited access and exclusive lanes are represented as links, or arcs, exclusive to one or another. Taking these limitations into consideration, we have developed a unique model, which we have termed Vehicle Routing Problem with Exclusive Links (VRP-EL). The model was validated and tested for its performance on scenarios with varying ratios of exclusive links. Scenarios up to 500 customers were tested on a meta-heuristic algorithm, simulated annealing. VRP-EL produces realistic outcomes. Limiting certain links to be selected according to vehicle types increases overall travel distance. However, this increase outweighs the cost of re-planning and rerouting had they not been constrained initially. The reduction in traveling distance leads to fossil fuel reduction for the overall system. The estimation of reduced carbon emissions through applying the proposed model is presented. Considering the severe traffic congestion and carbon emissions caused by motorcycles in Vietnam, the proposed model leads to a sustainable road environment.

scholarly journals Optimization of a Capacitated Vehicle Routing Problem for Sustainable Municipal Solid Waste Collection Management Using the PSO-TS Algorithm

2020 ◽  
Vol 17 (6) ◽  
pp. 2163 ◽  
Author(s):  
Qingqing Qiao ◽  
Fengming Tao ◽  
Hailin Wu ◽  
Xuewei Yu ◽  
Mengjun Zhang
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Social Benefits ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Penalty Costs ◽  
Capacitated Vehicle

Sustainable management of municipal solid waste (MSW) collection has been of increasing concern in terms of its economic, environmental, and social impacts in recent years. Current literature frequently studies economic and environmental dimensions, but rarely focuses on social aspects, let alone an analysis of the combination of the three abovementioned aspects. This paper considers the three benefits simultaneously, aiming at facilitating decision-making for a comprehensive solution to the capacitated vehicle routing problem in the MSW collection system, where the number and location of vehicles, depots, and disposal facilities are predetermined beforehand. Besides the traditional concerns of economic costs, this paper considers environmental issues correlated to the carbon emissions generated from burning fossil fuels, and evaluates social benefits by penalty costs which are derived from imbalanced trip assignments for disposal facilities. Then, the optimization model is proposed to minimize system costs composed of fixed costs of vehicles, fuel consumption costs, carbon emissions costs, and penalty costs. Two meta-heuristic algorithms, particle swarm optimization (PSO) and tabu search (TS), are adopted for a two-phase algorithm to obtain an efficient solution for the proposed model. A balanced solution is acquired and the results suggest a compromise between economic, environmental, and social benefits.

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