scholarly journals Routing Optimization for Shared Electric Vehicles with Ride-Sharing

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Chuanxiang Ren ◽  
Jinbo Wang ◽  
Yongquan You ◽  
Yu Zhang
Keyword(s):  
Electric Vehicles ◽  
Optimization Model ◽  
Operation Mode ◽  
Utilization Rate ◽  
Total Cost ◽  
Routing Optimization ◽  
Ride Sharing ◽  
Proposed Model ◽  
Demand Information ◽  
User Demand

Shared electric vehicles (SEVs) are becoming a new way for urban residents to travel because of their environmental protection, energy saving, and sustainable development. However, at present, the operation mode of shared electric vehicles has the problem that the vehicle cannot be utilized efficiently. For this reason, this paper studied the mode of SEVs with ride-sharing (MSEVRS) and SEVs routing optimization under this mode. Firstly, the operation principle of MSEVRS is presented, which includes the collection of user demand information and SEVs information and the routing optimization of SEVs, both of which are completed by the user and SEVs management center. Secondly, the routing optimization model of SEVs with ride-sharing is proposed, in which the SEVs operation cost, user time cost, user rental cost, and user ride-sharing bonus are taken into account. And the genetic algorithm is designed to solve the model. Finally, a case study is carried out to illustrate the effectiveness of the proposed model. The results show that the proposed routing optimization model achieves the optimal SEVs route, realizes the MSEVRS, and improves the utilization rate of SEVs. Compared with the current SEVs mode (CSEVM), the MSEVRS reduces the number of vehicles, user rental cost, the total cost of users, and the total cost of user and company of SEVs. And the total distance is reduced, which means saving energy. Moreover, it shows that MSEVRS obtains a better cost performance and service for users and has a better application prospect.

scholarly journals Optimization Model and Algorithm of Empty Pallets Dispatching under the Time-Space Network of Express Shipment

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Kang Zhou ◽  
Shiwei He ◽  
Rui Song ◽  
Xiaole Guo ◽  
Kaiming Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Clonal Selection ◽  
Transportation Cost ◽  
Transport Cost ◽  
Utilization Rate ◽  
Time Requirement ◽  
Total Cost ◽  
Time Space ◽  
The Cost

Relying on the express freight network, the dispatching of empty pallets based on the pallet pool mode is studied to reuse pallets with the minimum transport cost, enhance the pallet utilization rate, reduce the waste of resources, and save the cost of logistics. Considering the influence of transport efficiency for different modes in transportation process, differences of transportation cost, carbon emissions, and transportation timeliness of demand points required, an optimization model is constructed. The objective of the model is to minimize the total cost including transportation cost, inventory cost, lease cost, and loss cost. According to the structural characteristics of the model, genetic algorithm and improved cloud clonal selection operation is used to solve the model. Finally, the validity and rationality of the optimization model are verified by a case study. The result shows that the total dispatching cost of considering time requirement is 1.8 times the cost without considering the time requirement, respectively, both less than the total cost of pallets leasing. Moreover, when there are 3 supply points and 2 demand points and the number of iterations is 100, after the algorithms are run for 30 times, the worst values are 9305 and 8317 for genetic algorithm and the improved cloud clonal selection operation, respectively. Therefore, the efficiency of the improved cloud clonal selection operation is higher than genetic algorithm.

scholarly journals Allocating Freight Empty Cars in Railway Networks with Dynamic Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ce Zhao ◽  
Lixing Yang ◽  
Shukai Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Transportation Cost ◽  
Allocation Problem ◽  
Total Cost ◽  
Storage Cost ◽  
Proposed Model ◽  
Railway Networks

This paper investigates the freight empty cars allocation problem in railway networks with dynamic demands, in which the storage cost, unit transportation cost, and demand in each stage are taken into consideration. Under the constraints of capacity and demand, a stage-based optimization model for allocating freight empty cars in railway networks is formulated. The objective of this model is to minimize the total cost incurred by transferring and storing empty cars in different stages. Moreover, a genetic algorithm is designed to obtain the optimal empty cars distribution strategies in railway networks. Finally, numerical experiments are given to show the effectiveness of the proposed model and algorithm.

Routing Optimization of City Distribution Considering Access Restriction

2014 ◽  
Vol 505-506 ◽  
pp. 959-966 ◽  
Author(s):  
Xin Jin ◽  
Yang Tang ◽  
Qi Xu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Benchmark Problems ◽  
Local Authorities ◽  
Urban Freight ◽  
Routing Optimization ◽  
Proposed Model ◽  
Urban Freight Transport ◽  
Negative Impacts

Nowadays, urban freight transport has become one of the most significant contributors to congestion and pollution. To combat these negative impacts, local authorities implement some restrictive regulations imposed on logistic enterprises about the time and area to which their vehicles can access. Under this circumstance, this paper constructed a city distribution routing optimization model considering access restriction. A Genetic Algorithm was proposed to solve the model. Numerical experiments based on the Solomons benchmark problems proved the effectiveness of the proposed model and algorithms.

scholarly journals A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 253-270
Author(s):  
Mohammed Bin Hariz ◽  
Dhaou Said ◽  
Hussein T. Mouftah
Keyword(s):  
Data Exchange ◽  
Smart Cities ◽  
Time Data ◽  
School Bus ◽  
The Public ◽  
Ride Sharing ◽  
Dynamic Mobility ◽  
Proposed Model ◽  
Loading System ◽  
Suitable Combination

This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.

scholarly journals A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4636
Author(s):  
Mohammed Elhenawy ◽  
Mostafizur R. Komol ◽  
Mahmoud Masoud ◽  
Shiqiang Liu ◽  
Huthaifa I. Ashqar ◽  
...  
Keyword(s):  
User Needs ◽  
Computational Results ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Ride Sharing ◽  
Proposed Model ◽  
Micro Mobility

Substantial research is required to ensure that micro-mobility ride sharing provides a better fulfilment of user needs. This study proposes a novel crowdsourcing model for the ride-sharing system where light vehicles such as scooters and bikes are crowdsourced. The proposed model is expected to solve the problem of charging and maintaining a large number of light vehicles where these efforts will be the responsibility of the crowd of suppliers. The proposed model consists of three entities: suppliers, customers, and a management party responsible for receiving, renting, booking, and demand matching with offered resources. It can allow suppliers to define the location of their private e-scooters/e-bikes and the period of time they are available for rent. Using a dataset of over 9 million e-scooter trips in Austin, Texas, we ran an agent-based simulation six times using three maximum battery ranges (i.e., 35, 45, and 60 km) and different numbers of e-scooters (e.g., 50 and 100) at each origin. Computational results show that the proposed model is promising and might be advantageous to shift the charging and maintenance efforts to a crowd of suppliers.

Shared Autonomous Vehicle System Design for Battery Electric Vehicle (BEV) and Fuel Cell Electric Vehicle (FCEV)

2021 ◽  
Author(s):  
Ungki Lee ◽  
Sunghyun Jeon ◽  
Ikjin Lee
Keyword(s):  
Fuel Cell ◽  
System Design ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Proton Exchange ◽  
Battery Electric Vehicle ◽  
Test Bed ◽  
Alternative Fuel Vehicles ◽  
Total Cost ◽  
Fuel Cell Electric Vehicle

Abstract Shared autonomous vehicles (SAVs) encompassing autonomous driving technology and car-sharing service are expected to become an essential part of transportation system in the near future. Although many studies related to SAV system design and optimization have been conducted, most of them are focused on shared autonomous battery electric vehicle (SABEV) systems, which employ battery electric vehicles (BEVs) as SAVs. As fuel cell electric vehicles (FCEVs) emerge as alternative fuel vehicles along with BEVs, the need for research on shared autonomous fuel cell electric vehicle (SAFCEV) systems employing FCEVs as SAVs is increasing. Therefore, this study newly presents a design framework of SAFCEV system by developing an SAFCEV design model based on a proton-exchange membrane fuel cell (PEMFC) model. The test bed for SAV system design is Seoul, and optimization is conducted for SABEV and SAFCEV systems to minimize the total cost while satisfying the customer wait time constraint, and the optimization results of both systems are compared. From the results, it is verified that the SAFCEV system is feasible and the total cost of the SAFCEV system is even lower compared to the SABEV system. In addition, several observations on various operating environments of SABEV and SAFCEV systems are obtained from parametric studies.

scholarly journals Energy Trading with Electric Vehicles in Smart Campus Parking Lots

2018 ◽  
Vol 8 (10) ◽  
pp. 1749 ◽  
Author(s):  
Mohamed Ahmed ◽  
Young-Chon Kim
Keyword(s):  
Electric Vehicles ◽  
Market Mechanism ◽  
University Campus ◽  
Energy Trading ◽  
Control Center ◽  
Parking Lots ◽  
Electric Vehicle Charging ◽  
Parking Lot ◽  
Demand Information ◽  
Knapsack Algorithm

Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking lots where electric vehicles are able to exchange energy through buying and selling prices. The proposed architecture consists of four layers: the parking energy layer, data acquisition layer, communication network layer, and market layer. Electric vehicles are classified into three different types: seller electric vehicles (SEVs) with an excess of energy in the battery, buyer electric vehicles (BEVs) with lack of energy in the battery, and idle electric vehicles (IEVs). The parking lot control center (PLCC) plays a major role in collecting all available offer/demand information among parked electric vehicles. We propose a market mechanism based on the Knapsack Algorithm (KPA) to maximize the PLCC profit. Two cases are considered: electric vehicles as energy sellers and the PLCC as an energy buyer, and electric vehicles as energy buyers and the PLCC as an energy seller. A realistic parking pattern of a parking lot on a university campus is considered as a case study. Different scenarios are investigated with respect to the number of electric vehicles and amount of energy trading. The proposed market mechanism outperforms the conventional scheme in view of costs and profits.

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