scholarly journals Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time

2021 ◽  
Vol 13 (15) ◽  
pp. 8180
Author(s):  
Xu Zhang ◽  
Fei-Yu Jin ◽  
Xu-Mei Yuan ◽  
Hai-Yan Zhang
Keyword(s):  
Transportation Network ◽  
Transportation Cost ◽  
Monte Carlo Sampling ◽  
Path Optimization ◽  
Practical Significance ◽  
Adaptive Genetic Algorithm ◽  
Low Carbon ◽  
Multimodal Transportation ◽  
Total Cost ◽  
Dual Uncertainty

The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in the high-quality development situation. This paper investigates the low-carbon path optimization problem under dual uncertainty. A hybrid robust stochastic optimization (HRSO) model is established considering the transportation cost, time cost and carbon emission cost. In order to solve this problem, a catastrophic adaptive genetic algorithm (CA-GA) based on Monte Carlo sampling is designed and tested for validity. The multimodal transportation schemes and costs under different modes are compared, and the impacts of uncertain parameters are analyzed by a 15-node multimodal transportation network numerical example. The results show that: (1) the uncertain mode will affect the decision-making of multimodal transportation, including the route and mode; (2) robust optimization with uncertain demand will increase the total cost of low-carbon multimodal transportation due to the pursuit of stability; (3) the influence of time uncertainty on the total cost is significant and fuzzy, showing the trend of an irregular wave-shaped change, like the ups and downs of the mountains. The model and algorithm we proposed can provide a theoretical basis for the administrative department and logistic services providers to optimize the transportation scheme under uncertainty.

scholarly journals Hierarchical hub location model and hybrid algorithm for integration of urban and rural public transport

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877326 ◽  
Author(s):  
Wei Zhong ◽  
Zhicai Juan ◽  
Fang Zong ◽  
Huishuang Su
Keyword(s):  
Public Transport ◽  
Rural Areas ◽  
Programming Model ◽  
Transportation Network ◽  
Transportation Cost ◽  
Capacity Constraint ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub And Spoke ◽  
Total Cost

Integration of urban and rural infrastructure is critical to integrating urban and rural public transport. A public transport hub is an important element of infrastructure, and it is the key facilities that serve as transferring points between cities and towns. The location of hub is related to the convenience of travel for urban and rural residents and the closeness of economic interactions between urban and rural areas. In this article, considering the background of the integration of urban and rural public transport, from the perspective of public transport hubs in urban and central town, a multi-level hub-and-spoke network is designed, and the location of integration of urban and rural public transport hub is determined. Based on the connection associated with central towns and the capacity constraints of hubs and to achieve the minimum total cost, this article proposes a mixed-integer programming model that employs a genetic and tabu search hybrid optimization algorithm to validate and analyze, which used the urban and rural public transport data from a specified area of Shandong province in China. The results indicate that the model can simultaneously determine locations for hubs in cities and central towns while minimizing total cost. The hub capacity constraint significantly influences the location of two-level hubs. The hub capacity constraint in the model can reduce the transportation cost for an entire network and optimize the transportation network. This study on urban and rural public transport hub location in a hub-and-spoke network not only reduces the transportation cost of the network but also completes and supplements the location theory of integration of urban and rural public transport.

Analysis of Identification Methods of Key Nodes in Transportation Network

2022 ◽  
Author(s):  
Qiang Lai ◽  
Hong-hao Zhang
Keyword(s):  
Transportation Networks ◽  
Transportation Network ◽  
Practical Significance ◽  
Node Degree ◽  
Connected Subgraph ◽  
Network Efficiency ◽  
Identification Methods ◽  
Identification Method ◽  
Bus Networks ◽  
Key Nodes

Abstract The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

A RESULT-ORIENTED FRAMEWORK TO SUPPORT THE LOW-CARBON TRANSFORMATION OF ENERGY SERVICES MARKETS

2020 ◽  
Vol 5 (2) ◽  
pp. 25-41
Author(s):  
Valeriy Deshko ◽  
◽  
Oleksandr Kovalko ◽  
Oleksandr Novoseltsev ◽  
Maria Yevtukhova ◽  
...  
Keyword(s):  
Renewable Energy Sources ◽  
Practical Significance ◽  
Low Carbon ◽  
Energy Services ◽  
Goods And Services ◽  
Organizational Mechanism ◽  
Production And Consumption ◽  
Almost All ◽  
Efficiency And Productivity

Today, the scope of energy services markets (ESMs) has expanded worldwide and covered almost all areas of production and consumption of goods and services for both industrial and public appointments, as well as households, mainly due to energy efficiency and renewable energy sources. At the same time, the incompleteness of theoretically grounded bases significantly reduces the pace of these markets development. The purpose of this study is to present the framework for the determination of directions and construct a model of structural organization and functional interaction of the ESMs participants. Such approach allows, by combining resources, capabilities and information, to expand the scope and improve the efficiency and productivity of energy services. A new structure-function model of ESMs participants’ interaction has been developed. In addition, a new organizational mechanism is proposed to support the efficient functioning of the ESMs in the form of a cycle of continuous improvement of the energy services results. The practical significance of the study is to create a conceptual framework for the organization and functioning of ESMs, which allows to systemically assess the new opportunities for such markets in both developed and developing countries.

scholarly journals Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Longlong Leng ◽  
Yanwei Zhao ◽  
Zheng Wang ◽  
Hongwei Wang ◽  
Jingling Zhang
Keyword(s):  
Fuel Consumption ◽  
Carbon Emission ◽  
Time Windows ◽  
Travel Distance ◽  
Low Carbon ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Total Cost ◽  
Location Routing ◽  
Self Adaptive

In this paper, we consider a variant of the location-routing problem (LRP), namely, the regional low-carbon LRP with reality constraint conditions (RLCLRPRCC), which is characterized by clients and depots that located in nested zones with different speed limits. The RLCLRPRCC aims at reducing the logistics total cost and carbon emission and improving clients satisfactory by replacing the travel distance/time with fuel consumption and carbon emission costs under considering heterogeneous fleet, simultaneous pickup and delivery, and hard time windows. Aiming at this project, a novel approach is proposed: hyperheuristic (HH), which manipulates the space, consisted of a fixed pool of simple operators such as “shift” and “swap” for directly modifying the space of solutions. In proposed framework of HH, a kind of shared mechanism-based self-adaptive selection strategy and self-adaptive acceptance criterion are developed to improve its performance, accelerate convergence, and improve algorithm accuracy. The results show that the proposed HH effectively solves LRP/LRPSPD/RLCLRPRCC within reasonable computing time and the proposed mathematical model can reduce 2.6% logistics total cost, 27.6% carbon emission/fuel consumption, and 13.6% travel distance. Additionally, several managerial insights are presented for logistics enterprises to plan and design the distribution network by extensively analyzing the effects of various problem parameters such as depot cost and location, clients’ distribution, heterogeneous vehicles, and time windows allowance, on the key performance indicators, including fuel consumption, carbon emissions, operational costs, travel distance, and time.

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