ABSTRACT
Sudden infectious diseases and other malignant events cause excessive costs in the supply chain, particularly in the transportation sector. This issue, along with the uncertainty of the development of global epidemics and the frequency of extreme natural disaster events, continues to provoke discussion and reflection. However, transport systems involve interactions between different modes, which are further complicated by the reliable coupling of multiple modes. Therefore, for the vital subsystem of the supply chain-multimodal transport, in this paper, a heuristic algorithm considering node topology and transport characteristics in a multimodal transport network (MTN): the Reliability Oriented Routing Algorithm (RORA), is proposed based on the super-network and improved k-shell (IKS) algorithm. An empirical case based on the Yangtze River Delta region of China demonstrates that RORA enables a 16% reduction in the boundary value for route failure and a reduction of about 60.58% in the route cost increase compared to the typical cost-optimal algorithm, which means that RORA results in a more reliable routing solution. The analysis of network reliability also shows that the IKS values of the nodes are positively correlated with the reliability of the MTN, and nodes with different modes may have different transport reliabilities (highest for highways and lowest for inland waterways). These findings inform a reliability-based scheme and network design for multimodal transportation. Practical Applications: Recently, the COVID-19 epidemic and the frequency of natural disasters such as floods have prompted scholars to consider transport reliability. Therefore, efficient and reliable cargo transportation solutions are crucial for the sustainable development of multimodal transport in a country or region. In this paper, a new algorithm is designed to obtain a reliability-oriented optimal routing scheme for multimodal transport. Using actual data from the Yangtze River Delta region of China as an example for experimental analysis, we obtain that: (1) the proposed algorithm is superior in terms of efficiency, accuracy, and route reliability, which means that the new algorithm can quickly find more reliable routing solutions in the event of urban transport infrastructure failures;and (2) highway hubs have the greatest transport reliability. Conversely, inland waterway hubs are the least reliable. The influence of national highways and railways on the multimodal transport system is unbalanced. These findings provide decision support to transport policymakers on reliability. For example, transport investments should be focused on building large infrastructure and increasing transport capacity, strengthening the connectivity of inland waterway hubs to hubs with higher transport advantages, and leveraging the role of large hubs. © 2023 American Society of Civil Engineers.
ABSTRACT
The transportation industry is closely related to the macroeconomic development. The transportation services index (TSI) can be used to measure the relationship between them. The freight services index in Henan Province (HNFSI) is proposed based on the TSI. The HNFSI index is used to analyze the correlation, the periodicity, and the impact of COVID-19 between the development of economic and transportation in Henan Province. The results show that the correlation coefficient between the HNFSI index and the Growth Rate of Industrial Added Value which represents trends in economic development, is 0.745. The freight transportation demand increases with a certain periodicity and regularity. Due to the influence of COVID-19, the HNFSI in January 2020 decreased by 37.7% compared to the same period of 2019, and decreased by 56.3% in February. However, after March 2020, the freight service is greatly improved. © ASCE.
ABSTRACT
With the increasing concern on carbon emission, climate change, and human well-being, governments worldwide are exploring ways to encourage the usage of sustainable modes of transport. Particularly, cycling is gaining attention as a health and green travel mode, and bicycle-sharing systems are experiencing world-spread adoption. Moreover, in response to the COVID-19 pandemic, countries have begun to expand cycling infrastructures to promote cycling considering its advantages of keeping proper social distance. This study thus develops a bilevel model for the strategic planning of the infrastructure for a bike-sharing system. The upper-level problem is to simultaneously determine the location of bike stations and bike lanes to minimize the construction cost and the total travelers’ travel time cost. The lower-level problem is the combined mode and route choice network equilibrium problem with elastic cycling demand. One of the novelties of this study to the existing bike network literature is that it captures the reality that some travelers only begin to cycle and use bike-sharing services when there are bike stations close to both their origins and destinations. To solve the proposed bi-level model, a sequence-based selection hyper-heuristic is developed, which employs a hidden Markov model as the online learning method to determine a set of problem-tailored heuristics to explore the solution space. Numerical examples are carried out to examine the model properties and algorithm performance. The results demonstrate the positive impact of bike infrastructures on promoting cycling measured by the mode share increment.
ABSTRACT
COVID-19 has critically impacted many aspects of societies worldwide, particularly on mobility. This chapter summarizes impacts of the COVID-19 pandemic, reviews existing research, and identifies future research needs in the scope of traffic theory and modeling/optimization and traffic flow. We first review models on contagion spreading through transportation networks, including aggregated spatial metapopulation models and disaggregated individual-based models. Further research is needed to consider both intercity and intracity mobilities and leverage emerging multiple data resources for constructing individuals’ complete trip chains. Based on modeling contagion spreading, we further discuss transport operation needs in the aftermath of COVID-19. There remains a need for operating multimodal urban transport systems to satisfy basic travel demands while minimizing contagion risks. Relevant research needs are identified in optimizing transport operation via modern data acquisition technologies and advanced modeling methods. Practical intervention measures and policy implications are recommended for optimizing transport systems during the COVID-19 pandemic.
ABSTRACT
This study aims to contribute to more sustainable mobility solutions by proposing robust and actionable methods to assess the resilience of a multimodal transport system. Resilience is seen in a dynamic lean setting, looking at aspects in the network topology and user’s flow and demand throughout a parameterizable period. We hypothesize that this network’s appropriate multi-layered and traffic-sensitive modeling can promote the integrated analysis of different transport modes and support an improved resilience analysis. We operationalize the lean resilience conceptual construct with the proposed muLtImodal traNsportation rEsilience aSsessment (LINES) methodological process. Using the city of Lisbon as a study case, we illustrate the relevance of the proposed methodology to detect actionable vulnerabilities in the bus–tram–subway network.
ABSTRACT
This study demonstrated associations between multimodality and built environment characteristics, and proposed policy implications for fostering multimodal travel behaviors. It conducted a U.S. nationwide analysis using ordinary least square regression and gradient boosting decision tree regressor models with American Community Survey 2015–2019 5-year estimates and the United States Environmental Protection Agency Smart Location Database version 3.0. Notable findings were as follows: First, built environment characteristics were found to be statistically significant predictors of multimodality across the U.S. Second, certain features were identified as having considerable importance, specifically including population density, regional accessibility, walkability index, and network density, all of which should be given particular attention by transportation and land-use planners. Third, the non-linear effects of built environment characteristics on multimodality suggested an effective range to encourage multimodal transportation choice behaviors in various situations. The findings can guide the development of effective strategies to transform the built environment, which may subsequently be used to minimize reliance on automobiles and promote people to travel more sustainably.
ABSTRACT
How to dispatch emergency supplies timely and efficiently and reduce the damage caused by emergencies has become the focus of social attention. On the premise of considering the characteristics of special emergencies such as the epidemic situation of COVID-19, this paper constructed a kind of emergency supplies scheduling network of multi-supply points and multimodal transportation. Taking the lowest transportation cost, the least time penalty and the minimum risk of infection of dispatchers as the optimization objectives, it established a kind of multi-objective optimal scheduling model. In view of the limitation of the optimization algorithm based on clustering in solving multi-supply points, especially multi-objective scheduling optimization problems, the paper proposed a kind of hybrid niche genetic algorithm for variable length genotypes considering the idea of full feasible regions, which could avoid the problem above by restoring the search range of the solution to the fully feasible regions. The experiment results of 23 benchmark instances show that the optimization performance of the algorithm is stronger and it can search better solutions than best-known solutions of some examples. On this basis, the simulation results of four kinds of genetic algorithms in emergency supplies scheduling examples of multi-supply points and multimodal transportation come to a conclusion that the improved strategies such as hybrid niche are superior. (English) [ FROM AUTHOR] 如何及时、高效地调度应急物资以减小突发事件带来的伤害成为社会关注的焦点问题。在综合考虑新 冠肺炎疫情这类特殊突发事件特点的前提下, 构建了一类多供应点多式联运应急物资调度网络, 并以运输成本 最低、时间惩罚最少、配送员被感染风险最小为优化目标建立了一类多目标调度优化模型。考虑到基于聚类思 想的优化算法在解决多供应点, 尤其是多目标调度优化问题中缩减可行域方法科学性存疑的局限性, 提出了一 类考虑完全可行域思想的变长基因型混合小生境遗传算法, 并借助 ２３个基准测试实例验证了这一算法的有效 性, 更新了部分实例的现有最优解。在此基础上, 通过比较多供应点应急物资多式联运算例中四类遗传算法的 仿真结果进一步验证了混合小生境等改进策略的优越性。 (Chinese) [ FROM AUTHOR] Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Advanced air mobility (AAM) is a broad concept enabling consumers access to on-demand air mobility, cargo and package delivery, healthcare applications, and emergency services through an integrated and connected multimodal transportation network. While a number of technical and social concerns have been raised about AAM, early use cases for emergency response and aeromedical transport may be key to demonstrating the concept and building public acceptance. Using a five-step multi-method approach consisting of preliminary scoping, modeling performance metrics, developing baseline assumptions, analyzing scenarios, and applying a Monte Carlo sensitivity analysis, this study examines the potential operational and market viability of the air ambulance market using a variety of aircraft and propulsion types. The analysis concludes that electric vertical take-off and land (eVTOL) aircraft could confront a number of operational and economic challenges for aeromedical applications compared to hybrid vertical take-off and land (VTOL) aircraft and rotorcraft. The study finds that technological improvements such as reduced charge times, increased operational range, and battery swapping could make the eVTOL aircraft more reliable and cost-effective for aeromedical transport.
ABSTRACT
High distribution costs constitute one of the major obstacles to the sustainable development of rural logistics. In order to effectively reduce the distribution costs of last mile delivery in rural areas, based on three typical transport modes (local logistics providers, public transport, and crowdsourcing logistics), this study first proposes a multimodal transport design for last mile delivery in rural areas. Then, a cost–benefit model for multimodal transport is proposed which uses genetic algorithms (GA) to solve the logistical problems faced. Finally, Shapley value is used to fairly allocate profits and represent the marginal contribution of each mode in multimodal transport. The numerical results show that multimodal transport can effectively reduce the distribution costs of last mile delivery in rural areas. When the order demand of each node tends to be stable, the marginal contribution of crowdsourcing logistics is often greater than that of the other two distribution modes. The marginal contribution of public transport is highest only when the number of orders per node is very small.