Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system, where intermodal hubs are subject to site-dependent probabilistic disruptions. The disruption probabilities of intermodal hubs are estimated by using a probabilistic model which is developed using real world data. We developed an accelerated Benders decomposition algorithm to solve this challenging NP-hard problem. Numerical analysis show that the model selects to use intermodal hubs located in areas with low disruption probabilities. In case of a disaster, the reliable solution results in 6.21% savings over the minimum cost solution.     

Urban Sensing by Crowdsourcing: Analysing Urban Trip behaviour in Zurich

The research on which this essay is based sought to provide a deeper understanding of live urban activities. The main idea was to obtain in‐depth trip information by integrating sensing technology with crowdsourcing‐based methods. Location and acceleration sensors embedded in smartphones can deliver useful trip information. Research had previously been conducted to find an accurate data analysis algorithm for high‐level data mining, an efficient sensing method for power saving. As a proof of concept, this essay presents a case study of Zurich that successfully implemented previous research achievements in the real environment. It established that urban travel behaviour can, in fact, be collected by sensors embedded in mobile devices, and that the data thus obtained can be used to measure the characteristics of trip behaviour in cities by means of an advanced classifying algorithm and analysis. The strength of this research is its pioneering role in clearing the ground for future urban data collection methods and planning strategies. Specifically, this study could provide answers to the following key questions: How can crowdsourcing be applied to the collection of urban transportation data? What kinds of information can be extracted from the crowdsourced mobile sensing platform? What kinds of knowledge, within the transportation domain, can be derived from the above?     

Combinatorial clock-proxy exchange for carrier collaboration in less than truck load transportation

A carrier collaboration problem in less-than-truck load transportation is considered, where multiple carriers exchange their pickup and delivery requests in order to improve their operational efficiency. We extend the clock-proxy auction proposed by Ausubel et al. (2006) to a combinatorial clock-proxy exchange for the problem. This mechanism combines the price discovery of the clock exchange designed based on Lagrangian relaxation with the efficiency of the proxy exchange determined based on the information observed in the clock phase. Numerical experiments on randomly generated instances demonstrate the necessity of the proxy phase and the effectiveness of the clock-proxy exchange.     

Making dynamic ride-sharing work: The impact of driver and rider flexibility

We conduct an extensive computational study to quantify the impact of different types of participants’ flexibility on the performance of a single-driver, single-rider ride-sharing system. Our results consistently show that small increases in flexibility, e.g., in terms of desired departure time or maximum detour time, can significantly increase the expected matching rate, especially when the number of trip announcements in the system is small. The insights gained from our study can provide the basis for the design of information campaigns and incentives schemes aimed at increasing the performance and success of ride-sharing systems.     

A MILP model for planning the trips of dynamic positioned tankers with variable travel time

The transportation of the crude oil produced in offshore oilfields to onshore terminals is performed by vessels, known as shuttle tankers. Scheduling shuttle-tanker operations entails solving complex problems to ensure a timely offloading of the platforms, taking into account several logistics and inventory constraints. This work proposes a new MILP formulation that advances previous works by considering variable travel time between platforms and terminals. The combination of the MILP formulation with an optimization solver constitutes a decision-support tool to aid engineers reach optimal decisions for a planning horizon. To handle large-scale instances, rolling-horizon and relax-and-fix strategies are proposed.     

Stochastic seat allocation models for passenger rail transportation under customer choice

We study the seat allocation problem for passenger rail revenue management, in which a rail operator attempts to determine the optimal quantity of seats to be allocated to each cabin class for each train service. We formulate the problem with single-stage and multi-stage decisions as two stochastic programming models that incorporate passengers’ choice behavior. We transform the stochastic models into equivalent deterministic mathematical programs that are easy to solve. Then, we form a variety of seat allocation polices from the optimal solutions to the seat allocation models. A number of simulation tests are offered to test the policies.     

A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application

Growing importance of intermodal transportation necessitates modeling and solving load planning problems by taking into account various complex decisions simultaneously like transportation mode/service type selection, load allocation, and outsourcing. This paper presents a mixed-integer mathematical programming model for a multi-objective, multi-mode and multi-period sustainable load planning problem by considering import/export load flows to satisfy transport demands of customers and many other related issues. Several multiple objective optimization procedures are utilized in order to handle conflicting objectives simultaneously under crisp and fuzzy decision making environments. A real-life case study is also performed to present application and usefulness of the proposed model.     

Optimizing station location and fleet composition for a high-speed rail line

This paper proposes a new strategic planning model for high-speed rail ventures. It is a mixed-integer optimization model that applies to a given line and focuses on two key strategic decisions: station location and fleet composition. Our purpose is to improve on previous station location models by including fleet composition decisions. In the new model, we additionally take into account in an approximate fashion the interrelationships between strategic and subsequent tactical decisions, regarding line planning, train scheduling and fleet assignment issues. The usefulness of the model is demonstrated for a case study involving a planned Lisbon-Oporto high-speed rail line.     

Travel and tourism competitiveness index: The impact of air transportation,railways transportation,travel and transport services on international inbound and outbound tourism

The objective of the study is to examine the impact of air transportation, railways transportation, travel and transport services on international inbound and outbound tourism in a panel of 19 tourists - oriented countries, over a period of 1990–2014. By applying principal component analysis, the study constructs travel and tourism competitiveness index for inbound and outbound tourism. The main constructs of inbound tourism index include international tourists' arrival, tourism receipts, receipts of passengers' transports items and travel items while the constructs of the outbound index include international tourists' departure, tourism expenditures, and expenditures for passengers transport and travel items. The result of panel Fully Modified OLS (FMOLS) regression shows that the presence of air transportation, railways transportation, and trade openness positively affect inbound tourism index, while travel and transport services negatively affect tourism competitiveness index. The causality results confirm the bidirectional relationship between inbound tourism, air transportation, railways passengers carried, trade openness and travel and transport services, while there is a unidirectional causality running from inbound index to railway goods transported, from air transport freight to trade factor, and from travel services to air transport freight. Outbound tourism index confirmed the bidirectional causality relationship with air transportation, railways transportation, and travel and transport services, while the causality running from outbound index to trade factor, from air transport passenger carried to travel services, and from railway goods transported to trade and transport services, which support the unidirectional causality relationship between them. The variance decomposition results show that air transportation freight is the contributor that largely influences inbound-outbound tourism, while railways passengers carried and trade openness has the least share to influence inbound and outbound tourism index for the next 10-year period. The impulse response function indicates that air transportation, railways transportation, trade openness and travel services will positively impact on inbound truism while travel and transport services will positively affect outbound tourism for the next 10-year period. The study concludes with the importance of transportation sector that deem desirable to promote tourism worldwide. The concentration of different modes of transportation including air transportation, railways transportation, and travel and transport system would helpful to advance international tourism.     

The influence of neighborhood environment and household travel interactions on school travel behavior: an exploration using geographically-weighted models

Professional and popular interest in active school transportation (walking and cycling) is matched by an emerging literature on this topic. This paper explores school travel behavior of 11-year old children in Toronto, Canada. In particular, the effects of the neighborhood environment and caregiver-child travel interactions on travel mode choice were studied. Results indicate that the built environment near both home and school locations was associated with the odds of walking. However, predicted built environment effects were less accurate in some neighborhoods. Availability of adults at the time of school travel likely encouraged driving. School transportation interventions that broadly consider school and neighborhood-oriented policies and enable independent mobility may increase walking rates. Presence of spatial autocorrelation in the prevalence of walking suggests that more research is required to understand inter-household similarities in behaviors that are spatially structured.