Joint inventory-location problem under the risk of probabilistic facility disruptions

This paper studies a reliable joint inventory-location problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks (e.g., due to natural or man-made hazards). When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. We propose an integer programming model that minimizes the sum of facility construction costs, expected inventory holding costs and expected customer costs under normal and failure scenarios. We develop a Lagrangian relaxation solution framework for this problem, including a polynomial-time exact algorithm for the relaxed nonlinear subproblems. Numerical experiment results show that this proposed model is capable of providing a near-optimum solution within a short computation time. Managerial insights on the optimal facility deployment, inventory control strategies, and the corresponding cost constitutions are drawn.     

Subsidy and public transit performance: A factor analytic approach

The need to measure and evaluate transit system performance has led to the development of numerous performance indicators. However, depending upon the indicator, we oftentimes reach different conclusions regarding transit system performance. The research reported in this paper uses factor analytic methods to generate a set of underlying attributes (factors) that capture the performance of public transit systems in Indiana. Similar to what is reported in the literature, this study finds three attributes that best describe transit system performance: efficiency, effectiveness, and overall performance. Based upon systemsÕ factor scores, the study finds that systems scoring highly on one attribute generally perform well on the remaining attributes. Further, there is an inverse relationship between system performance and subsidies, a finding that supports performance based subsidy allocations.     

Park and ride facilities on light rail transit systems

There is now considerable interest in exploring the idea of strategic park and ride as a means of promoting the use of rail transit and encouraging a transfer of commuters from car to public transport. This is especially evident in North America, where extensive park and ride facilities have been installed on a number of light and heavy urban rail systems. There is a general consensus about the most suitable types of location for facilities, but less agreement on the development of a reliable method of forecasting demand and also on the required size of sites. Experience in practice indicates that although park and ride is attractive to commuters, schemes do not generally result in lasting reductions in highway congestion, due to rising car ownership and use and the phenomenon of generated traffic.Abbreviations Centro West Midlands Passenger Transport Executive - K&R Kiss and ride - LRT Light Rail Transit - PT Public Transport - RT Rapid Transit - TRRL Transport & Road Research Laboratory, UK     

Reliable sensor deployment for network traffic surveillance

New sensor technologies enable synthesis of disaggregated vehicle information from multiple locations. This paper proposes a reliable facility location model to optimize traffic surveillance benefit from synthesized sensor pairs (e.g., for travel time estimation) in addition to individual sensor flow coverage (e.g., for traffic volume statistics), while considering probabilistic sensor failures. Customized greedy and Lagrangian relaxation algorithms are proposed to solve this problem, and their performance is discussed. Numerical results show that the proposed algorithms solve the problem efficiently. We also discuss managerial insights on how optimal sensor deployment and surveillance benefits vary with surveillance objective and system parameters (such as sensor failure probabilities).     

Finding the most reliable path with and without link travel time correlation: A Lagrangian substitution based approach

Path travel time reliability is an essential measure of the quality of service for transportation systems and an important attribute in travelers’ route and departure time scheduling. This paper investigates a fundamental problem of finding the most reliable path under different spatial correlation assumptions, where the path travel time variability is represented by its standard deviation. To handle the non-linear and non-additive cost functions introduced by the quadratic forms of the standard deviation term, a Lagrangian substitution approach is adopted to estimate the lower bound of the most reliable path solution through solving a sequence of standard shortest path problems. A subgradient algorithm is used to iteratively improve the solution quality by reducing the optimality gap. To characterize the link travel time correlation structure associated with the end-to-end trip time reliability measure, this research develops a sampling-based method to dynamically construct a proxy objective function in terms of travel time observations from multiple days. The proposed algorithms are evaluated under a large-scale Bay Area, California network with real-world measurements.     

Optimal shipment decisions for an airfreight forwarder: Formulation and solution methods

We study the freight forwarder’s shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times.After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems.     

A test of inter-modal performance measures for transit investment decisions

Choices among alternative transit capital investments are often complex and politically controversial. There is renewed interest in the use of performance indicators to assist in making rational and defensible choices for the investment of public funds. To improve the evaluation of rail and bus performance and provide more useful information for transit investment decision-makers, it is important to use performance indicators that fairly and efficiently compare different transit modes. This paper proposes a set of inter-modal performance indicators in which service input, service output, and service consumption are measured by total cost, revenue capacity miles/hours, and unlinked passenger trips/miles respectively based on economic principles and evaluation objectives. The proposed improvements involve the inclusion of capital as well as operating costs in such comparisons, and the recognition of the widely varying capacities of transit vehicles for seated and standing passengers. Two California cases, the Los Angeles – Long Beach Corridor and the Market/Judah Corridor in San Francisco, are used for testing their usefulness in the evaluation of the efficiency and effectiveness of rail and bus services. The results show substantial differences between performance indicators in current use and those proposed in this study. The enhanced inter-modal performance indicators are more appropriate for comparing the efficiency and effectiveness of different modes or a combination of transit modes at the corridor and system levels where most major investment decisions are made. This revised version was published online in June 2006 with corrections to the Cover Date.     

Unlimited Access

Universities and public transit agencies have together invented an arrangement – called Unlimited Access – that provides fare-free transit service for over 825,000 people. The university typically pays the transit agency an annual lump sum based on expected student ridership, and students simply show their university identification to board the bus. This paper reports the results of a survey of Unlimited Access programs at 35 universities. University officials report that Unlimited Access reduces parking demand, increases students' access to the campus, helps to recruit and retain students, and reduces the cost of attending college. Transit agencies report that Unlimited Access increases ridership, fills empty seats, improves transit service, and reduces the operating cost per rider. Increases in student transit ridership ranged from 71 percent to 200 percent during the first year of Unlimited Access, and growth in subsequent years ranged from 2 percent to 10 percent per year. The universities' average cost for Unlimited Access is $30 per student per year.     

Why do people fare evade? A global shift in fare evasion research

ABSTRACT

Fare evasion is a significant concern for most transit authorities. The traditional approach to fare compliance has focussed on modifying the physical control of ticketing or ticket inspection rates. Yet recently the perspective on fare evasion has begun to shift toward profiling the fare evader or understanding the customer motivations to fare evade. This paper uses a literature review method to document the characteristics of these three perspectives on fare evasion: the conventional transit system perspective, the customer profiling perspective and the customer motivations perspective. We find that the conventional transit system perspective, although straightforward to measure and control, has its limits particularly in “open” transit systems. The customer profiling perspective attempts to identify, based on demographics, which customers are more likely to fare evade. However this perspective has little use beyond profiling and is ethically questionable. The customer motivations perspective provides a richer understanding of how customers define fare evasion and what attitudes, social norms and circumstances motivates them to fare evade. Considering that between 20% and 40% of a city’s residents admit to fare evading at some point, understanding these complex motivations can help improve revenue compliance at a time when most governments heavily subsidise their transit systems.