Measuring quality of service in dial-a-ride operations: the case of a Canadian city

In many countries, dial-a-ride services are provided by public authorities to elderly and handicapped people who cannot use regular transit. Cost minimization is key to running these services, but one can observe a growing interest in quality measurement and improvement. A first step in improving quality is to define a quality measurement scale specific to dial-a-ride services. A second step is to incorporate quality measurements in mathematical models that serve as a basis for optimization algorithms. To this end, an extensive survey of dial-a-ride users was conducted in Longueuil, the largest suburb of Montreal, Canada. This paper describes the steps of the survey and presents its main conclusions: (1) 56 attributes were identified based on interviews, (2) the questionnaire developed has proved to be reliable and valid, (3) an exploratory factor analysis allowed us to determine 13 dimensions of quality in dial-a-ride services, (4) the most important criteria for users were identified, and (5) population segmenting variables by which subgroups of users can be categorized were also determined. Managerial implications of our results are also discussed.     

The Pollution-Routing Problem

The amount of pollution emitted by a vehicle depends on its load and speed, among other factors. This paper presents the Pollution-Routing Problem (PRP), an extension of the classical Vehicle Routing Problem (VRP) with a broader and more comprehensive objective function that accounts not just for the travel distance, but also for the amount of greenhouse emissions, fuel, travel times and their costs. Mathematical models are described for the PRP with or without time windows and computational experiments are performed on realistic instances. The paper sheds light on the tradeoffs between various parameters such as vehicle load, speed and total cost, and offers insight on economies of ‘environmental-friendly’ vehicle routing. The results suggest that, contrary to the VRP, the PRP is significantly more difficult to solve to optimality but has the potential of yielding savings in total cost.     

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988–1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.     

Taxicab operating characteristics in the United States

In 1982, a national survey of U.S. taxicab operators was conducted. This survey sought to assess the economic, operational and organizational status of the industry and to determine how these characteristics have been changing in response to rising costs and an economic recession. Two results of this survey are reported in this paper; the size structure and the organization of the industry. Both of these characteristics show that it has recently been undergoing two fundamental changes. These are the rapid switch away from employees as drivers to independent contractor drivers and decreasing average company size.     

Static and changing port economic impacts

This paper attempts to provide general guidelines for conducting a port' economic impact analysis. In so doing, a methodology is proposed to organize efficiency the search for port-related industries and to determine the degree of their dependence on a port. this methodology is applied to the port of Hampton Roads. In addition, some constraints in predicting the changes in the economic impact of a port attribute to changes in the volume cargo are identified.     

The importance of attitudes in the decision to use mass transit

This paper reports the results of tests of the hypotheses that attitudinal variables are important in mode choice decisions and that they can significantly increase the explanatory power of network-based mode choice models. Conflicts between the results of previous work by Lovelock and Johnson are resolved by this study. Attitudinal items used by Johnson and by Lovelock in separate studies in the San Francisco Bay area were included in a survey of Chapel Hill households. Tests of the incremental explanatory power of the attitudinal variables in mode choice models confirm that the items used by Johnson do not contribute to the explanatory power of models using network time and cost data. Similar tests showed that Lovelock's attitudinal items do significantly increase the predictive ability of the models. The conflicting results of these previous studies are therefore due to the content of the items. Attitudinal data, including both attitude items and measures of perceptions of system attributes, do enhance the predictive power of models involving network data.This research was supported by a grant from the Urban Mass Transportation Administration, U.S. Department of Transportation, Washington, D.C.     

Taxonometric evaluation

Transportation planning has for too long been unbalanced in that an excessive amount of time has been spent on building increasingly complex quantitative models at the expense of rather important aspects of the design and forecasting stages of the process. This paper therefore sets out to consider two related problems: that of forming a coherent and useful link between the design and evaluation stages and that of suggesting a method of dealing with probabilistic forecasts within the evaluation model.The solutions to both of these problems are linked. It is suggested that the structure of and variables contained within the formal evaluation model must also necessarily play a part in the scheme design or selection process. This process is itself seen as one of hierarchical selection wherein classes of scheme or solution are successively more explicitly identified as sensibly different and, where possible, the preferred class is identified. Central to this taxonometric procedure is the idea of sensible differentiation between classes whose characteristic performance is only known uncertainly and some algorithms for achieving this are suggested.     

Impact of freshwater on a subarctic coastal ecosystem under seasonal sea ice (southeastern Hudson Bay, Canada). III. Feeding success of marine fish larvae

We monitored the feeding success (percent feeding incidence at length and mean feeding ratio at length) of Arctic cod (Boreogadus saida) and sand lance (Ammodytes sp.) larvae in relation to prey density, light, temperature and potential predator density under the ice cover of southeastern Hudson Bay in the spring of 1988, 1989 and 1990. Both prey density and light limited larval fish feeding. The relationship between feeding success and actual food availability (nauplii density X irradiance) was adequately described by an Ivlev function which explained 64 and 76% of the variance in Arctic cod and sand lance feeding success respectively. By affecting both prey density and irradiance, the thickness of the Great Whale River plume (as defined by the depth of the 25 isohaline) was the main determinant of prey availability. Arctic cod and sand lance larvae stopped feeding when the depth of the 25 isohaline exceeded 9 m. Limitation of feeding success attributable to freshwater inputs occurred exclusively in 1988, the only time when the depth of the 25 isohaline exceeded the 9 m threshold. The close dependence of larval fish feeding success on the timing of the freshet and plume dynamics suggests a direct link between climate and survival of Arctic cod and sand lance larvae. The actual impact of climate fluctuations and/or hydro-electric developments on recruitment will depend on the fraction of the larval dispersal area of the two species that is affected by river plumes.     

Modelling the hydrodynamics and ecosystem of the North-West European continental shelf for operational oceanography

This paper outlines an approach to complex spatio-temporal marine ecosystem modelling as applied to the North Western European Continental Shelf. The model presented here combines an eddy-permitting (approximately 6 km horizontal resolution) baroclinic model, the Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS), with the European Regional Seas Ecosystem Model (ERSEM). This has been run within an operational framework using operationally available high resolution atmospheric and lateral boundary forcing, allowing hindcast and near-real time nowcast simulations to be performed. The modelled surface temperature and chlorophyll distributions are presented, and interannual variations discussed. Validation of both the physical and ecosystem submodels show the system to be effective, whilst highlighting areas where improvements in the system can be made. Distinct regional differences in predictive skill are shown. The system presented is ready for operational implementation to provide products and services for use both scientifically and in coastal zone and shelf seas management activities. A programme of work to update the system is already in place.