A multiobjective chance constrained programming model for supplier selection under uncertainty

Risk management is an inherent part of supplier selection. While companies are enjoying the benefits of outsourcing, risks brought by this practice should be taken into account in the process of decision making. This paper presents a multiobjective stochastic sequential supplier allocation model to help in supplier selection under uncertainty. Demand for products, capacities at suppliers as well as transportation and other variable costs are the main sources of uncertainty and are modeled using probability distributions. Disruptions are exogenous events and the model provides proactive mitigation strategies against disruptions by assigning backup suppliers who can be used in case of a default at a primary supplier. When there is no disruption, the model’s solution is an optimal supplier order assignment, considering operational risks.     

Approximate network loading and dual-time-scale dynamic user equilibrium

In this paper we present a dual-time-scale formulation of dynamic user equilibrium (DUE) with demand evolution. Our formulation belongs to the problem class that Pang and Stewart (2008) refer to as differential variational inequalities. It combines the within-day time scale for which route and departure time choices fluctuate in continuous time with the day-to-day time scale for which demand evolves in discrete time steps. Our formulation is consistent with the often told story that drivers adjust their travel demands at the end of every day based on their congestion experience during one or more previous days. We show that analysis of the within-day assignment model is tremendously simplified by expressing dynamic user equilibrium as a differential variational inequality. We also show there is a class of day-to-day demand growth models that allow the dual-time-scale formulation to be decomposed by time-stepping to yield a sequence of continuous time, single-day, dynamic user equilibrium problems. To solve the single-day DUE problems arising during time-stepping, it is necessary to repeatedly solve a dynamic network loading problem. We observe that the network loading phase of DUE computation generally constitutes a differential algebraic equation (DAE) system, and we show that the DAE system for network loading based on the link delay model (LDM) of Friesz et al. (1993) may be approximated by a system of ordinary differential equations (ODEs). That system of ODEs, as we demonstrate, may be efficiently solved using traditional numerical methods for such problems. To compute an actual dynamic user equilibrium, we introduce a continuous time fixed-point algorithm and prove its convergence for effective path delay operators that allow a limited type of nonmonotone path delay. We show that our DUE algorithm is compatible with network loading based on the LDM and the cell transmission model (CTM) due to Daganzo (1995). We provide a numerical example based on the much studied Sioux Falls network.     

Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors

Microeconomic optimisation of scheduled public transport operations has traditionally focused on finding optimal values for the frequency of service, capacity of vehicles, number of lines and distance between stops. In addition, however, there exist other elements in the system that present a trade-off between the interests of users and operators that have not received attention in the literature, such as the optimal selection of a fare payment system and a designed running speed (i.e., the cruising speed that buses maintain in between two consecutive stops). Alternative fare payment methods (e.g., on-board and off-board, payment by cash, magnetic strip or smart card) have different boarding times and capital costs, with the more efficient systems such as a contactless smart card imposing higher amounts of capital investment. Based on empirical data from several Bus Rapid Transit systems around the world, we also find that there is a positive relationship between infrastructure cost per kilometre and commercial speed (including stops), achieved by the buses, which we further postulate as a linear relationship between infrastructure investment and running speed. Given this context, we develop a microeconomic model for the operation of a bus corridor that minimises total cost (users and operator) and has five decision variables: frequency, capacity of vehicles, station spacing, fare payment system and running speed, thus extending the traditional framework. Congestion, induced by bus frequency, plays an important role in the design of the system, as queues develop behind high demand bus stops when the frequency is high. We show that (i) an off-board fare payment system is the most cost effective in the majority of circumstances; (ii) bus congestion results in decreased frequency while fare and bus capacity increase, and (iii) the optimal running speed grows with the logarithm of demand.     

Capacity drops at merges: An endogenous model

The Newell-Daganzo merge model is not only very simple but also accurately reproduces experimental findings. However, the capacity downstream of the merge is an exogenous variable in the model. This is a serious limitation for merges that behave as active bottlenecks because their downstream capacity is a direct consequence of the merging behavior. This paper proposes an analytical model that extends the Newell-Daganzo model by incorporating, endogenously, the capacity drop related to the merging process. Two cases are investigated depending on the traffic states on the on-ramp. The model properties are analyzed and a sensitivity analysis is performed to quantify the relative contribution of the each parameter in the capacity drop. Finally, the extended Newell-Daganzo model is validated with experimental data coming from an active merge bottleneck on the M6 freeway in UK.     

Railway wheel-flat detection and measurement by ultrasound

This work presents an innovative ultrasound technique designed to detect and quantify flats formed in the rolling surface of railway wheels. Differently from other approaches, ultrasonic pulses (Rayleigh waves) are sent over a measuring rail. The variations in the round-trip time of flight (RTOF) of the ultrasound pulse to the rail-wheel contact point allow detecting and quantifying the wheel-flats. In spite of the wear state of the irregularity, the method provides the loss of material and the length of the flat originally formed by abrasion. A theoretical background supports the technique which offers many advantages for railway maintenance. Simulations and experimental results match the expected ones.     

Mobility, social exclusion and well-being: Exploring the links

Building on a growing research foundation, transport policy makers have begun to associate the ability to be mobile with having a role in the facilitation of social inclusion. However, the further connection to well-being is not as well understood. This paper explores the association between a person’s travel patterns, their risk of social exclusion and self-assessed well-being. Key influences on social exclusion are discussed, with trip making emerging as a significant influence. Trip making is not a significant direct influence on well-being but does exercise an indirect influence through the impact on risk of social exclusion. The modelling process enables a value for additional trips to be estimated, the value being about four times the values derived from conventional generated traffic approaches. Similar high values are found in separate metropolitan and regional case studies, confirming the significance of the results.     

Minimum Efficient Scale (MES) and preferred scale of container terminals

The decision on the scale of a port terminal affects the terminal’s managerial, operational and competitive position in all the phases of its life. It also affects competition structures in the port in which the terminal is operating, and has a potential impact on other terminals. Port authorities and terminal operators need to know the scale of the terminal when engaging in concession agreements. In economic theory the scale of a plant/firm is typically defined in relation to the Minimum Efficient Scale (MES), the long-run output where the internal economies of scale are fully exploited. However, there are a number of theoretical and empirical indications that in ports the scale of a terminal is commonly guided by a combination of the MES and other determining factors. The “preferred” scale is the result of a complex interaction between the MES, the port governance framework and objectives, the market size and structure, technological change and operational considerations, physical and geographical limitations, and the business patterns of shipping lines. This study analyses the factors resulting in a preferred container terminal scale that in most of the times is different from the MES. The analysis of the technical, market-related and governance-related factors is supported by theoretical and empirical insights that illustrate the presence of a range of actual ”preferred” scales of terminal concessions that usually are different, below or above, MES.     

Mesoscale subduction at the Almeria–Oran front: Part 1: Ageostrophic flow

This paper presents a detailed diagnostic analysis of hydrographic and current meter data from three, rapidly repeated, fine-scale surveys of the Almeria–Oran front. Instability of the frontal boundary, between surface waters of Atlantic and Mediterranean origin, is shown to provide a mechanism for significant heat transfer from the surface layers to the deep ocean in winter. The data were collected during the second observational phase of the EU funded OMEGA project on RRS Discovery cruise 224 during December 1996. High resolution hydrographic measurements using the towed undulating CTD vehicle, SeaSoar, traced the subduction of Mediterranean Surface Water across the Almeria–Oran front. This subduction is shown to result from a significant baroclinic component to the instability of the frontal jet. The Q-vector formulation of the omega equation is combined with a scale analysis to quantitatively diagnose vertical transport resulting from mesoscale ageostrophic circulation. The analyses are presented and discussed in the presence of satellite and airborne remotely sensed data; which provide the basis for a thorough and novel approach to the determination of observational error.     

Transport and nation‐state governments worldwide: a further review

The review undertaken in this Paper shows how, in 1984, governments of nation‐states of the world deal with the important function of Transport. In all 115 countries are included and, with the information now given, it is possible to compare the situation with 1981–82, and also have a current global view of affairs affecting Transport as managed by governments. Such a review is part of the service which Transport Reviews provides for its readers. It is hoped to conduct a further review in 1988.     

Estimating traffic demand risk – A multiscale analysis

This paper proposes a novel method for estimating the traffic demand risk associated with transportation. Using mathematical properties of wavelets, we develop a statistical measure of traffic demand sensitivity with respect to GDP. This measure can be adapted in a flexible way to capture risk levels relevant for different investment horizons. We demonstrate the timescale decomposition of risk with Swedish traffic demand data for 1950–2005. In general, rail transport shows a stronger co-movement with GDP than road transport. Moreover, we examine the volatility exhibited by traffic demand. Our findings suggest that rail investments are more risky than road investments. Since the findings can be used for optimal investment timing and for choice between public investment alternatives, they are deemed important for public policy in general.