A decision support system for developing the managerial policy of urban paratransit services: A case study of the Massachusetts Bay Transit Authority

In the wake of the Americans with Disability Act (ADA) of 1990, paratransit services were offered to improve mobility, employment opportunities, and access to community services for individuals who are mentally or physically handicapped. Due to the complexity involved in ADA rules and transportation regulations as well as the customized, on-demand service requirements, paratransit services are far more costly to render than fixed-route based mass transit services. In times of ongoing budget crisis among public entities, many public transit authorities cope with a dilemma of meeting the growing demand and complex service requirements, while controlling rising paratransit costs. Considering this dilemma, this paper proposes a decision support system (DSS) that can aid the mass transit authority in evaluating paratransit service performance, while continually improving performance over time. To validate the usefulness of the proposed DSS, it has been applied to the actual case of the Massachusetts Bay Transit Authority (MBTA)

What’s in a Coefficient? The “Not so Simple” Interpretation of R2, for Relatively Small Sample Sizes

There are several misconceptions when interpreting the values of the coefficient of determination, R2, in simple linear regression. R2 is heavily dependent on sample size n and the type of data being analyzed but becomes insignificant when working with very large sample sizes. In this paper, we comment on these observations and develop a relationship between R2, n, and the level of significance α, for relatively small sample sizes. In addition, this paper provides a simplified version of the relationship between R2 and n, by comparing the standard deviation of the dependent variable, Sy, to the standard error of the estimate, Se. This relationship will serve as a safe lower bound to the values of R2. Computational experiments are performed to confirm the results from both models. Even though the focus of the paper is on simple linear regression, we present the groundwork for expanding our two models to the multiple regression case

Transport poverty meets the digital divide : accessibility and connectivity in rural communities

Peer reviewedPublisher PD

Developing a resource allocation model for the Scottish Patient Transport Service

The Patient Transport Service is a vital component of many healthcare systems. However, increasing demand and constrained resources impose great challenges, especially in Scotland where there is a substantial remote and rural population. This case study describes the development of a decision support tool for strategic resource allocation decisions. The tool had to be relevant to management's practical needs including transparency to a range of stakeholders and a flexible speedy response to help management explore various operational and policy options. However, the tool also had to demonstrate rigour and identify an efficient allocation of resources. In response to these requirements, the decision support tool was constructed from simple models, verified in comparisons with more rigorous and sophisticated approaches, notably a Dial-a-Ride genetic algorithm and an open vehicle routing simulation. Using this tool, management were able to: identify a more rational, strategic allocation of resources; quantify the remote and rural effect; examine trade-offs between service level and resource requirements within various scenarios for future demand

A Reverse Logistics Network Model for Handling Returned Products

58827Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company’s bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.S

The relocation of a hybrid manufacturing/distribution facility from supply chain perspectives: a case study

In this paper we present a real-world case study involving the re-location of a combined manufacturing and distribution (warehousing) facility. The relocation decision was called to adapt to dynamic changes in business environments surrounding the firm's supply chain operations. Such changes include changes in supplier and customer bases, distribution networks, corporate re-engineering, business climate and government legislation. To aid management in formulating a more efficient and effective relocation strategy, we designed the configuration of supply chain networks and assessed the viability of the proposed sites from supply chain perspectives using the analytic hierarchy process (AHP).Supply chain management Warehouse location Analytic hierarchy process