Application of multiple criteria decision making for network improvement

In this paper we propose application of multiple criteria decision making to problems of a metropolitan network improvement plan. Initially, a bilevel multiple objective network design model is considered in two objectives which are minimal government budget and minimal total travel time of road users. We seek feasible improvement alternatives among those bottleneck links in an existing road network structure and travel demand. We present an effective heuristic algorithm to obtain noninferior solutions; then ELECTRE III multiple criteria decision making and group decision making are used to evaluate and to select a compromise solution among those noninferior solutions. From the design phase in multiple criteria decision making, multiple objective mathematical programming is used to formulate a continuous network design model. However, from the phase of evaluation, multiple criteria decision making to solve the discrete network design problem. The network of metropolitan Taipei is taken as an example to illustrate the operation of this model.     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A two-stage approach to modeling vacant taxi movements

In this paper, a two-stage modeling approach is proposed to predict vacant taxi movements in searching for customers. The taxi movement problem is formulated into a two-stage model that consists of two sub-models, namely the first and second stage sub-models. The first stage sub-model estimates the zone choice of vacant taxi drivers for customer-search and the second stage sub-model determines the circulation time and distance of vacant taxi drivers in each zone by capturing their local customer-search decisions in a cell-based network within the zone chosen in the first stage sub-model. These two sub-models are designed to influence each other, and hence an iterative solution procedure is introduced to solve for a convergent solution. The modeling concept, advantages, and applications are illustrated by the global positioning system data of 460 Hong Kong urban taxis. The results demonstrate that the proposed model formulation offers a great improvement in terms of root mean square error as compared with the existing taxi customer-search models, and show the model capabilities of predicting the changes in vacant taxi trip distributions with respect to the variations in the fleet size and fare. Potential taxi policies are investigated and discussed according to the findings to provide insights in managing the Hong Kong taxi market.     

A bus route evaluation model based on GIS and super-efficient data envelopment analysis

When compared to large cities in developed countries, the shares of public transportation in most Chinese cities are low. Increasing the competitiveness of urban public transportation remains an urgent problem. A capable evaluation method for public transportation is required to assist the development of urban transit systems. This paper focuses on the bus system. Being devoid of standard criteria, it is difficult to determine the efficiency of a transit system or any bus line using a single evaluation index. This paper proposes a comparative analysis to evaluate bus lines so as to filter out candidates for further optimization. From the viewpoints of transit planning, operation and quality of service, this paper establishes 10 subordinate evaluation indices and then uses geographical information system tools, global positioning system data and smart card data to assist the index definition and calculation. Super-efficient data envelopment analysis (DEA) method is adopted for the proposed single factor and comprehensive evaluation models. Finally, the bus system in Shenzhen, China is used as a case study. The comparable significant results validate the capability of the proposed model.     

Measuring production and consumption efficiencies using the slack‐based measure network data envelopment analysis approach: the case of low‐cost carriers

One of the most important outcomes of the deregulation of air transportation policy is the emergence of low‐cost carriers (LCCs) around the world. Although LCC airlines have been in operation for more than 30 years, not every LCC is successful. In order to reduce the inefficiencies of LCCs, this paper measures the performance of LCCs by using slack‐based measure network data envelopment analysis. This model combines both the production process with input orientation and the consumption process with output orientation into a unified model. Furthermore, envelopment map analysis LCCs are performed to determine the reasons for the LCCs' inefficiency and how improvements can be made. A sample of 16 low‐cost airlines from Europe, the USA, and Asia were selected for operational performance analysis. The results show that the main reason for easyJet's, US Airways', and Virgin Blue's inefficiency is production inefficiency, so these LCCs should reduce their input quantities to increase efficiency. Jet2, Aer Lingus, and JetBlue were, by contrast, found to be consumption inefficient; these LCCs should increase their output quantities in order to enhance performance. Copyright © 2012 John Wiley & Sons, Ltd.     

Analysis of three independent real-world driving studies: A data driven and expert analysis approach to determining parameters affecting fuel economy

It is well established that individual variations in driving style have a significant impact on vehicle energy efficiency. The literature shows certain parameters have been linked to good fuel economy, specifically acceleration, throttle use, number of stop/starts and gear change behaviours. The primary aim of this study was to examine what driving parameters are specifically related to good fuel economy using a non-homogeneous extended data set of vehicles and drivers over real-world driving scenarios spanning two countries. The analysis presented in this paper shows how three completely independent studies looking at the same factor (i.e., the influence of driver behaviour on fuel efficiency) can be evaluated, and, despite their notable differences in location, environment, route, vehicle and drivers, can be compared on broadly similar terms. The data from the three studies were analysed in two ways; firstly, using expert analysis and the second a purely data driven approach. The various models and experts concurred that a combination of at least one factor from the each of the categories of vehicle speed, engine speed, acceleration and throttle position were required to accurately predict the impact on fuel economy. The identification of standard deviation of speed as the primary contributing factor to fuel economy, as identified by both the expert and data driven analysis, is also an important finding. Finally, this study has illustrated how various seemingly independent studies can be brought together, analysed as a whole and meaningful conclusions extracted from the combined data set.