Konstantinos Kepaptsoglou

The Gravity Model Specification for Modeling International Trade Flows and Free Trade Agreement Effects: A 10-Year Review of Empirical Studies

The gravity model has been extensively used in international trade research for the last 40 years because of its considerable empirical robustness and explanatory power. Since their introduction in the 1960s, gravity models have been used for assessing trade policy implications and, particularly recently, for analyzing the effects of Free Trade Agreements on international trade. The objective of this paper is to review the recent empirical literature on gravity models, highlight best practices and provide an overview of Free Trade Agreement effects on international trade as reported by relevant gravity model-based studies over the past decade.

A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network

Emergency response services are critical for modern societies. This paper presents a model and a heuristic solution for the optimal deployment of many emergency response units in an urban transportation network and an application for transit mobile repair units (TMRU) in the city of Athens, Greece. The model considers the stochastic nature of such services, suggesting that a unit may be already engaged, when an incident occurs. The proposed model integrates a queuing model (the hypercube model), a location model and a metaheuristic optimization algorithm (genetic algorithm) for obtaining appropriate unit locations in a two-step approach. In the first step, the service area is partitioned into sub-areas (called superdistricts) while, in parallel, necessary number of units is determined for each superdistrict. An approximate solution to the symmetric hypercube model with spatially homogeneous demand is developed. A Genetic Algorithm is combined with the approximate hypercube model for obtaining best superdistricts and associated unit numbers. With both of the above requirements defined in step one, the second step proceeds in the optimal deployment of units within each superdistrict.

The bus bridging problem in metro operations: conceptual framework, models and algorithms

Metro networks provide efficient transportation services to large numbers of travelers in urban areas around the World; any unexpected operational disruption can lead to rapid degradation of the provided level of service by a city’s public transportation system. In such instances, quick and efficient substitution of services is necessary for accommodating metro passengers including the widely used practice of “bridging” metro stations using bus services. Despite its widespread application, bus bridging is largely done ad-hoc and not as part of an integrated optimization procedure. In this paper we propose a methodological framework for planning and designing an efficient bus bridging network. Furthermore, we offer a set of structured steps and optimization models and algorithms for handling bus bridging problems.

A Real-Time Parking Prediction System for Smart Cities

A methodological framework for multiple steps ahead parking availability prediction is presented. Two different types of predictions are provided: the probability of a free space to continue being free in subsequent time intervals, and the short-term parking occupancy prediction in selected regions of an urban road network. The available data come from a wide network of on-street parking sensors in the “smart” city of Santander, Spain. The sensor network is segmented in four different regions, and then survival and neural network models are developed for each region separately. Findings show that the Weibull parametric models best describe the probability of a parking space to continue to be free in the forthcoming time intervals. Moreover, simple genetically optimized multilayer perceptrons accurately predict region parking occupancy rates up to 30 minutes in the future by exploiting 1-minute data. Finally, the real time, Web-based, implementation of the proposed parking prediction availability system is presented.

An Empirical Investigation of Passenger Wait Time Perceptions Using Hazard-Based Duration Models

Waiting time in bus stops heavily affects traveler attitude towards public transportation and therefore is an important element for consideration when planning and operating a bus system. Furthermore, what passengers perceive as waiting time is often quite different from their actual waiting time at a bus stop. In this context, we present an empirical investigation of actual and perceived waiting times at bus stops for the case of a large bus network, using hazard-based duration models. The analysis is based on a questionnaire survey undertaken at bus stops of the Athens, Greece, bus network. Results indicate that age, trip purpose, and trip time period seem to have an impact on that perception, with older individuals, work, and education trips being factors that increase perceived waiting time and lead to an overestimation of actual waiting, while perceived waiting time decreases during morning time periods.

Model for Planning Emergency Response Services in Road Safety

In an era of continuous growth in mobility and demand for transportation, safety is an issue of major social concern and an area of extensive research and work by practitioners and academics. Emergency response services are very important in handling and minimizing the impacts of traffic accidents and for saving human lives. In this paper, we develop an efficient emergency response plan for responding to traffic accidents; the objective is to strategically deploy emergency response vehicles in a large urban transportation network. We combine a location model with a genetic algorithm and guide location decisions through accident metrics such as accident frequencies and severities at different parts of the network. We demonstrate the usefulness and applicability of this approach by planning for a real-world case study in the city of Thessaloniki, Greece.

Optimizing Pricing Policies in Park-and-Ride Facilities: A Model and Decision Support System with Application

Abstract Park-and-ride facilities are of major importance to the attractiveness and operation of modern transit systems because travelers tend to prefer public transportation when they are able to combine the use of these facilities with their private vehicles. Among those elements examined when developing/operating a park-and-ride facility is the pricing policy to be established for its users. Indeed, the pricing policy is among those tools that can aid transportation agencies in managing park-and-ride facilities, by providing incentives or disincentives of parking for various categories of users. This paper contributes to the literature by offering a new approach for obtaining optimal pricing schemes for a parking facility, with respect to its financial viability. In particular, a financial analysis model is combined with a genetic algorithm for determining the optimal pricing parameters for park-and-ride facilities. The model is applied for a shared-use, park-and-ride facility of the Athens metro network in Greece. Results of the computational study indicate that the model can offer near optimal pricing schemes in a short amount of time. Also, a decision support system is developed for incorporating the model in a user friendly computerized framework.

Bus-to-Depot Allocation: Models and Decision Support System

Reducing the cost of operations is one of the most important considerations for urban transport systems. Deadhead kilometer costs are an important aspect of operating costs and are associated with buses traveling empty to and from depots; minimizing these costs is referred to as the bus-to-depot allocation problem and addressing it may be important in reducing overall costs. We present a model and an associated decision support system (DSS) for optimally allocating buses to depots while minimizing deadhead costs and keeping depot occupancy at “ideal” operational levels. The model and DSS are tested in the Athens, Greece, large urban transit system and results indicate that considerable cost savings can be realized compared to current allocation schemes.

Genetic Algorithm-Based Approach for Optimal Location of Transit Repair Vehicles on a Large Urban Network

Determining the optimal location of a fleet of vehicles is necessary in a number of potential applications, such as special repair vehicles for buses on a large public transportation network. The Athens Urban Transport Authority operates a large bus fleet over an extensive network for 19 h a day and serves a population of approximately 4 million people, all in a heavily congested road network. During the 2004 Summer Olympic Games, held in Athens, most spectators, employees, and volunteers were transported to and from Olympic Games venues by public transportation. Dedicated Olympic Games bus lines operated under a tight around-the-clock schedule. During normal operations and particularly during events such as the Olympic Games, incidents such as vehicle breakdowns and minor accidents can have a severe effect on the operation of the public transport network and can cause a significant decrease in the level of service. To help the authority locate bus repair vehicles over the entire network, a decision support system was developed on the basis of an embedded genetic algorithm used for obtaining optimal location solutions. The systems design and performance make it easy to operate under real-time conditions, which is useful for planning and for fast vehicle redeployment.

Quality Management in Mobility Management: A Scheme for Supporting Sustainable Transportation in Cities

ABSTRACT Mobility management (MM) has been among Europes prevailing approaches for promoting and achieving sustainable transportation in urban areas, with considerable work undertaken by researchers and practitioners in this area during the past two decades. However, development of MM policies and measures in European cities does not follow an organized and consistent approach for planning, designing, applying, and evaluating a comprehensive MM-system. In that context, the objective of this article is to propose a scheme, based on quality management (QM) principles, that would aid cities in systematically developing and deploying MM-plans and MM–measures and therefore in successfully supporting sustainability in their transportation system. The developed Quality Management Scheme for Mobility Management (QMSMM) is an integrated process of four major components, encompassing policy setting, planning, implementing, and monitoring and evaluating; these components are structured in a feedback loop and supported by a set of quality criteria per component. The structure, components, and elements of the QMSMM are presented in detail, along with supporting procedures for assessing a citys adaptation and compatibility with the scheme. Also, insights on a QMSMM demonstration to the MM-program of the city of Kortrijk, Belgium, are offered.