No abstract

This work presents our research and implementation of the School Bus Routing Problem applied to the rural area of a brazilian city. We use a complete set of real georeferenced data containing a sample of 944 students, 23 schools, and the full road network of a city of population of 280,000 inhabitants occupying an area of 2,348 km 2 . Our goal is to optimize the daily transportation of students considering the real publicly available fleet composed of heterogeneous vehicles. As our solution is being evaluated for application over the entire country, we have included some 'quality' parameters for tunning the application to distinct economic/social realities. A mixed integer linear programming model and a GRASP based algorithm are proposed to solve the routing problem.

No abstract

No abstract

No abstract

No abstract

In this work we tackle the bus stop selection step for the School Bus Routing Problem (SBRP). Our goal is to minimize the number of bus stops in order to assign all students to a bus stop respecting a home-to-bus-stop walking distance constraint. Our strategy creates a large number of possible bus stops points in a road network and uses a pseudo-random constructive heuristic algorithm to assign students to a bus stops. Our approach is tested on a real georeferenced data of a brazilian city and is compared with a different methodology. Results demonstrate that the proposed approach is able to find good solutions for this optimization problem. Besides,the higher the number of possible points to install bus stops, the smaller is the number of bus stops required to attend all students.

† Current address: Rod. MG-443 km 7, Fazenda do Cadete, Ouro Branco-MG, room 107.2, CE 36420-000, Brazil. ‡ These authors contributed equally to this work.Abstract: Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of the Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. We compare the proposed strategies to the intuitive strategy of allocating communication units at the most popular zones of the road network. Experiments show that the strategies derived from the general heuristic provide higher coverage than the intuitive strategy when using the same number of communication devices. Moreover, the resulting pattern of coverage is very interesting, with roadside units deployed a circle pattern around the traffic epicenter. safety, real estate, transportation, and utilities-more inteligent". Nam and Pardo [2] group key conceptual components of smart cities into three categories of core factors: Technology (infrastructures of hardware and software), people (creativity, diversity, and education), and institution (governance and policy). Given the connection between the factors, a city is smart when investments in human/social capital and IT infrastructure fuel sustainable growth and enhance a quality of life, through participatory governance [3].Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050 [4]. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In fact, several researches are already in advanced state: The development of autonomous vehicles [5] combined with car-sharing services [6] may shape a new automotive industry, and introduce a new paradigm in the way we use vehicl...