A Cultural Algorithm for the Urban Public Transportation (original) (raw)
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Cultural Algorithm to improve the generation of paths for the Public Transportation in Leon City
Abstract. In the last years the population of Leon City, located in the state of Guanajuato in Mexico, has been considerably growing, causing habitants to occupy most of their time in public transportation. As a consequence of the demographic increase and bottleneck traffic, users deal with the daily problem of optimizing their time to get on time to their destiny. To give a solution to this problem of obtaining an optimized route between two points in a public transportation, a method based on the cultural algorithms technique is proposed.
Intelligent Application to Reduce Transit Accidents in a City Using Cultural Algorithms
Distributed Computing and Artificial Intelligence, 2013
Ciudad Juárez, a large city located along the Mexico-United States border with a population over a million people in 87 km 2 has recently experienced a history of violence and insecurity related directly to organized crime: assaults, kidnappings, multi-homicides, burglary, between others. However the second leading cause of death in the city is associated with traffic accidents: 1,377 deaths in 2011 alone. For this reason, citizens have actively pursued specific programs that would decrease the overwhelming statistics: 3,897 deaths from 2008 to 2012. The reason of the following project is to provide drivers with a technological tool with indicators and sufficient information based off statistics compiled by the Centro de Investigaciones Sociales (Social Research Centre) at Autonomous University of Ciudad Juárez and other public sources. Then drivers would have more information on possible traffic accidents before they happened. This research tries to combine a Mobile Device based on Cultural Algorithms and Data Mining to determine the danger of suffering a traffic accident in a given part of the city during a specific time.
Accommodating user preferences in the optimization of public transport travel
… Journal of Simulation Systems, Science & …, 2004
Traffic congestion is becoming a serious problem in more and more modern cities. Encouraging more private-vehicle drivers to use public transportation is one of the most effective and economical ways to reduce the ever increasing congestion problem on the streets (Hartley and Bargiela, 2001). To make public transport services more attractive and competitive, providing travellers with individual travel advice for journeys becomes crucial. However, with the massive and complex network of a modern city, finding one or several suitable route(s) according to user preferences from one place to another is not a simple task. In this paper, the author presents and compares two solutions to accommodate public transport users' preferences. The first approach is using three different single-purpose shortest path algorithms to accommodate three different user preferences. And the second approach is using the K-shortest paths algorithm to compute a reasonable number of ranked shortest paths, with the ultimate 'most optimal' path being selected by consideration of the preferences. Some experiments have been done based on the public transportation network of Nottingham City.
Research of Intelligent Model of Optimal Route for the Urban Public Transport
With the vigorous development of economics, urban transportation construction is continuing to expand and the need for traffic travel is increasing. The key solutions to relieve the over-crowdedness of urban traffic reside in the following aspects: to give priority to the development of public transport; to scientifically organize the public transportation resources for operations; to maximize the advantages of public transport; and to improve the overall efficiency and service levels of the public transport system. In this paper we first discuss the stateof-arts of researches on domestic and international urban public transport systems. Based on our discussion, we analyze the urban public transport network architecture from aspects such as the basic components of public transport network, and the characteristics of public transport network, etc. In addition, we judge comprehensively according to the preference for the passengers travel choices, transit network model characteristics and time cost. Combined with the survey of Shanghai residents on travel habits, we verified and analyzed the constraints of passengers travel decision-making factors. Through comparative analysis, based on the ISM analysis method we can effectively analyze the psychology and the principle of optimal choice of passenger travel, and by the algorithm of proposed model, this paper provides ideas for the shift of transit mode of passengers travel route from a traditional mode to a multi-modal one.
TRANSASIST is an intelligent system for the management of circulations in urban environment, based on modern information and communication technologies at European standards level. The system manages different types of information regarding the urban transport and integrates GIS environment for work with vectorial digital maps, multimedia techniques, solutions for complex data acquisition and wireless communication technologies. TRANSASIST is a dynamic system that allows on-line information and management of complex data structures regarding the urban road transport infrastructure and characteristics. In the TRANSASIST system development, a modern approach based on UML technology has been used. TRANSASIST helps citizens to travel across urban areas by finding the best route between two points offering solutions for public transport, private transport and pedestrian movement. Gabriela Rodica Hrin, PhD engineer mathematician, is General Director of the National Institute for Research ...
Logistics using a new Paradigm: Cultural Algorithms
Programación matemática y software
Hoy en día la cuestión logística es muy importante dentro de las empresas en la medida algunas de ellas cuentan con departamentos exclusivamente dedicados a dicha área. Esto ha ido evolucionando con el tiempo, de modo que hoy es un aspecto fundamental de los negocios en la lucha por consolidarse o seguir siendo líderes en su campo. De acuerdo a lo anterior, sabemos que la logística puede ser dividida en diferentes clases, sin embargo, en este sentido nuestro estudio se basa en la distribución oportuna de los clientes con el menor costo, mayores ventas y mejor utilización del espacio resultando en un excelente servicio. Por último, se prepara un análisis comparativo de los resultados con respecto a otro método de optimización del espacio de soluciones.
Dynamic Trip Planner for Public Transport Using Genetic Algorithm
Transport
This paper reports the development of a public transport trip planner to help the urban traveller in planning and preparing for his commute using public transportation in the city. A Genetic Algorithm (GA) approach that handles real-time Global Positioning Systems (GPS) data from buses of the Metropolitan Transport Corporation (MTC) in Chennai City (India) has been used to develop the planner. The GA has been shown to provide good solutions within the problem’s computation time constraints. The developed trip planner has been implemented for static network data first and subsequently extended to use real-time data. The “walk mode” and Chennai Mass Rapid Transit System (MRTS) have also been included in the geospatial database to extend the route-planner’s capabilities. The algorithm has subsequently been segmented to speed up the prediction process. In addition, a temporal cache has also been introduced during implementation, to handle multiple queries generated simultaneously. The r...
Public Transportation Algorithm for an Intelligent Routing System
16th ITS World …, 2009
Due to the high complexity of the required calculations, Intelligent Routing Systems have to apply latest Operations Research techniques to be able to create routes efficiently. This paper proposes a solution to the Multi Path Orienteering Problem with ...
Technical Journal, 2019
In road networks, it is imperative to discover a shortest way to reach the final destination. When an individual is new to a place, lots of time is wasted in finding the destination. With the advancement of technology, various navigation applications have been developed for guiding private vehicles, but few are designed for public transportation. This study is solely concentrated on finding the possible shortest path in terms of minimum time and cost to reach specific destination for an individual. It requires an appropriate algorithm to search the shortest path. With the implementation of Dijkstra’s algorithm, the shortest path with respect to minimum travel time and travel cost was computed. Public transportation network of Pokhara city was taken for the case study of this research. The results of this analysis indicated that when the “time” impedance was used by the algorithm, it generated the shortest path between the origin and destination along with the path to be followed. Th...
TELKOMNIKA Telecommunication Computing Electronics and Control, 2018
Currently, the existence of city transport is increasingly eliminated by private vehicles such as cars and motorcycles. This situation is further exacerbated by the behavior of city transport drivers who are less discipline in driving, or in picking up and dropping off their passengers. The bad behavior is partly caused by the low level of passenger occupancy. The drivers try to search for passengers as much as possible but often ignore the traffic rules. To overcome this problem, an optimal transport route with high passenger potential is required. Therefore, this study investigated the optimal route of city transport based on the passenger occupancy rate in the city of Bandung as the case study. The method employed for determining the optimal route is Genetic algorithm combined with Ordinary Kriging method used for the process of passenger prediction and fitness calculation. The optimal routes are those with higher occupancy rate. The analysis results showed that the use of the Genetic algorithm with a low numb er of generations succeed in creating new optimal routes even though the increase is not too high the maximum only reaches 4%.This result is certainly important enough to be used in making better public transport routes.