Development of practical urban routing systems with an improved genetic algorithm

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Development of practical urban routing systems with an improved genetic algorithm


Author: Liu, Yingbo
Title: Development of practical urban routing systems with an improved genetic algorithm
Degree: M.Sc.
Year: 2012
Subject: Transportation engineering.
Geographic information systems.
Urban transportation.
Choice of transportation -- Mathematical models.
Genetic algorithms.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Mechanical Engineering
Pages: xii, 175 leaves : ill. (chiefly col.) ; 30 cm.
Language: English
InnoPac Record:
Abstract: With the fast development of science and technology as well as economy, urbanization has been quickly deepened. Therefore, private cars have more and more become the major method for people's transportation. However, with the increasing vehicles, traffic jam is becoming more and more serious. To solve this problem, without enlarging existing traffic paths, optimal urban routing system could be one effective solution. The problem of searching the shortest route between two nodes is a well-known problem. Many shortest route algorithms have been proposed in the literature under various conditions and constraints. With the planning of road design organizations, by combining the data of geology, and together with the overall urban planning and the distribution of economic regions, the urban road network has been gradually established. But with the development of urban construction, increasing population and more and more complicated traffic networks, this design can nevertheless meet the needs of current transportation loads, and public traffic systems are thus frequently obstructed. In order for optimal routing selection and avoiding traffic jam, traditional GPS navigation features certain significance, but it only takes the shortest route into consideration. Although it could highlight certain reference value, it is on the other hand a blind searching process without online and realtime modification. Therefore, a more systematic optimal urban routing system is yet to be investigated, especially for a complicated rapidly-changing urban road network. Genetic algorithm is an optimal algorithm with random searching mechanisms that imitate biological genetic evolution and natural selection process. Many traditional search algorithms are only single-point searching ones and thus easily fall into local minimum solution. Genetic algorithm deals with many individuals in a group at the same time, which is to evaluate several solutions in the searching space. Thus, it can reduce the risk of local minimum solution and benefit the overall optimization.
Based on genetic algorithm and several constrained conditions, this study establishes an optimal urban routing system. To this objective, traditional genetic algorithms are improved in this study to overcome its defects such as slow convergence rate and easily being traped into local minimum. Through examples of road networks, comparisons between traditional algorithms and the improved genetic algorithm are conducted, thus proving that the improved GA is feasible and effective. In establishing the optimal routing system, we also consider many restraints on routing selection, such as peak hour, raining and snowing, to make the system more realistic and efficient, thus changing people's concept about traditional routing systems. At last, this study establishes a practical optimal routing system for Weihai City with the improved GA. This disseration mainly consists of four chapters. The first chapter introduces the research background and the state-of-the-art development of optimal routing systems, and also discusses the defects of the existing research, thus defining the objectives and significance of this study. The second chapter introduces traditional genetic algorithms, provides the expression and the mathematic model of road network to solve problems, then improves the traditional algorithms, conducts experimental simulations and confirms the effectiveness of the improved GA. The third chapter lists the manufacturing process and functions of the system in details, and also establishes the optimal routing system for Weihai City. The fourth chapter provides some discussions about the advantages and disadvantages of the methods adopted in this study, as well as the outlook of the future. A conclusion is drawn at last.

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