NDLI: Public transport network optimization based on a Multi-objective Optimization Problems Evolutionary Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Hou Lin Li Wen-yong Ma Li Xu Jian-min
Copyright Year	2009
Description	Author affiliation: School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, 541004, China (Hou Lin; Li Wen-yong; Ma Li) \|\| College of Traffic and Communications, South China University of Technology, Guangzhou 510641, China (Xu Jian-min)
Abstract	Considering the benefits of passengers and bus corporations, this paper established a mathematical model of public transport network optimization. A Multi-objective Optimization Problems Evolutionary Algorithm (MOPEA) is presented to solve optimization problems in the public transport network. In this algorithm, the theory of particle system changing from non-equilibrium to equilibrium is used to define the Rank function and Niche function, so all the individuals in the population have chance to participate in the evolving operation such as crossover and mutation to solve the global Pareto optimal solutions of public transport network optimization problems. This algorithm can avoid premature phenomenon of public transport network optimization problems. At the same time, diversity of objective functions is reserved. This algorithm can gain compromise optimal results of conflicting multi-objective optimization problem—Pareto optimal front, and avoid changing multi-objective functions into one objective function by inducting experiential weight coefficient. At last, an example was given and the result showed that this algorithm had more advantages than traditional evolutionary algorithms.
Starting Page	4408
Ending Page	4412
File Size	204970
Page Count	5
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5192410
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Extraterrestrial phenomena Genetic mutations Transportation Evolutionary computation Telecommunication traffic Pareto optimization MOPEA Educational institutions network optimization Equations Design optimization Genetic algorithms Pareto optimal front public transport
Content Type	Text
Resource Type	Article

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