Dynamic Traffic Assignment: Genetic Algorithms Approach

作者: Adel W. Sadek , Brian L. Smith , Michael J. Demetsky

DOI: 10.3141/1588-12

关键词: Routing (electronic design automation)Nonlinear programmingReal-time Control SystemDistributed computingEngineeringAssignment problemRoad trafficSoftwareOperations researchRelaxation (approximation)

摘要: Real-time route guidance is a promising approach to alleviating congestion on the nation's highways. A dynamic traffic assignment model central development of strategies. The artificial intelligence technique genetic algorithms (GAs) used solve developed for real-world routing scenario in Hampton Roads, Virginia. results GA are presented and discussed, performance program compared with an example commercially available nonlinear programming (NLP) software. Among main conclusions that GAs offer tangible advantages when problem. First, allow relaxation many assumptions were needed problem analytically by traditional techniques. can also handle larger problems than some NLP software packages.

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