Artificial Intelligence in Highway Location and Alignment Optimization

This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph.Contents:About the AuthorsOverview of Highway Location and Alignment Optimization Problem:IntroductionHighway Cost and ConstraintsReview of Artificial Intelligence-based Models for Optimizing Highway Location and Alignment DesignHighway Alignment Optimization with Genetic Algorithms:Modeling Highway Alignments with GAsHighway Alignment Optimization FormulationConstraint Handling for Evolutionary AlgorithmsHighway Alignment Optimization Through Feasible GatesPrescreening and Repairing in Highway Alignment OptimizationOptimizing Simple Highway Networks: An Extension of Genetic Algorithms-based Highway Alignment Optimization:Overview of Discrete Network Design ProblemsBi-level Highway Alignment Optimization within a Small Highway NetworkBi-level HAO Model Application ExampleHighway Alignment Optimization Model Applications and Extensions:HAO Model Application in Maryland Brookeville Bypass ProjectHAO Model Application in US 220 Project in MarylandHAO Model Application to Maryland ICC ProjectRelated Developments and ExtensionsAppendices:Notation Used in the MonographTraffic Inputs to the HAO Model for the ICC Case StudyReferencesIndex
Readership: The monograph is a valuable reference for graduate and postgraduate researchers who seek to solve transportation system and network optimization problems using Artificial Intelligence techniques. Artificial Intelligence;Genetic Algorithms;GAs;Highway Location Search and Selection;Alignment Optimization;Horizontal Alignments;Vertical Alignments;Three-Dimensional Highway Alignments;Bi-Level Optimization;Sustainable Highway Design;Highway Planning;Highway Life Cycle Costs;Geographic Information Systems0Key Features:This monograph deals with Artificial Intelligence-based optimization methods for highway location selection and alignment design and evaluation. It will be useful for graduate and postgraduate researchers who seek transportation system evaluation and network optimization with AI techniques. The monograph will also provide highway location engineers and planners with insight on determining the best highway location and alignments, given various resources (such as terrain, land use, geometry, and traffic data) available in early stages of a new highway development. Note that the GA-based HAO method highlighted in the monograph can offer well optimized candidate alternatives developed with automated GIS data extraction and comprehensive evaluation procedures, rather than merely satisfactory alternatives. Furthermore, it can greatly reduce the cost and time required for the traditional highway design processThe authors are highly qualified in the field of transportation system evaluation and optimization. Their collective backgrounds in solving transportation problems, performing research to develop new formulations and methods in transportation, and knowledge of AI tools, is extremely strongNo other book is available in transportation engineering communities that comprehensively reviews optimization methods for highway location selection and alignment design with emphasis on an AI-based HAO model and its real-world applications