Artificial intelligence in highway location and alignment optimization: applications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments

Contents:

About the Authors
Overview of Highway Location and Alignment Optimization Problem:
Introduction
Highway Cost and Constraints
Review of Artificial Intelligence-based Models for Optimizing Highway Location and Alignment Design
Highway Alignment Optimization with Genetic Algorithms:
Modeling Highway Alignments with GAs
Highway Alignment Optimization Formulation
Constraint Handling for Evolutionary Algorithms
Highway Alignment Optimization Through Feasible Gates
Prescreening and Repairing in Highway Alignment Optimization
Optimizing Simple Highway Networks: An Extension of Genetic Algorithms-based Highway Alignment Optimization:
Overview of Discrete Network Design Problems
Bi-level Highway Alignment Optimization within a Small Highway Network
Bi-level HAO Model Application Example
Highway Alignment Optimization Model Applications and Extensions:
HAO Model Application in Maryland Brookeville Bypass Project
HAO Model Application in US 220 Project in Maryland
HAO Model Application to Maryland ICC Project
Related Developments and Extensions
Appendices:
Notation Used in the Monograph
Traffic Inputs to the HAO Model for the ICC Case Study
References
Index

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.