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Springer Optimization Models and Methods for Equilibrium Traffic Assignment

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Description

This comprehensive guide explores the traffic assignment problem through mathematical and practical perspectives, offering readers new approaches, methods and algorithms developed by the authors over several years of research and publication. The book presents original methodological techniques alongside prospective implementations designed to solve real-world traffic challenges. Tailored for civil engineering students, traffic engineers and algorithm developers, this work provides rigorous analysis of variables, functions and fundamental principles governing traffic systems. Part of the Springer Tracts on Transportation and Traffic series (Volume 15), it combines theoretical foundations with practical applications to advance understanding of equilibrium traffic assignment. Whether you're developing traffic assignment algorithms, managing urban transport networks or studying advanced civil engineering topics, this text delivers the technical depth and innovative solutions needed to address complex transportation problems.

Key Features

Focuses on traffic assignment problems with detailed examination of mathematical and practical variables, functions and basic principles underlying transportation systems.

Presents original methodological techniques and new algorithms developed by the authors through years of research and publication in transportation engineering.

Designed for civil engineering students, traffic engineers and algorithm developers seeking advanced knowledge in equilibrium traffic assignment methods.

Part of the Springer Tracts on Transportation and Traffic series (Volume 15), establishing credibility within academic and professional transportation circles.

Includes prospective implementations and practical approaches to apply theoretical concepts in real-world traffic management and network optimisation scenarios.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
06 December 2020
Listed Since
10 November 2020

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