Differential Evolution Algorithm Based Solution Approaches for Solving Transportation Network Design Problems

Abstract

Differential Evolution algorithm has effectively been used to solve engineering optimization problems recently. The Differential Evolution algorithm, which uses similar principles with Genetic Algorithms, is more robust on obtaining optimal solution than many other heuristic algorithms with its simpler structure. In this study, Differential Evolution algorithm is applied to the transportation network design problems and its effectiveness on the solution is investigated. In this context, Differential Evolution based models are developed using bi-level programming approach for the solution of the transportation network design problem and determination of the on-street parking places in urban road networks. In these models, optimal investment and parking strategies are investigated on the upper level. On the lower level, deterministic traffic assignment problem, which represents drivers' responses, is solved using Frank-Wolfe algorithm and VISUM traffic modeling software. In order to determine the effectiveness of the proposed models, numerical applications are carried out on Sioux-Falls test network. Results showed that the Differential Evolution algorithm may effectively been used for the solution of transportation network design problems.