Parameter Selection In Particle Swarm Optimization For Transportation Network Design Problem

TL;DR

This paper investigates how different parameter settings in particle swarm optimization affect solving transportation network design problems, aiming to improve efficiency and solution quality.

Contribution

It introduces a heuristic PSO-based algorithm tailored for transportation network design and evaluates its performance under various parameter configurations.

Findings

Parameter tuning significantly impacts PSO effectiveness.

Optimal PSO parameters improve solution quality and convergence speed.

The proposed method offers a practical approach for complex transportation planning problems.

Abstract

In transportation planning and development, transport network design problem seeks to optimize specific objectives (e.g. total travel time) through choosing among a given set of projects while keeping consumption of resources (e.g. budget) within their limits. Due to the numerous cases of choosing projects, solving such a problem is very difficult and time-consuming. Based on particle swarm optimization (PSO) technique, a heuristic solution algorithm for the bi-level problem is designed. This paper evaluates the algorithm performance in the response of changing certain basic PSO parameters.