OCNEDec 22, 2014

Parameter Selection In Particle Swarm Optimization For Transportation Network Design Problem

arXiv:1412.7185v33 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental study for transportation planners, focusing on parameter tuning in an existing method.

The paper tackles the transportation network design problem by evaluating how changes in particle swarm optimization (PSO) parameters affect algorithm performance, but it does not provide concrete numerical results.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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