Open AccessApplication of particle swarm optimization to transportation network design problem
Author(s) -
Abbas Babazadeh,
Hossain Poorzahedy,
Saeid Nikoosokhan
Publication year - 2011
Publication title -
journal of king saud university - science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 38
eISSN - 2213-686X
pISSN - 1018-3647
DOI - 10.1016/j.jksus.2011.03.001
Subject(s) - ant colony optimization algorithms , particle swarm optimization , mathematical optimization , heuristic , metaheuristic , computer science , set (abstract data type) , bilevel optimization , network planning and design , optimization problem , mathematics , computer network , programming language
Transportation network design problem (TNDP) aims to choose from among a set of alternatives (e.g., set of new arcs) which minimizes an objective (e.g., total travel time), while keeping consumption of resources (e.g., budget) within their limits. TNDP is formulated as a bilevel programming problem, which is difficult to solve on account of its combinatorial nature. Following a recent, heuristic by ant colony optimization (ACO), a hybridized ACO (HACO) has been devised and tested on the network of Sioux Falls, showing that the hybrid is more effective to solve the problem. In this paper, employing the heuristic of particle swarm optimization (PSO), an algorithm is designed to solve the TNDP. Application of the algorithm on the Sioux Falls test network shows that the performance of PSO algorithm is comparable with HACO
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