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Hybrid Meta‐Heuristic Algorithm for the Simultaneous Optimization of the O–D Trip Matrix Estimation
Author(s) -
Stathopoulos Antony,
Tsekeris Theodore
Publication year - 2004
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.2004.00367.x
Subject(s) - simulated annealing , algorithm , convergence (economics) , genetic algorithm , mathematical optimization , matrix (chemical analysis) , computer science , heuristic , greedy algorithm , optimization algorithm , local search (optimization) , rate of convergence , mathematics , materials science , computer network , channel (broadcasting) , economics , composite material , economic growth
In the present article, the origin–destination (O–D) trip matrix estimation is formulated as a simultaneous optimization problem and is resolved by employing three different meta‐heuristic optimization algorithms. These include a genetic algorithm (GA), a simulated annealing (SA) algorithm, and a hybrid algorithm (GASA) based on the combination of GA and SA. The computational performance of the three algorithms is evaluated and compared by implementing them on a realistic urban road network. The results of the simulation tests demonstrate that SA and GASA produce a more accurate final solution than GA, whereas GASA shows a superior convergence rate, that is, faster improvement from the initial solution, in comparison to SA and GA. In addition, GASA produces a final solution that is more robust and less dependent on the initial demand pattern, in comparison to that obtained from a greedy search algorithm.
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