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A novel hybrid PSO-ACO approach with its application to SPP

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Abstract

State-of-the-art in the area of shortest path problem (SPP) is considered to propose a novel hybrid approach, realized based on the well-known particle swarm optimization in association with ant colony optimization. The subject addressed in the present research is worthy of investigation due to the fact that efficient outcomes may be useful, in so many academic and industrial environments, which are encountered optimized path problems. Based on the matter presented, a number of applications of the SPP are in vehicle routing in the transportation systems, traffic routing in the communication networks and path planning in the VLSI design. Regarding the approach considered here, it should be noted that the main aim is to find the SPP between specified point and corresponding destination one, as long as some static obstacles are assumed in terrain. The properties of the present model enable us to organize a meta-heuristic in line with ant colony algorithms to solve the shortest path design. Subsequently, in order to evaluate the proposed approach, the investigated results are compared with other meta-heuristic algorithms. Computational results illustrate that the efficiency of the proposed approach is desirable with respect to other related techniques.

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Acknowledgments

The present corresponding author would like to express the best and the warmest regards to respected Editors of “Evolving System”, Springer Publisher and also the whole of respected potential reviewers, for suggesting their impressive, desirable and technical comments on the present investigation. Afterwards, we are grateful to the Islamic Azad University (IAU), South Tehran Brach in supporting the present research. Finally, the corresponding author appreciates Mrs. Maryam Aghaei Sarchali, Mohadeseh Mazinan and also Mohammad Mazinan for their sufficient supports in the process of paper investigation and organization.

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Authors and Affiliations

  1. Department of Control Engineering, Faculty of Electrical Engineering, South Tehran Branch, Islamic Azad University (IAU), No. 209, North Iranshahr St., P.O. Box 11365/4435, Tehran, Iran

    A. H. Mazinan

  2. Department of Control Engineering, South Tehran Branch, Islamic Azad University (IAU), No. 209, North Iranshahr St., P.O. Box 11365/4435, Tehran, Iran

    F. Sagharichiha

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  1. A. H. Mazinan
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  2. F. Sagharichiha
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Correspondence to A. H. Mazinan.

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Mazinan, A.H., Sagharichiha, F. A novel hybrid PSO-ACO approach with its application to SPP. Evolving Systems 6, 293–302 (2015). https://doi.org/10.1007/s12530-014-9126-9

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