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Determining Optimal Link Capacity Expansions in Road Networks Using Cuckoo Search Algorithm with Lévy Flights

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  • Ozgur Baskan

Abstract

During the last two decades, Continuous Network Design Problem (CNDP) has received much more attention because of increasing trend of traffic congestion in road networks. In the CNDP, the problem is to find optimal link capacity expansions by minimizing the sum of total travel time and investment cost of capacity expansions in a road network. Considering both increasing traffic congestion and limited budgets of local authorities, the CNDP deserves to receive more attention in order to use available budget economically and to mitigate traffic congestion. The CNDP can generally be formulated as bilevel programming model in which the upper level deals with finding optimal link capacity expansions, whereas at the lower level, User Equilibrium (UE) link flows are determined by Wardrop’s first principle. In this paper, cuckoo search (CS) algorithm with Lévy flights is introduced for finding optimal link capacity expansions because of its recent successful applications in solving such complex problems. CS is applied to the 16-link and Sioux Falls networks and compared with available methods in the literature. Results show the potential of CS for finding optimal or near optimal link capacity expansions in a given road network.

Suggested Citation

  • Ozgur Baskan, 2013. "Determining Optimal Link Capacity Expansions in Road Networks Using Cuckoo Search Algorithm with Lévy Flights," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-11, September.
    • Handle: RePEc:hin:jnljam:718015
    DOI: 10.1155/2013/718015
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    Cited by:

    1. Ziyi Zhou & Min Yang & Fei Sun & Zheyuan Wang & Boqing Wang, 2021. "A Continuous Transportation Network Design Problem with the Consideration of Road Congestion Charging," Sustainability, MDPI, vol. 13(13), pages 1-16, June.
    2. İnayet Özge Aksu & Tuğçe Demirdelen, 2022. "The New Prediction Methodology for CO 2 Emission to Ensure Energy Sustainability with the Hybrid Artificial Neural Network Approach," Sustainability, MDPI, vol. 14(23), pages 1-29, November.
    3. Lozano, Jorge-Mario & Zuluaga, Santiago & Sánchez-Silva, Mauricio, 2020. "Developing flexible management strategies in infrastructure: The sequential expansion problem for infrastructure analysis (SEPIA)," Reliability Engineering and System Safety, Elsevier, vol. 200(C).

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