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Solving the Median Shortest Path Problem in the Planning and Design of Urban Transportation Networks Using a Vector Labeling Algorithm

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  • Kali Prasad Nepal
  • Dongjoo Park

Abstract

This paper proposes an alternative algorithm to solve the median shortest path problem (MSPP) in the planning and design of urban transportation networks. The proposed vector labeling algorithm is based on the labeling of each node in terms of a multiple and conflicting vector of objectives which deletes cyclic, infeasible and extreme-dominated paths in the criteria space imposing cyclic break (CB), path cost constraint (PCC) and access cost parameter (ACP) respectively. The output of the algorithm is a set of Pareto optimal paths (POP) with an objective vector from predetermined origin to destination nodes. Thus, this paper formulates an algorithm to identify a non-inferior solution set of POP based on a non-dominated set of objective vectors that leaves the ultimate decision to decision-makers. A numerical experiment is conducted using an artificial transportation network in order to validate and compare results. Sensitivity analysis has shown that the proposed algorithm is more efficient and advantageous over existing solutions in terms of computing execution time and memory space used.

Suggested Citation

  • Kali Prasad Nepal & Dongjoo Park, 2005. "Solving the Median Shortest Path Problem in the Planning and Design of Urban Transportation Networks Using a Vector Labeling Algorithm," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(2), pages 113-133, April.
    • Handle: RePEc:taf:transp:v:28:y:2005:i:2:p:113-133
    DOI: 10.1080/03081060500053509
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    Cited by:

    1. Miranda, Pablo A. & Blazquez, Carola A. & Obreque, Carlos & Maturana-Ross, Javier & Gutierrez-Jarpa, Gabriel, 2018. "The bi-objective insular traveling salesman problem with maritime and ground transportation costs," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1014-1036.

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