Robust shortest path problem based on a confidence interval in fuzzy bicriteria decision making

Takashi Hasuike*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


This paper proposes a model for a robust shortest path problem with random edge costs. The proposed model is formulated as a bicriteria optimization problem to minimize the total cost of the path from a start node to an end node as well as to maximize the range of the confidence interval satisfying the condition that the total cost of any path in the region is less than a target value in terms of robustness. It is not always the case that a solution that simultaneously optimizes all of the objectives exists when the objectives conflict with each other. In this paper, fuzzy goals for both objectives and the aggregation function are introduced in a solution approach that considers the decision maker's preference and the subjectivity of her or his judgment in multicriteria decision making. The fuzzy bicriteria problem is transformed into a constrained shortest path problem. Furthermore, an exact algorithm based on Dijkstra's algorithm and a heuristic algorithm based on the Lagrange relaxation-based algorithm are developed for the constrained shortest path problem.

Original languageEnglish
Pages (from-to)520-533
Number of pages14
JournalInformation Sciences
Publication statusPublished - 2013 Feb 1
Externally publishedYes


  • Bicriteria decision making
  • Confidence interval
  • Fuzzy goal
  • Robust programming
  • Shortest path problem

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence


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