Fuzzy optimal search methods

Can Işik, Salwa Ammar

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper gives analytical approaches and algorithms for decision tree search techniques. The decision trees are assumed to have a fixed number of stages and predefined possible states at every stage. The costs of traversing the tree are characterized as approximate and defined as fuzzy numbers. Two search methods, each drawing from an existing non-fuzzy search algorithm, are described. The first method is a dynamic programming search, where the principle of optimality with fuzzy costs is addressed. The second method is an A* search for which the notion of a lower bound estimate of costs is utilized to increase the efficiency of the search. Algorithms for each method are included. Theorems and proofs which complete the analytical development of these techniques are also included. Finally, a numerical example illustrating the procedure is given.

Original languageEnglish (US)
Pages (from-to)331-337
Number of pages7
JournalFuzzy Sets and Systems
Issue number3
StatePublished - Mar 26 1992


  • Search methods
  • fuzzy A search
  • fuzzy cost
  • fuzzy dynamic programming
  • operations research

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence


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