APPLIED DATA MINING IN TTRP WITH FUZZY DEMANDS AND CAPACITIES

Abstract

Recently, the Truck and Trailer Routing Problem (TTRP) has been tackled with uncertainty in the coefficients of constrains. In order to solve this problem it is necessary to use methods for comparison fuzzy numbers. The problem of ordering fuzzy quantities has been addressed by many authors and there are many indices to perform this task. However, it is impossible to give a final answer to the question on what ranking method is the best in this problem. In this paper we focus our attention on a model to characterize TTRP instances. We use a data mining algorithm to derive a decision tree that determined the best method for comparison based on the characteristics of the TTRP problem to be solved.