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F. Torfi, R. Z. Farahani and N. Hedayat, “A New Model to Determine the Weights of Multiple Objectives in Combinational Optimization Problems,” Proceedings of ICCESSE International Conference on Computer, Electrical, Systems Science and Engineering, 07, Paris, 2010, pp. 1933-1955.

has been cited by the following article:

• TITLE: Fuzzy Least-Squares Linear Regression Approach to Ascertain Stochastic Demand in the Vehicle Routing Problem

  AUTHORS: Fatemeh Torfi, Reza Zanjirani Farahani, Iraj Mahdavi

  KEYWORDS: Fuzzy Least-Squares, Stochastic, Location, Routing Problems

  JOURNAL NAME: Applied Mathematics, Vol.2 No.1, January 30, 2011

  ABSTRACT: Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands: approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed method can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the sto- chastic demand challenges in vehicle routing system management and solve relevant problems.