A global satisfaction degree method for fuzzy capacitated vehicle routing problems

Carlos Alberto Franco Franco, Juan Carlos Figueroa-Garcia

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2 Scopus citations

Abstract

There are several uncertain capacitated vehicle routing problems whose delivery costs and demands cannot be estimated using deterministic/statistical methods due to a lack of available and/or reliable data. To overcome this lack of data, third–party information coming from experts can be used to represent those uncertain costs/demands as fuzzy numbers which combined to an iterative–integer programming method and a global satisfaction degree is able to find a global optimal solution. The proposed method uses two auxiliary variables
and the cumulative membership function of a fuzzy set to obtain real–valued costs and demands prior to find a deterministic solution and then iteratively find an equilibrium between fuzzy costs/demands via α and λ. The performed experiments allow us to verify the convergence of the proposed algorithm no matter the initial selection of parameters and the size of the problem/instance.
Original languageEnglish
Article number6
Pages (from-to)1-12
Number of pages13
JournalHeliyon
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)

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