Title: Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model

Authors: Hanzel Grillo; David Peidro; M.M.E. Alemany; Josefa Mula

Addresses: Research Centre on Production Management and Engineering (CIGIP), Polytechnic University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain ' Research Centre on Production Management and Engineering (CIGIP), Polytechnic University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain ' Research Centre on Production Management and Engineering (CIGIP), Polytechnic University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain ' Research Centre on Production Management and Engineering (CIGIP), Polytechnic University of Valencia, Camino de Vera s/n, 46022 Valencia, Spain

Abstract: Traditionally, supply chain planning problems consider variables with uncertainty associated with uncontrolled factors. These factors have been normally modelled by complex methodologies where the seeking solution process often presents high scale of difficulty. This work presents the fuzzy set theory as a tool to model uncertainty in supply chain planning problems and proposes the particle swarm optimisation (PSO) metaheuristics technique combined with a backward calculation as a solution method. The aim of this combination is to present a simple effective method to model uncertainty, while good quality solutions are obtained with metaheuristics due to its capacity to find them with satisfactory computational performance in complex problems, in a relatively short time period.

Keywords: metaheuristics; particle swarm optimisation; PSO; backward calculation; fuzzy set theory; master planning; bioinspired computation; fuzzy logic; supply chain planning; supply chain management; SCM; uncertainty modelling.

DOI: 10.1504/IJBIC.2015.069557

International Journal of Bio-Inspired Computation, 2015 Vol.7 No.3, pp.157 - 169

Received: 18 Sep 2014
Accepted: 07 Jan 2015
Published online: 26 May 2015 *

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