CREDIBILITY-BASED FUZZY PROGRAMMING MODELS TO SOLVE THE BUDGET-CONSTRAINED FLEXIBLE FLOW LINE PROBLEM

Abstract

This paper addresses a new version of the exible ow line prob- <br />lem, i.e., the budget constrained one, in order to determine the required num- <br />ber of processors at each station along with the selection of the most eco- <br />nomical process routes for products. Since a number of parameters, such as <br />due dates, the amount of available budgets and the cost of opting particular <br />routes, are imprecise (fuzzy) in practice, they are treated as fuzzy variables. <br />Furthermore, to investigate the model behavior and to validate its attribute, <br />we propose three fuzzy programming models based upon credibility measure, <br />namely expected value model, chance-constrained programming model and <br />dependent chance-constrained programming model, in order to transform the <br />original mathematical model into a fuzzy environment. To solve these fuzzy <br />models, a hybrid meta-heuristic algorithm is proposed in which a genetic al- <br />gorithm is designed to compute the number of processors at each stage; and <br />a particle swarm optimization (PSO) algorithm is applied to obtain the op- <br />timal value of tardiness variables. Finally, computational results and some <br />concluding remarks are provided.