چكيده به لاتين
Some electronic devices have a short lifespan and on the other hand, on the other hand, and variety-seeking and consumerism are increasingly growing in today’s societies. Moreover, electronic wastes contain precious substances such as gold, silver, copper, and aluminum. The proper disposal and processing of them by recycling offer considerable advantages to the environment, given the hazardous natures of such devices’ substances. The proposed reverse logistics with waste electrical and electronic equipment (WEEE) is an important task considered by researchers, the use of which offers economic benefits and reduces the environmental impacts of wastes. The present study models the electrical and electronic equipment (EEE) reverse logistics process as a bi-objective mixed-integer programming model under uncertainties. The mathematical model investigates two objectives: an economic objective and an environmental objective. The former is minimizing costs, while the latter is maximizing the environmental score by reverse logistics processes in marketing and recycling. The parameters of demand and WEEE return rate were treated as two uncertain parameters. A bi-objective scenario-based stochastic programming (SSP) approach was adopted to deal with the uncertainties, in which both objective functions were considered under possible scenarios. A case study of an electronic equipment manufacturer in Isfahan, Iran was included. The model was solved by a nominal approach, a scenario-based stochastic programming (SSP) approach and a robust scenario-based stochastic programming (RSSP) approach via the epsilon-constraint (EC) and augmented epsilon-constraint (AEC) methods to obtain optimal Pareto solutions and compare the methods. Finally, the optimal results obtained from the two approaches SSP and RSSP were evaluated. The evaluation results show a better output of both SSP and RSSP approaches using the AEC method than the EC method.
