چكيده به لاتين
Production is a common operation that has been used for many years. Production operation performs by using the resources and consumption of resources increases by increasing production. Therefore, using of these resources requires precise planning. Returning products to production cycles will reduce resource costs. In addition, reducing the production costs, the existence of a system for collecting and recycling the used-products, especially focusing on the products that take a very long time in nature to be decomposed, is in line with environmental objectives. Besides, this network is profitable for investors. In supply chain networks, there is an uncertainty in the demand and the returned-product from customers. The models in addition to uncertainty, determine the optimal number and location of facilities and the flow between them. The supply chain includes all of the activities that are effective in supplying customer requirements. The network of the papers reviewed in this study are including forward and reverse, reverse, and supply chain. In this research, the model was solved with exact solutions by using the LINGO software. The proposed model is multi objective optimization problem, so was solved by e-constraint method, also this problem was solved by Non-Dominated Sorting Genetic Algorithm II (NSGAII). For more efficiency of meta-heuristics algorithms, the parameters of algorithms are tuned by Taguchi method. After tuning the parameters, the model with different dimensions was coded by MATLAB software. After that, the result obtained from LINGO and MATLAB software are compared. In small-scale problems, solving by exact methods and in large-scale problems, solving by Meta-heuristics algorithm are more efficient.
